#238 Sriram Krishnan - Senior White House Policy Advisor for AI

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Sriram Krishnan.

Am I saying that right?

Perfect.

Nailed it, Sean.

Perfect.

I'm sorry.

But

man,

we've become friends over the course of the year.

And man, I've just been super excited to get you in here.

I didn't think it was going to happen until, to be honest, until the next election, because I know you're so busy with all the AI stuff within the White House.

So I just want to say, man,

it is an honor to have you here.

I've been looking forward to talking to you on the show about all the stuff that you're doing with the AI race with China and just AI in general.

Lots of questions throughout the country and lots of fear, lots of excitement,

a mixed bag of emotions here.

Like I said, I'm just, I am really excited.

And I love your backstory.

You know, we were talking at breakfast about the American dream and you came here from India and

have been a part of many empires and

you just you've done really well for yourself and your family and and that's what I love to to showcase here is the American dream and you are very much a big part of that of what that represents and and all things are possible in this country so thank you man uh well thank you and thank you Sean I mean it's an hon it's an honor for me to be here and I've watched you for I think over a year and a half you know when we first met up.

And I've just been blown away by just the stories

we both talked about at breakfast.

So many amazing people, men and women, who have just done some amazing things for this country.

And I just kind of love this space and the environment you have created.

So the honor is mine.

I'm nervous.

I'm intimidated to kind of be in this room, which is kind of...

one of the probably one of the badass most patriotic rooms I've ever been in, by the way.

No, but thank you.

I'm super excited.

Thank you.

Well, if it helps, I'm also nervous.

I get nervous for every one of these things.

Wearing a jacket, I feel so bad.

I got to wear this.

I got to wear a suit because it's part of the job.

It's part of the office.

And I'm like, man, I'm going to go to Chandra and look like a dark out there in a suit.

Oh, no.

I appreciate you.

You know, wearing the jacket.

Thank you.

Thank you.

But everybody starts off with an introduction here.

So here we go.

Sri Ram

Krishnan, appointed by President Trump, you are the senior White House Policy Advisor for Artificial Intelligence.

You're a leader in Silicon Valley with a product leadership career spanning Microsoft, Facebook, and Twitter, helping shape everything from Windows Azure to Facebook's audience network and Twitter's home timeline.

In 2021, you joined Andreessen Horowitz as a general partner, opening the firm's first international office in London focused on investing in AI and crypto.

You grew up with humble beginnings in Chennai, India, where your love for technology began when you convinced your father to buy you a computer.

With no internet access, you taught yourself to code from books.

When a Microsoft executive in India discovered one of your blog posts, you were invited to interview an opportunity that marked the beginning of an exciting professional journey in the United States.

You also co-hosted the

Arthy and Sri Ram show with your wife.

The show grew from a clubhouse talk show into a widely downloaded

top tech and business podcast.

Today at the White House, you are a key architect in America's AI action plan, leading efforts to extend the U.S.

U.S.'s global dominance in AI.

You have also participated in high-level diplomatic efforts, including AI delegations to Paris and the Middle East, advocating for the global usage of U.S.

AI tech stack.

Most importantly, you're a family man.

You've been together with your wife for 22 years,

and you even hosted a podcast together, and

you're a huge pro wrestling fan.

So we'll get into all that, but

like I said,

I want to do your backstory, your coming to the U.S., how you got into the tech, which we just covered a little bit,

and then everything you're doing now with AI.

So, like I said, a lot of excitement, a lot of fear, a lot of mixed emotions about it.

So it's going to be an amazing interview.

Thank you.

And thank you for that.

That was super kind of you.

Thank you.

Oh, my pleasure.

My pleasure.

So we got a couple of things to crank out here real quick.

All right.

One of them is I have a Patreon community and it's a subscription network, but they've been with me actually before I even started the podcast.

Then when I did the podcast, I started it in my attic.

And now here we are in a brand new studio.

And so, one of the things that I offer them to do is I offer them the opportunity to ask each and every guest a question.

So, this is from Andre.

What emerging technology or trend do you believe will have the most transformative impact on society in the next five to ten years?

And how can policymakers and innovators collaborate to maximize its benefits while addressing potential risks.

Well, thanks, Andre.

I think, you know, sort of the obvious answer for me is all things AI and artificial intelligence.

I think if you look at the last 60 to 80 years, there has been a few huge technology trends.

In the 60s and 70s, the first microprocessor was invented in Silicon Valley.

And the transistor and the microprocessor, which kind of powered Intel, the Moore's Law, and things which power every single phone, every single laptop.

Then in the 90s, you had the internet,

starting with dial-up internet, you know, using the phone line, which is kind of how I started.

People of our age group probably started.

And then now, of course, you don't talk of logging off anymore.

The internet is just everywhere.

So I think that was transformational for society in some really good ways and some maybe questionable bad ways.

Then you had the mobile phone happen in, I'm guessing, say, 2008 when the iPhone came out and everything, just people just moving everything onto that phone.

But I don't think AI now is the next big platform.

And we are in the early days of it, right?

Like I would say the AI revolution, you know, we can go back to the history and we can get into that, but I think really started with the launch of Chat GPT about two and a half years ago, where it sparked, captured people's imagination.

And now we're just starting to see, wow, like what can we do when this thing is advancing so quickly?

So I think AI is the game in town that I think is most important.

I think crypto is also really interesting, but I really spend a lot of my time thinking on AI.

And I think my job and working with others in the administration is to harness it for the American people.

Like, how do we make sure that it makes every individual's lives better,

whether it's like, you know, a dad, you know, trying to make sure they provide for the family, somebody trying to teach their kids, whatever it is, we want to make sure sure it makes their lives better.

At the same time, we're also in this very intense

race with China on all things AI, which we can get into in detail.

So I think the way I see my job is, one, we need to win the AI race with China.

I think the consequences are catastrophic.

if we don't

and second equally important is making sure like ai benefits every single american like every single person watching this, Andre, who asked the question, my hope is, you know, when my time administration is done, they're like, okay, AI is helping me in my life just a little bit.

That's the goal anyway.

Yeah, you know, I feel like with AI,

this is, I mean, we were talking about it at breakfast, but, you know, you had mentioned it's like when the automobile was invented.

I feel like this is, this is a moment in humanity like when the wheel was invented.

Everything's going to change.

And, you know, what I love about our conversation at breakfast and what I love about you is, you know, you understand the importance to win the AI race against China, but you also understand the balance that needs to happen within, you know, within not just the U.S., but within the world.

And there is a lot of fear of AI is going to take all of our jobs.

AI is going to, you know, crush everything.

And

you are the guy that has to navigate through all of that and make sure it benefits American citizens and humanity as a whole whole while simultaneously winning the race against China, which is no easy task because China plays by damn near zero rules.

And so

it's going to be a fascinating discussion.

Yes, it is.

It's super fun.

But got a couple gifts for you.

Oh, wow.

Okay.

Yeah.

One.

This is the part I was looking forward to the most.

I have no shame.

I want the gifts.

There we go.

Those are Vigilance League gummy bears made here in the USA, legal in all 50 states.

No THC or anything like that in there.

Got candy.

Yeah, yeah.

All right, let's do it.

Dying to know what you think here.

Damn.

One out of five.

Five being the best.

I'm going to say five.

Nice.

Wow.

Good answer.

Good answer.

And I got you another gift.

Oh, man.

So

I think you're really going to like this one.

Okay, wow.

Here you go.

So I got a friend over at Sig Sauer.

Do you know what Sig Sauer is?

His name's Jason.

I told him you were coming on.

He's trying to figure out AI.

So he's really looking forward to this episode, but he wanted me to give you this.

Wow.

Wait, hold on.

How do I get this open?

Here we go.

Oh, my goodness.

Okay, what am I?

Tell me, explain this to me.

All right.

So that is the, you want to hold it up?

Yeah.

It's unloaded.

I'm going to teach you how to use that.

Yeah.

Maybe you can teach me some AI stuff and I'll teach you how to shoot.

Yeah.

But so that is the Sig Sauer 211 GTO 9mm.

It's got 21 rounds in the magazine, plus one in the pipe, so 22 round capacity.

It's got that, see those slits in the front?

Yeah.

So that is to help with.

with recoil management.

So it's going to keep your gun down when you shoot.

It'll minimize recoil a little bit, keep your gun a little bit flatter.

They're redoing their whole optics optics line.

That's their latest red dot.

So using a red dot makes shooting a lot easier to hit the target.

And so in the gun industry, there's this rage about these 2011 pistols.

Everybody wants a 2011 pistol.

And Sig was...

Sig was, I don't want to say late to the game, but everybody's been really excited about what they're going to release in the 2011 series.

And so that is their first model.

This is gorgeous.

This came out.

But I'm going to ask you a favor.

And after we're done, you got to show me some of the ropes and how to use this properly.

Hey, I would love to do it.

You know, one of the things as a federal, this is gorgeous.

So thank him for me.

This is gorgeous.

And, you know, as a federal employee, you got to declare every single gift you get.

And this is going to be, I think, probably the most interesting declaration for sure.

You know, when I file in the paperwork, but no, this is gorgeous.

So thank you.

And you're going to teach me how to use this.

I will.

We'll do it on a break.

There we go.

All right.

Now, well, before we

now,

I have a gift for you.

I love gifts.

All right, let's do this.

And

thank you.

Just keep this right here.

Now,

outside of, I would say, technology, I would say one of the most important things in my life is professional wrestling.

I got...

hooked to it as a young kid, started watching it.

I think it was my introduction to America.

It was my introduction to sort of sports and entertainment.

It's been a huge part of my life.

So

I got you.

Let me get this out of here.

This guy.

No way.

Here.

Hold on.

There you go.

So this

is a

WWE title belt.

It's not just any WW title belt.

You know, fans, you know, who are watching this will know this is known as the winged eagle WWE championship belt because, or back to the WWE, so in the 90s, right?

Like they had like WWE has had, WWF back then has had many, many championship title belts.

But

connoisseurs or fans might say, and there may be some controversy on this, the best one of all time was this guy right here, right?

It has been held by greats like Breath the Headman Hart, who's my favorite guy growing up, The Undertaker, Sean Michaels, a lot of greats.

They actually had a comeback where Cody Rhodes worked recently.

It is a core, core part of my childhood.

I had it on t-shirts, everything else.

And this guy, particularly thing I'm holding in my hand, when my wife and I had this podcast for the last four years until this job, if you watch episodes, you'll see a title behind me on the shelf.

And so I grabbed that.

That's it?

Oh, yeah.

Oh, man.

So, you know, this is like some classic pro wrestling history like right here there you go man i love this there you go

wow thank you

that is amazing so that'll be displayed at the studio from here till till it's over yeah well sean uh sean's title reign starts right now do you did you watch pro wrestling much as a kid now i watched Actually, I watched it in the 90s.

Okay.

Who was your favorite?

Who was my favorite?

I don't know.

It was probably.

I went back and forth, but I really liked Hulk Hogan and the Ultimate Warrior.

R.I.P., Hulk Hogan, Terry Bollia,

Sean Michaels, Jake the Snake, all of them.

What is your favorite match that you remember?

You know what I always liked was the Survivor Series cage matches.

Yes, yes.

Which one?

Do you remember, like, for example, like, well, there was the SummerSlam one between Brett and his brother Owen, but which one?

I don't remember exactly which one, but those were always my favorite

when they would all show up.

Yeah.

I think when I was a kid, I loved those.

And I don't know what I was watching.

It was like, you know, these Lodge and Life characters.

You had Hulk Hogan.

eat your vitamins, say your prayers, train every day.

You know, the red and yellow coming out.

My guy was Brett Hart.

So Bret Hart, do you know Brett?

Oh, yeah.

Brett the Hitman Hart.

I would say if you ask people for the Mount Rushmore professional wrestling, Brett will always be in there.

He was one of the most technically savvy wrestlers of all time.

Fantastic at telling stories with his body and in the ring.

Even if you watch his matches now, it is just so incredibly crisp and smooth.

And I know we're talking about breakfast, you mentioned Stone Cold, you know, Steve Austin.

Brett was involved in maybe one of of the most important matches of Stone Cold's career, right?

Like the IQuit WrestleMania match.

Have you seen this?

No.

Oh, okay.

So this is great, right?

Like, so

I forget which year.

I'm going to say 96, but I may be off.

But so do you know what a heel and a face is in pro wrestling?

Okay.

So in professional, okay, in professional wrestling, right?

By the way, folks, spoiler, it's not real.

It's scripted.

um you know uh and it's kfab as they would say uh a kfab is sort of the reality inside professional wrestling and inside kfab a face or a baby face is the good guy and a heel um is the bad guy right like so hulk hogan right for years was always the face the red and yellow right he slams slams andre right like you know he was the face um and then the heel would be the bad guy and the heels would do evil conniving things.

You know, they would, you know, do a low blow or throw something in your eye.

Or, you know, it's one of those things where they kind of cheat to win.

Those are the bad guys.

And in the 90s, what was happening was the WW was kind of going.

maybe along with pop culture was going through the shift where often sometimes the bad guys would start to get cheered a little bit more right they were these anti-authority figures and you know you know uh and the good guys what people would call the classic uh white meat baby face right like you know we're not getting enough cheers and so in 96 you know brett um you know was i think was the i'm not sure whether he was the champion at this match but uh brett was a good guy he was a face he's one of the lead faces at the time and stone cold steve austin was kind of coming up then was a heel he was a bad guy and they kind of set up this match it's called the you know the i quit match and the idea behind this was that you know the only way for you to win is the other guy has to say, I quit.

No tap outs, no counterouts, you got to say, I quit.

And I think the match was in Chicago.

It's WrestleMania.

By the way WrestleMania is sort of WWE's big extravaganza.

It's like the Super Bowl.

It's a big event.

There's been, I think, 41 so far.

And so they have this guest referee, Ken Shamrock, who's from, I think, a mixed martial arts background back then.

So, and Brett and Steve had this amazing idea, right?

So what happens is they fight all over the ring, all over the crowd.

It's bloody, you know, Steve Austin, you know,

he starts bleeding,

cut open the hard way, it got juice, as the wrestlers would say.

And at the end, you know, Brett had his finishing move.

the shop shooter, right?

And, you know, and the shop shooter, once you're in the sharp shooter, like when I was a kid, right?

Like, even though you had this thing with like, do not try this at home, right?

Like when my cousins were over, like, I'm putting them in the shop shooter.

Kids, don't try this at home.

And, but at the end of the match, you know, you know, and you know, Steve's in this bloody mess.

Brett puts him in the shop shooter, right?

And, you know, and there's this iconic image of Steve just yelling out in pain, blood in his face, but he's not saying, I quit.

He's not saying, I submit.

And Ken Shamrock, you know, it's like, do you quit, Steve?

And he's like, no, right.

And after like minutes of Steve in agony, he refuses to quit and he passes out.

Right.

And, you know, and, you know, and they end the match there.

So

that match was crucial for both their careers because it's one of the rare matches where they did what was known as a double turn.

So a turn in pro wrestling is when a good guy becomes a bad guy, right?

Like a face becomes a heel or vice versa.

And in this match, because Brett would not let go of the hold, right?

And he would then push Sam Rock, he kind of became a bad guy.

At the same time, because Steve did not give up, he was bleeding he was in pain he never said I quit right he became a good guy and it launched Steve's career so that is sort of one of the in people ask you for the like top five matches in history like that's that's like one of the top ones so anyway so Brett so that's a great part of WWE history right there man thank you this is This is amazing, totally unexpected.

This is awesome.

I was excited.

I was excited for this.

Wrestling has been like a big, big part of my life.

I've learned so much from it.

I've learned storytelling.

I've learned

what connects to audiences.

Because a lot of people think about it and they go, oh, it's just like grown men and spandex, like throwing each other around, right?

Or they say, what you did, which is like, I used to watch it as a kid.

And I used to watch a kid.

It's great.

You watch it.

It's super fun.

I try and getting my kids to watch it.

It's great.

It's practical.

Good guys, bad guys, they're large in life.

They're huge.

They're characters.

But as I got older, right, I saw the sophistication and and the art form, right?

Like, because number one, it requires serious athletic ability, right?

These guys

and women, you know, are incredibly athletic.

They're taking real risks, right?

Like when they jump, you know.

you know, off the uh off the corner and onto a table, well, that's a real table, that's a real corner, and people have hurt themselves and you know, some really bad thing happens.

So they're taking real risks, right?

And then they're trying to tell a story, right?

And instead of a story which is through CGI and dialogue, right?

It is a story they are telling with their bodies, with some, you know, promos and dialogue, but also with the audience together.

Okay, so wrestling only works because the audience is in there with you.

And often the greatest wrestlers know to change what they're doing to get a different reaction or sometimes change something what they're doing on the fly because of the audience.

And there's a famous example of this.

You know who The Rock is, obviously.

Oh, yeah.

Okay, so by the way, I don't know what we're talking about.

Yeah, we want to get into wrestling first, okay?

And

so,

but one of the greatest WrestleMania matches of all time was in WrestleMania 17 in Toronto.

And The Rock is a good guy.

And Hulk Hogan, and The Rock's a young guy.

I think it was maybe late 20s or 30s.

He's kind of the peak of his young career.

He's a great guy.

And Hulk Hogan had come back as a bad guy.

And I think Hulk Hogan was maybe in his late 40s.

He was kind of in the slightly the tail end of his career, right?

Like he was not the red and yellow.

And this is WrestleMania, right?

And, you know, you should watch it on YouTube.

They come to the middle of the ring, they look at each other, and, you know, it's like light bulbs going off everywhere, like 100,000 people flashing, and, you know, and they just turn around, look at the audience, and people are like, oh my God, you get Hulk Hogan, one of the greats, the greatest of all time, slammed Andre the Giant.

And then you have the people Samp, you know, The Rock, right?

And so what happens, remember, the rock went in as the good guy.

Hogan is the bad guy.

Within the first 30 seconds, right, it becomes very clear that the crowd doesn't care who the good guy or the bad guy is.

They wanna cheer Hulk.

They wanna cheer Hogan.

They wanna cheer their childhood hero, right?

And one of the amazing things which happens is in the first 30 seconds to a minute, the rock does good guy moves.

A good guy is supposed to work in a certain way, right?

You do legitimate moves, you don't cheat, et cetera.

The bad guy works certainly in a particular way.

But these guys, without even talking to each other, they realize, oh, wow, like this is something different.

And they call Naudible.

And without even talking to each other, they say, we're going to flip the story, right?

And for the rest of the match, The Rock acts physically.

as the bad guy.

And if you watch it, you can see that happen.

And there is this amazing moment which happens where like about near the end of the match, the rock hits Hogan with his finisher you know the rock bottom and Hogan kicks out and he hulks up he's like and he's sucking in the Hulking mania sucking in the energy and and people like connected to their childhood I remember watching I was connected to my childhood right people like oh my god

no the rock eventually you know winds up winning but it is one of those amazing moments I was watching it decently because obviously Tragically, Hogan passed away recently.

So I went back and watched a lot of these old matches.

And it's one of those amazing things where you're like 100,000 people, right, feeling something together, two iconic superstars, right?

Like knowing how to navigate them.

And in the fly, without even talking to each other, redoing the storytelling and creating, you know, something which any wrestling fan would tell you.

If you're watching that, and if you don't have goosebumps, like, you know, something's wrong with you, right?

And so anyway, so I'm a big fan of pro wrestling.

I still watch it now.

I'm fortunate to become friendly with some of the people who do it for a living.

I have a lot of respect.

I learn a lot from it.

Interesting, interesting.

You know, we have a saying here,

it us or as the whole team, we compare U.S.

politics to professional wrestling.

That is true.

Do you see any similarities?

Absolutely.

First of all, the...

The person I work for, the President of the United States, is in the WWE Hall of Fame.

Okay, so let's just start there.

And I think that, you know, a lot of people in politics and other parts of the world, other domains learn from pro wrestling.

For example, right?

You know what cutting a promo is?

No.

Okay, so cutting a promo is when, let us say, you and I, I'm a good guy or a bad guy, and we have this big match coming up this weekend, right?

And we want to get everyone to buy it.

Back in the day, you would pay 60 bucks, get it on pay-per-view.

You know, these days, you probably subscribe on Netflix or something.

A promo is us trying to hype up the match and you'll be like i'd be like another time

sean

i respect you for everything you've done but this sunday you're going down right like or something like that that was a bad promo right like don't judge me and but you kind of build up to it and you you basically you know put over the other person kind of put over meaning you make sure the other person looks a legitimate threat because nobody wants to see you fight someone who's not a legitimate threat so you got to put over the other person right and then at the same time you're trying to build interest, you know, for this match, right?

And I think, you know, if you look at a lot of people in politics, they have learned from that.

And even outside politics, for example, Floyd Mayweather, Money Mayweather,

he took a lot of how we constructed the TMT, the money character from pro wrestling, right?

Connor McGregor.

Exactly, right?

The walk, the whole thing, right?

Like a lot from pro wrestling, kind of, because people want to be invested.

They want to see the story, story you know they want to be invested in you right they want to see you kick someone's ass or see your ass get kicked because you know you're the jerk whatever but ultimately you're trying to get people to invest in a story and i guess you know uh watch the fight and i think some of the best people to do it find a way to do it where you're like man i'm going to watch history and i got to watch it so and maybe i'll stop at this you know uh people ask me you know what if i'm going new to pro wrestling right i'm okay you're going to teach me how to use use a six-star.

I'm going to get you back into pro wrestling.

Right.

And the match,

I'm going to have two matches.

I'm going to have you watch.

And these are from 2009 and 2010.

Okay.

And they're Sean Michaels and The Undertaker.

Okay, two matches in a row.

So the quick story there is that Sean Michaels and The Undertaker, I'm sure you know who they are.

We've seen them growing up.

Oh, yeah.

Right.

Now, The Undertaker had

what was called the streak.

And the streak was

the sequence of matches at every WrestleMania that he had won.

He was the only person, and at the time, I think he had won maybe 11 or 12 years in a row.

Imagine one football team winning every Super Bowl for 11 years in a row.

He eventually wound up getting the streak broken, I think, at 18 years, but at the time, the streak was this magical thing.

It's like next person up, who's going to take him down?

But, you know, he doesn't get taken down.

Sean Michaels, right?

Like, you know, Mr.

WrestleMania, right?

Like, he was somebody who's iconic wins went up against the undertaker so wrestlemania 25 right i think this was 2009 they have this epic contest right just epic contest one of the greatest matches of all time right you watch it right you know uh it just the storytelling they do 100 000 people again invested you know i get ghosts from just talking about it right now amazing match Now, what happens after that, Sean Michaels,

basically the character, goes crazy.

He's like, I came so close and I couldn't get it done.

And so he challenges the Undertaker again for a rematch at the next year's WrestleMania, a year later.

And Taker says, no.

And Sean just does a lot of these things to get him to say yes.

And so he goes on.

And Taker says, okay, fine.

I'm going to give you a rematch, but it's not going to be any match.

You know, if you win, you're going to break the streak.

Nobody has ever done this before.

But if I win,

you're going to end your career.

Okay?

So

now you can think of this as a wrestling storyline, right?

It's like two people in a room wrote it up.

On the other hand, it is real because we grew up with watching Taker win every match for through our childhood.

It is a part of my story growing up, right?

It is part of history.

At the same time, we grew up with Shawn Michaels, right?

Like, I loved Shawn Michaels, I hated Shawn Michaels, I loved Shawn Michaels again.

So, you knew when you watched that WrestleMania,

something beautiful, which was real, was going to end that evening, right?

When somebody counted one, two, three.

And anyway, so you should watch him.

At the end of the match, you know, it is huge and emotional.

And Sean is beaten down.

And Taker tells him, you got to stay down, man.

It's too much.

You got to stay down.

And Sean

gives him this throat slash gesture, which basically says, like,

You got to put me down.

Otherwise, I'm going to keep coming back.

And then Taker does this big move, wins.

and then there is a sense of

sadness there because you know, you're like, wow, this amazing match ended, but Sean's career did really end.

He retired after that match, and it was one of those sort of this epic mythological feelings, like these two amazing gladiators who have never been beaten for.

So, anyway, so when I tell people to watch wrestling, like you know, you should watch that, you should watch Rock versus Sogan, and it'll make you feel something.

I will, I will

incredible.

Let's move into your story.

Yeah, you ready?

All right, where did you grow up?

Um, I grew up in India in a city called Chennai.

Uh, it was called Madras when I grew up.

Um, India has four major cities: uh, Delhi, Mumbai, uh, Kolkata, and Chennai, and we are in the south.

And you know, what I would call, what Indians would call like a lower middle class, middle class upbringing uh my mom stayed at home you know took care of the kids uh she was very focused on family uh very religious in a lot of ways uh very focused on just raising us in sort of the proper way with a lot of right values my dad uh kind of had the same job for 40 years uh he worked in this uh

this nationalized uh company.

And we were one of those people where, you know,

I think my dad, when you're a kid growing up, you don't really think about how your parents are acting towards you.

It's just like the way they are.

But looking back now, and especially, you know, we're just kind of talking about sort of our parenting journey in a way.

I see how much they gave me in so many ways.

So my dad, you know, we never had like real money of any kind,

but he always made sure that, you know, we were comfortable and that, you know, we never felt like

we were left out.

But I now know, just knowing some of the numbers, like that must have not been super easy.

I also really respect now because I took for granted then, you know, he passed away,

he died in 2006, but he was just there all the time.

You know, took me to school like every single day.

came back from work, a long day of work, hung out with us every single day.

And back then, you know, it's like that just the way things, when you're a kid, you're five, seven, eight, you're like, that's all everyone else.

But now I realize how fortunate I was to kind of have that stable grounding experience.

And my mom was just sort of this huge source of strength.

You know, she was taking care of us without a lot of resources.

And, you know, she was incredibly focused on my education

because when she grew up, you know, they didn't have any access to books or you know they had really struggled economically and she was like I'm just gonna make sure you had a good education and she would save up money and you know I used to get really into reading a lot and she would make sure I could always buy things

and again at the time I didn't really appreciate all the sacrifices they were going through to make that happen for me

But I'm just very, very grateful for the experience I had because I think like that grounded me, taught me, you know,

what

being a great parent who's dependable, who's always there,

you know, looks like.

And I've been so much more fortunate in so many ways.

But

yeah, that was a, I would say I had a pretty great childhood.

Yeah, you know,

I watch your socials and I mean, it's just, it's really, it's nice to see somebody in the position that you're in that is so focused on family, see all the stuff that you're posting with your kids and your wife.

And

you take your family time very seriously but um and i commend you for that i think that

i think you're a very positive example of what it means to be a husband and a father and a family man and um you know what

one thing i would like to talk about with you is you know this i mean you're raising your kids here in the united states you've done very well for yourself and that is a

i

probably shouldn't assume anything, but I think that looks very different to than how you grew up in India.

And so could could you go go into some of the differences or what your childhood was like growing up in India?

Well,

very obviously, I've just been very fortunate here.

And I think my kids are very young.

So I think this very, very different childhood from what I had.

But let's see.

So

we

you know,

we were what India has this term, which I don't think is as popular in the United States called middle class.

And, you know, in my family, education was a huge priority.

You know, they kind of,

I think my family kind of pinned all their hopes and dreams on me in a lot of ways.

They were really focused on education, and it was very high pressure.

If you didn't do well academically, you know, you were really going to struggle, or at least that was what I thought.

No, I don't think this is actually true.

And I've seen a lot of folks kind of you know, have great successful careers and whatnot.

But that was what I was told, like, this is the way out.

And when I was 18 or 19, you know, I convinced my dad to buy me a computer,

one of these old, again, I'm dating myself here,

a Pentium III box.

Like, you know, back when, like, you know, a CPU was one of these big beige boxes that showed up and you stuck it on a table.

And it was a big deal.

for him.

I recently reconnected with somebody who knew him at the time and it cost him like a year's paycheck or something.

Wow.

This is is a big deal, right?

And

again, my kids, I'm like, you guys have it so easy, right?

Like, you know, but it was a big deal for him.

And I begged and pleaded for a long time.

Now, again, he was a lot of great things.

He was a rebel in a lot of ways.

I get some attitudes from him, but he didn't really understand technology.

It was like, he was not of that generation, right?

He just didn't understand computers.

But he took a bet, you know, so he spent this serious amount of money

on me.

And then I, even though he didn't know what I was going to to do with it uh and then I convinced him to get dial-up internet uh which was kind of a big deal uh and I would say like my whole story exists because of that and America because like you know well and I guess pro wrestling because that's kind of how I grew up like really you know understanding America in so many ways but you know I grew up you know I would spend every single night

learning compute the computer and learning to write code.

And way back then, it was a bit hard to kind of get, you know, you can get online and you run up the phone bill.

There's a concept which kids these days don't know, which is you log off the internet.

Do you remember that?

When you used to log off, I do remember.

Yeah.

Did you used to like run up the phone bill back home?

Oh, yeah.

Yeah.

And people like, Sean, get off the PC.

You know, we have to make a phone call, right?

Like, or you're like, you're doing, you have a big download and then somebody picks up the phone.

Anyway, so kid these days.

But

I would have to do it late at night because that is when the internet would be faster because during the day, other people would be using these phone lines that would be slower.

And I would get

all these kind of coding guides.

I would get all these used books on writing code.

And at the time, I was a bit lost, I would say,

in what I wanted to do with my life,

how I fit in.

I wasn't very social

and I was kind of lost.

But then I realized that this code was something that brought me joy.

And one of the things I think people who don't do computer science don't understand is the deep joy of creating something on your computer with computer science code, right?

Because the computer is unforgiving.

You have to figure out a way to get it to understand you.

You have to solve.

mental intellectual problems.

You never get it right in the beginning, but AI is now helping with that, which we can get to later.

And it is an intellectual exercise and and once you get it working it's just amazing right you just feel so good because you've created something and no one can take that away from you so i was just doing this every single night i would stay up from like 10 p.m till 4 a.m you know and then go late to school the next day i would just be writing code online and this is where i think two amazing, amazing things wound up happening.

One is my now wife, Arthy,

she was very similar to me because, you know, she came from a, you know, she was kind of one of the first people in her family to go to school in another city.

She was one of the first people to be kind of good with computers.

And

she was in a different city and she was learning how to write code herself.

Now, at the time, I'd kind of built a little bit of a reputation myself in my town as the computer science guy.

I'd written some piece of code.

Do you know what a virtual machine is?

A virtual machine?

Yeah.

No.

Okay, so a little nerdery nerdery here uh you know if you're going to nerd out for a bit so um

people usually write manipulate computers using programming languages but you might have heard of that right

and um but you know

But one of the things people figured out is if you directly have a programming language access the computer,

it might be unsafe or, you know, or it might be sort of hard to manipulate in lots of ways.

So they came with this idea of virtual machine, which is a computer that runs inside a computer.

Okay, and the reason you do it is you're not giving it access to all of it.

It's a sandbox, okay, which runs in a computer, but you can run any sort of code on it.

You can write a game, you can write all these amazing things on it.

Now, it's some very sophisticated piece of technology because you've got to be really fast because you've got to run it like a computer.

You know, you've got to know all the things a computer does and you've got to make sure it doesn't sort of break out of the sandbox and then does maybe evil things on the actual computer underneath.

And for a lot of reasons, you know, I got really into building virtual machines and how they work and how to make them fast, how to make them, you know, performant and all these kinds of things.

And it kind of had a little bit of a reputation.

Like, think of it like, you know, like, think of the guy, you know, in your high school who can maybe dunk or athletic and, you know, the schools around him, I was kind of like that guy.

And so the wife and I, you know, we started chatting online because somebody had introduced us, say, hey, you guys are these two nerdy computer science kids who seem to know how to do stuff with computers.

And can you help me?

And at the time, I didn't even know

she was a girl.

I didn't know what her age was, but she was like, I was just this friend who has similar interests to me.

So we would chat every single night.

We would stay up nightshight chatting.

And then after six months, you know, she's asking me, Hey, you know, like, who are you?

I'm chatting with you.

Who are you?

And I'm like, oh, I live in the city, which is kind of nearby.

And then we wound up meeting a few months after that.

First time we met.

And

we've been together ever since.

This was for the last 23 years now 23 years yes 23 years when did you get married we got married in 2010 and uh but we we we met each other in 2002 started dating in 2005 2006 then in 2010 our parents were like you folks are both crazy you'll never find anyone better than each other you know you got to get married and you know got married in 2010 you know have two kids the whole thing so yes so so i always have to say the best thing computers have brought me is Arthi because without that, you know, I wouldn't have her, I wouldn't, you know, and none of this would be possible.

The second thing which wound up happening is that I was writing all this code.

And at the time, you know, there was a Microsoft executive who was touring India and they wanted some student who could do some of the things I was doing.

And somebody had written seen, something I'd written online.

And I get this cold email saying, hey, you know, do you want to come out and do this little sort of event for us?

Because they wanted a student to come do a demo with this kind of this big shot exec.

And at the time, you know, I couldn't really like speak English.

I was kind of living in my bedroom doing these things on my computer.

And this is like, this is amazing.

So I remember I got on my very first plane ride ever.

I'd never been on a plane before.

And my first fancy hotel room.

And we were like, I'm guessing I was maybe 20 at the time.

It's like crazy, right?

In this fancy hotel room, mics are paying for it.

It went really well.

And this executive, you know, who's now retired, but it was amazing, was like, you kids, he met me and my now wife, Adi, he was like, you kids should work at Microsoft.

I was like, sir, we would love to, you know, but we're here.

We don't even know how to find you.

So, you know, long story short, you know, you know, he said, you know,

let's find a way to get you in because he was kind of impressed by all the things I was doing.

And it was very connected to some of the things Microsoft was also working on at the time, like cloud computing.

So he was like, hey, there's this kid who's doing these things things that we're also working on.

Let's just find a way to connect the dots.

And so a year later,

they flew me to Seattle,

Redmond, where Microsoft is off.

And I remember flying in, you know, and Seattle is a beautiful place, you know, the Pacific Northwest is beautiful.

And I just fell in love.

I was like, man, this is all I want to do.

I've grown up, you know, watching Hulk Hogan, watching The Rock, watching Star Trek, watching these movies.

And I'm now here.

And even though I couldn't really speak English very well, even though I didn't really fit in very well, I was like, computers I can do, and let me figure this out.

So that sort of, you know, started my whole journey.

So I think without sort of my parents, sort of the environment I had,

without like my dad spending, taking this bed on me, you know, he was not sure what a teenage son, teenage son's on the internet late at night, right?

He was like, I don't know what's happening there in the closed door.

Like, I don't know, right?

Like, you know, and

he was like, the door is closed

but uh but they took a bet on me and uh

um and you know you one of the things you realize you get older is how fortunate you are right like so without my parents you know being so focused on me and making sure i had a better life than they had give me these opportunities uh without you know,

um, these people who just saw me and they were like, hey, I see something in this kid.

Let's take a bet on him.

And I would say mostly, I would say this country, right?

You know,

every single thing I have professionally, my wife has, has been possible because of America.

We live in Seattle, we live in San Francisco, now I live in Washington, D.C., right?

Like, so I'm so grateful for all these things.

And I've just been very fortunate, right?

Like, I've been in the right time, right place, and I've been very, very fortunate.

Yes, yes, yes, you have.

And

wildly, both you and your wife are the wildly successful.

Are your parents still alive?

No, my,

you know, my father died in 2006

and my mom died three years ago.

And

I had sort of, I think, you know, one of the things you don't realize, so 2006, I was, what, 22, 23 when my dad passed away.

It's sort of a big regret in a way,

because I never

got to show him some of the success I wound up having later.

Like, I think, you know, a a lot of ways,

you want to show your parents that, oh my gosh, mom, dad, like, look what I made of myself.

Look what I've become.

And at the time, I had just gotten this job and he knew it was a big deal because it is, you know, I was doing these cool things and I was in the newspapers and whatnot.

But I never kind of got to show him,

you know, that, man, like, you know, all the investments that you made in me, right?

Like, you know, look, I've done something with that.

right?

I also,

I kind of missed out on having an adult relationship with him, which I think is quite important.

Yeah.

Right.

I do think, you know, I grew up in my 20s with my dad.

So I always look, you know, a lot of people don't have parents at all.

Or, you know, they didn't have the benefit of the childhood I had.

But.

I sort of feel like I missed out because I never, I was a kid growing up, right?

I had, you knew your dad in that facility, but I, I'm, it saddens me that he never saw me, you know,

you know, have my my career, never saw me get mad at, have my kids.

So I never had a sort of adult relationship with him.

I never got a chance to provide for him.

You know, I would have loved it.

So he was a rebel, by the way.

So he,

back in the community I grew up in, right?

It was very community-oriented, et cetera.

But you're kind of supposed to stick to your lane, right?

But he was a bit of a rebel.

He was like, I want to be a writer.

I want to write my own books.

He was kind of, he had all these creative ideas.

I think if he was just, if he didn't alive five years later, he would have self-published on the internet and you know, probably, you know,

being on YouTube comments with conspiracy theories,

he was that person.

But he missed out, right?

And but I think I have some of that nature in me to be like to speak out.

So one of the things he really taught me

is that

a lot of people would be like, you know, if you see something wrong, you mind your own business.

But if you saw something wrong in our community, he'd be the first person to go speak up and try and help one.

And as a kid, you're like, Man, like, I don't want to get into trouble.

Like, what is this?

Like, I don't want to keep my head down.

But he was always good at that.

So, I miss him.

I feel sad that I didn't get the chance to kind of show him everything and maybe provide for him.

My mom, you know, um, you know, she passed a few years ago, but you know, I'm very fortunate, and she got to kind of see my family, you know, and she built a very close relationship with my wife, you know, my first, uh, my first kid.

And yeah,

what would you, I mean,

what would you say to your dad if he was here today,

man.

Think about this

that I somehow made something of myself.

I don't know what I'll say it or show it to him, but you know, like a lot of parents, you know, he had, he was very proud of me, but you know, we sometimes he would have friction and he'd be like,

and I just want to show him that in the very imperfect way I am now, you know, I've sort of made something of myself, right?

And a lot of it thanks to him and a lot of the bets he took.

And,

you know, my hope is that, you know, somehow, somewhere he knows that.

But, you know, that's the one thing I always feel like I never got a chance.

You know,

you want to buy your parents cool stuff when you make some money.

Right.

Like, you know, I think people ask me, you know,

what is it when you ever make some money?

Right.

And I think one of the best things to, you know, is to go buy your parents something ridiculous that they will never buy for themselves.

And I got to do that with my mom, by the way.

So

and I will never do that with my dad.

So I always feel like, you know, but I think the deeper notion would be to be like, hey, it kind of worked out, you know, I made something of myself and thank you.

What about you?

Like, you know, how do you feel about your relationship with your parents and how it has evolved over time?

I think, you know, I think, I think me and you share a very similar sentiment.

And I just always wanted to prove to my parents that I could be something and do good for the world.

And it's something that I took on at the age of 18 when I joined the SEAL teams.

I mean,

that's really what pulled me through.

Yes, I wanted to go to war.

I wanted to fight for the country in the highest capacity possible and be the best that I could be because

I was a failure up to then.

And I didn't make good grades.

I wasn't very athletic.

I didn't really have much going for me.

And so, you know, what really pulled me through all that training and got me in was

I had a horrible fear of telling my dad that I failed again.

And

so that stuck with me at 18 and buds.

That's what got me through.

That's what got me into the agency, you know, was I wanted to, I just, I just always wanted my parents to know, you you know,

they did a good job and that

I could make something of myself regardless of, you know, how my childhood went.

And my parents are still alive and

we have a very, very close relationship.

How do your parents react when you first signed up?

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Well,

what is that conversation like?

That conversation went

when it came out.

Like I said, I did make good grades and I had a lot of potential.

I was a smart kid.

I was really good at math.

But I didn't apply myself because I wasn't interested.

And

it came out one day.

He was really frustrated.

I just got a report card or midterms or something, and it was not good.

And

C was probably the best grade.

And

he said,

it was an argument.

And he'd said, I'm not.

I'm not going to pay for your college.

I'm not going to do it.

He's like, you're not going to apply for yourself.

And I said, I don't give a shit if you pay for my college or not because I'm not going to college.

I'm going to become a Navy SEAL.

And

at that

moment, the whole

everything changed.

And he, you know, he, he, I mean, I think he thought it was full of shit because I didn't follow through on anything that I'd said that I was going to do.

And he had asked me, you know, how serious are you about it?

And I had told him, I said, yeah, I've had multiple meetings with the recruiters already.

I've already talked about it.

I want to sign.

I was only 16 or 17 at the time.

And why did you want to be a SEAL?

I don't know.

You know, I just always grew up playing G.I.

Joe's, watching G.I.

Joe.

I mean, your thing was professional wrestling.

GI Joe, actually.

G.I.

Joe equally.

I'm trying to get my kids into it right now.

Sorry.

What is your favorite G.I.

Joe type growing up?

Ooh, Snake Eyes.

Perfect.

Man, badass ninja.

Snake Eyes was a Storm Shadow, right?

And the the rich kids would have the sky, the

Sky Striker jet plane.

Oh, man.

Yeah.

Sorry, yes.

But that's what got me, I think that, so I was always, you know, and

early on in

my younger years, fourth grade, my dad took a job as a pharmacist in the Army.

And we went to Germany, and that's when Desert Storm was kicking off.

So I was always,

anytime we were at the bookstore, I was always grabbing all the magazines and books about what was going on over there.

And I would just look at the pictures of tanks and helicopters helicopters and planes and, and, and,

and, and, and military warfighters.

And I was always out in the woods building forts, carving spears, doing all, making bow and arrows and shit like that.

And, and, um, so

that just, that just always got me really interested.

And, and, uh, originally in my military career, I just, I didn't really care.

I just wanted to go fight in a war somewhere.

So I wanted to be a Marine.

Wanted to be, then I started looking into that, found force reconnaissance, talked to the Marine Corps at the recruiting station.

They laughed me out of the office because I was about a hundred pounds soaking wet.

Went to the Army, wanted to be a Ranger or a Green Beret, same deal, laughed me out of the office.

And the Navy recruiter sticked his head out and said, hey, you want to be a SEAL?

And I didn't even know what a SEAL was.

And because I was also very into all the Vietnam generation movies like Apocalypse Now, Platoon, all that kind of stuff.

And so they gave me a pamphlet on being a SEAL.

And I read it and went to the library, checked out a bunch of books, started watching movies.

And I was like, that's it.

That's what I want to do.

And

luckily wound up making it through and followed through.

And that took me into the CIA and had a...

awesome career there and and um

and then somehow i wound up podcasting

Well, thank you for everything you've done.

But I'm so fascinated with just how you signed up because I'm very curious about why people pick the careers they do,

especially for something like that.

Because when you're, how old were you when you signed up?

17.

Right.

So super young.

You don't really have a sense of the world.

But maybe you did because you were in, you've kind of been around the environment a little bit.

Like, I'm curious about what is it that makes someone be like, all right, I'm going to do this.

I'm going to serve my country.

I'm going to put myself in harm's way.

What do you think some of the general motivations are when people were like, I'm going to go sign up?

I mean, I think it's always different, especially in the SEAL teams.

I mean, I was one of the, maybe, no, I wasn't the youngest.

I was maybe the second youngest guy in my Buds class.

And, you know, when you go to Budge, you have all these, you have

guys that are coming in from other special operations units that had already been to war.

And they're just, they're trying to

operate at the highest level it as they possibly can you know and in what they think they want to do and so you've got 18 year olds up to 30 year olds you know that are trying out to become a seal and you know for me

i can't say that i was overly patriotic um

9-11 didn't happen until i was already uh it happened like right after boot camp.

So I was already in.

But even when 9-11 happened, I mean, I knew we were going to war, but I didn't understand what that meant.

So

like I kind of said at the beginning, for me, it was,

I mean, that's just what I wanted to do.

It wasn't necessarily just for the country.

It was what I wanted to do.

I wanted to experience,

I just wanted to experience that, you know, at the highest level.

And then on top of that, even more than my own desires, I just wanted to make my parents

and

particularly my dad proud because my brother and sister were good students, good at athletics, better than everything that I was doing.

And I could see that.

I could see the interest,

especially in my brother.

My brother was a really good ball player, baseball.

And I could see my dad gravitating towards, you know, what my brother and sister were doing and kind of like, well, Sean's just the fuck up of family.

And

I knew I needed to, you know, for my own mental health, change that to,

I just wanted my dad to be proud of me.

Was there a moment through your career serving or elsewhere where you're like, man, this is the moment I know my parents are proud of me.

Yeah,

after Hell Week.

After Hell Week.

Do you know what Hell Week is?

Okay, yeah.

Thanks a lot, by the way, to your show and hearing people talk about it on your show, too.

Oh, cool, cool.

But yeah,

that was the moment, you know, that was the first moment that I was, that I felt like, man, even though I'm only four weeks in

to over a two-year process, I was like, that's the biggest hurdle, you know?

And so

that was

my dad was my first phone call and I said, dad, you know, I made it through.

The rest, it's going to get easier from here.

It didn't get easier, but

that was the big hurdle.

And it felt really good.

And then graduating, buds, getting into the SEAL team, first combat deployment,

finally, you know, getting into

contracting at CIA.

I mean, you just, it just, that would, it's, it's always in the back of my head, even still today, you know, with the interviews that I do.

I take, I take this very seriously, and I've made a lot of mistakes

in the podcast world, but in general, you know, I just,

want to,

I have an ability to get stories out, you know, and make people comfortable during these interviews.

And,

you know,

it feels really good

to

be able to take somebody, you know, like I was telling you at breakfast, to take somebody that nobody's ever heard of,

who's starting a business, who's been through struggles and get them in here and get them vulnerable, especially with some of the

special operations guys that have, that have, you know,

there's a cost that comes to doing that job, both mentally and physically.

And there's a culture within that.

And, you know, the culture within the SEAL teams and the special operations and even just the military community in general is not one that's widely accepted by civilians.

I mean,

there's a lot of

drinking, debauchery, womanizing, fighting, bar fights.

I mean, and

now I can't even remember where I'm going with this, but

to get somebody, yeah, to get somebody vulnerable to talk about what that's like and suicide attempts and stuff after.

And a lot of these guys, you know, they get out, they don't have a voice, they aren't able to document what happened over there and

to showcase all of that, you know, what their career was like, what it was like getting out, the suicide attempts, the drug addictions, the womanizing,

the infidelity, and to have somebody come on here and

talk about all that and how they got out of it, you know, because a lot of veterans feel trapped.

They don't fit in with regular society, you know, and

regular society is fascinated in the lives of what me and my former colleagues used to do.

And so to open that up, you know,

it's like giving the American, not even just the American, the world.

I mean, it's a huge podcast now.

People all over the world listen to be able to get a peek behind that curtain on what that life actually is like from somebody that's lived it

is awesome.

And then the audience gets attracted to,

they're invested.

I mean,

we go from childhood all the way to current date.

And

to give somebody a glimpse into what that journey looks like is, I mean,

before this podcast was, it was unheard of.

You know, you didn't get that deep.

And so when the audience gets invested into a story like that,

these guys that are, you know,

I think a really good way out of that downward spiral after military service and after warfighting is entrepreneurship is a great segue out because we talked about purpose right at

breakfast today and how people need a purpose, whether they were a factory worker or

auto mechanic or whatever.

And we were talking about AI taking jobs.

I mean, for military guys, I think entrepreneurship gives you,

for anybody, I think it's an enormous amount of purpose.

And that and guys coming out of the military and women, I mean, they have, especially in the special ops community, or people that are wanting to be the best at what they can be, what they do.

I mean,

they're going to implement that in whatever they do, but they don't necessarily

get the traction, the exposure that they need to create a successful business journey as an entrepreneur.

And we've had

time and time again, we've had guys in that

they didn't have the exposure, but I could see the drive, you know, and I could just see them in the hamster wheel, like not getting any traction.

So to be able to bring them in, tell a life story, get the audience invested in their story and who they are as a person.

It just, you know, some of these stories are so

wild and

real that they don't care what your business is.

They just want to see you as a human succeed for all the sacrifices that you've made in the country.

And it brings other veterans hope.

And

it really brings anybody hope.

It's like, man, if this guy's dealing with this shit, then maybe I can, maybe I can push through what I'm going through.

And

we're able to turn a lot of startup businesses into multi-million dollar businesses really overnight.

And

that's what I love to do more than anything.

Or take somebody like you.

I mean, you have a...

huge name in the tech world.

You're very connected.

You're very successful, but I don't, I think there's still a lot of people that don't know who you are, who you are as a person, all your accomplishments, where you came from in India, in a middle class, in a middle class family in India.

I think a middle-class family in India looks a lot different than a middle-class family here in the United States.

And

so to be able to bring somebody on like you, who

I wouldn't say you came from nothing, but very little,

And to be able to come to the United States and build what you've built, you know, the life for you and your wife and your kids, I mean,

that is going to bring somebody, at least one person that's watching this hope, you know, and

because we live in this, you know, we live in this society where

it's become very popular to victimize yourself and make excuses on why you're not finding success.

And it's always somebody else's fucking fault, right?

And, and, but you control I'm a huge believer and you control your own destiny and when you find what you what your gifts are what you're good at what you're interested in

I don't believe there are limits you know I think yes there are limits like I'm not going to be a professional wrestler you know I'm a we'll we'll get you working

don't don't cut yourself short sorry sorry but but you know I'm a buck 80 it's just not going to work but

I find the things that I'm interested at that I'm good at and i i don't think there are limitations i think the sky is the limit and you can probably go higher than that and and

you

are a perfect example of that thank you that if if you have the drive and the work ethic and you don't spend your time looking for excuses on why you're not successful you will rise to the top and and and in stories like yours or

or Palmer's or the veterans or Blonsdale or a lot of the people people that I brought on, a lot of these guys, you know, they didn't, they didn't come from generational wealth.

They built something out of damn near nothing.

And

that's America right there.

That's it.

That's it.

And that's why I do it.

And

so long circle back.

I just want to say, well, thank you.

But, you know, one of the, I don't know how much people can see just the room we are in, but before we started, you kind of give me a tour.

And it's just a powerful space because every object here kind of has some meaning and so many of them uh you know are from people with just these insane amazing stories you know often people who have sacrificed so much uh for the country and this is so powerful uh and i think one of the things that you've just done so amazingly well and i'm not saying to kind of blow hot air up here behind is create a space where people can share things.

I think we were talking at breakfast about your your episode with one of your closest friends.

And one of the things I loved about that was that just seeing him, seeing somebody, you know, who's just, you know, such a great sort of masculine figure, but at the same time, you know, opening up about some of his struggles, you know, dealing with the family, dealing with sort of all the things that he had to overcome.

And also in the business world, I was very interested when he talked about how he was navigating the business world, right?

And,

you know, and I think so, you just created just this amazing space and platform for people to be part of.

So, well, thank you for that.

I think what you've just done is just amazing.

Well, thank you for saying that.

But let's get back to your story.

So, you go to Seattle and you start working for Microsoft.

What did you think of the United States?

Oh, man, dream come true.

Right?

Like, you grew up a lot of places around the world, and you know you watch this on movies you know i grew up on gi joe by the way like you know i have a whole big collection i grew up on top gun independence day you know rambo rocky the all the classics so you know and uh so you watching it on tv you have an idea uh i think the word american dream gets thrown on and thank you for that i had i didn't know of any of that i just was like this is a place where I can do something with my skill set.

And

one of the ways I can maybe make this useful is a lot of times people ask me, what is my advice for young people, people in their early 20s?

And I remember when I first got to Seattle.

And Redmond, I was just so lost.

I didn't have a driver's license.

I had never seen snow before and it was snowing.

And my wife and I, we were like, oh my God, like we had to walk a mile to the grocery store in the snow.

And you didn't have an assistant for a while, which was, you know, because we had to figure out our paperwork.

And

we just felt so lost.

We didn't know a lot of people there.

But

when I walked inside a Microsoft building, right, and I would see these computers with coding windows, I felt incredibly comfortable because I knew, you know, that I was very, very good at.

And I knew on that, there was anybody in the building, I could go toe-to-toe with them.

So, and i think that sense of mastery is very important right maybe whether that might have been my arrogance maybe i wasn't like that good but um if you are you know if you're kind of lost and you know one of the things i tell people is

find a way to become a master of one tiny niche thing So, for example, when I was there,

we had this sort of this big presentation we had to do for Bill Gates, another senior exec who were kind of running the show at the time, Bill Gates, Steve Ballmer, and this guy, Ray Ozzie.

And,

you know, and one of the things I did was like, I became the guy who, for the thing I was working on, the voice of the customer.

What I would do is I would go look at every single internet complaint, every single, I would call up customers.

I'd be like, hey, this is someone comes from Microsoft.

They'd be like, why are you calling me?

And I'd be like, hey, I just want to know what you guys think.

And I was not supposed to do that.

I was on the engineering side.

And the reason I tell the story is because over a few months, because I had the technical background and I was building some of these products, but I was also talking to customers on this very niche thing.

I became like the worldwide foremost expert on that thing, right?

How people were using it.

What were they doing?

What are the issues they were running into.

And by the way, it's a tiny thing.

Nobody else, I was a master because nobody else cared enough to make themselves a master.

But the reason it was great for me was when I would walk into a meeting and I would be people who are much older.

Okay, now they're younger than me.

So, but at least when you're in the early 20s, you know, somebody was like 40 years old, you're like, oh my God, that guy's ancient.

Little did I know.

So, you know, now I'm older.

But, but, and, and I had an accent, right?

I look different.

I'm weirdly tall, as you know, but when it came to this topic, which is about this kind of

this kind of programming we could do, that I was like, I'm the expert, right?

And even if the others didn't know it, I knew it because I spent every day, every night for months and months, and nobody could take that away from me.

So when you have these huge meetings, I once had to make this presentation to Steve Ballmer and these execs.

You know, I was comfortable because I had done all the work and I was an expert.

And so Microsoft was very intimidating because it had all these legendary people, some of these real icons.

But when I built this sort of sense of mastery, I found my way to comfort.

So I always talk about this when I talk to young people.

Or even people are trying to break into the technology industry, which is, you know, the technology industry can seem bizarre.

It has all these crazy, large-than-life personalities,

like Elon, Palmer, etc.

But if you can make yourself and everybody can make themselves the absolute expert in one area,

you're going to feel so good, right?

And it's going to start opening doors.

And so that was a big part.

The second thing was I think a lot of people took a bet on me there, and I'm very grateful.

One of the things I absolutely need to underline is I am the result of so many things going my way and so many people taking a chance on me when they did not need to.

Okay.

And let me name a couple of people.

And so this is going to get very nerdy and technical.

So sorry about that.

But

one of the things Microsoft had a lot of were these amazing technical geniuses who were really good at one thing.

And one of

the most iconic people was a guy named Dave Cutler.

And Dave Cutler

is probably known as probably the greatest programmer of the 20th century, the greatest one or two.

If actually, Palmer will tell you how much he admires Dave Cutler.

And the reason he's known as the greatest programmer of the 20th century is he basically built

the version of Windows in the 90s that became really popular.

And he's a personality.

When I showed up, he was in his late 60s.

He's now in his 80s.

He was known for being incredibly rude and mean to people.

There are legendary stories of him punching holes in walls, of throwing people out of his office.

He was not a person who suffered fools gladly.

But this guy had an insane work ethic.

He had more money than God, but he would show up to work every single day, you know, at age, must have been late 60s now.

Then, now he's in his 80s.

And then write code.

Okay.

So I remember, you know, and I was like, man, I used to idle worship this guy, right?

And computer science people, they still idol worship.

I need to find a way to impress this guy.

And I don't know how, I was terrified, right?

And so what I would do is, you know, he would show up on weekends.

I remember him once showing up on December 26th and working, right?

Which not a lot of people did.

And so I would start showing up on weekends and just see him in the hallways, etc.

And then after a while, he was like, all right, this young punk is here.

And then after like six months,

I found an error in his code.

This scared the shit out of me because, like, he was, he's basically like royalty when it comes to programming.

Like, you know, think, you know, I don't know, you're going up against Michael Jordan and you're saying, hey, by the way, you know, your jumper shooting form, I found an, I found an error, right?

Or Steph Curry, you know, that three-pointer, like, I saw something last night, like, I think you can fix.

So this is on that level.

So I was terrified, but I sort of went into his office and I was like,

and he was like, sir, I have this thing and this thing.

And he goes, ugh.

And he looks at his computer.

I'm like, man, this is the end of my career.

And he was known for firing people too, by the way.

End of my career right there.

And he was like, you know what?

You're right.

And then I was like, okay.

Then I ran out of the office.

And,

but, you know, the thing about him was he was so intellectually honest.

So he took my fix.

He made this buck fix in his code.

And then he kind of slightly, you know, him and others took me under their wing a little bit.

There are others, like a guy named Barry Bond, who was a deep mentor for me and my wife.

He would have us for or for lunch every day, just to kind of teach us things.

And so, so I was taking a bet on, right?

And Dave was a royalty, right?

And, you know, it's like Michael Jordan now seeing some punk kid and being like, I'm going to take you under my wing a little bit.

So he took a chance on me.

And when I had that stamp of endorsement, other people like, well, you know, if this guy survived Cutler, well, at least he can survive, you know,

you know, this crazy old person, you know, and he's good.

So it helped me.

So a lot of people took these crazy bets on me at Microsoft.

So when I think about Microsoft, you know, I mean, look, Microsoft is a crazy, complicated company, and a lot of people have mixed emotions about it.

But at that time, then I think about all the people who took a bet on me, even though they had no reason to.

And so now for my wife and me, you know, now are like in the position to take bets on people and i always think about okay how am i trying to spot the 20 25 year old version of me how would they look like where they come from maybe they know anything about computers maybe they don't know anything about ai you know let me find a way to you know just take a chance because i do think one of the most powerful things you can give a young person is this idea

that they are capable of much more than what they realized.

It's one of the most powerful things you can do.

And

I have been fortunate.

I had a couple of people do that to me, where I'd be like, wait, I didn't know, you know, I could even

do this meeting, right?

Or, you know, or I can start this project, or I can start a podcast.

And, you know,

but that was so powerful because you need that belief, right?

And I think about now, how do I find ways to give especially young people they say okay you are capable of so much more than what you realize right now it may not be easy it may take a lot of hard work you may not accomplish it it's you know whatever but you are capable and i think that is one of the most powerful gifts that i've been given from my parents uh others i've worked with and in i don't know

Whenever I possible, I try and find a way, can I capture some of that and give it to somebody else?

You empower people.

Well, thank you.

People empowered me.

They made me, gave me belief in myself when I didn't have belief in myself.

Maybe they gave me too much belief in myself.

Some people would say that too.

But it's a gift.

And, you know, I try and pay it forward whenever I can.

I love that.

I love that.

I think that, you know, I wish more people did that, you know,

that find success.

And I think a lot of people do that.

A lot of people that I talk to and hear do that.

People have done that for me.

You know, but maybe you had such great stories.

I just want to say, I don't want to put you on the spot, but when you're talking about breakfast,

you're given so many of these people this platform.

And

I don't want to sort of reveal this, but you were like, hey, you are capable of doing this.

And you're capable of so much more.

So I think you've done justice with this podcast, too.

Thank you.

Thank you.

I mean, that's how we make the country great.

Yes.

You know,

you pass it on, you pay it forward, you empower people, you give them confidence and

just shower them with positivity.

And

then it's up to them if they go on to do great things or

continue on the same route that they were.

I think that's in some ways, I think that is one of the most beautiful things about America, which is this idea that you have a shot, right?

Like, you know,

if you...

And I'm not going to pretend it is easy for everybody, right?

You know, a lot of people, you know, just come from different walks of life, have bad shit happen to them.

But I think at the core of it, one of the promises of this country is that, you know, if you work hard and if you apply yourself and you do all the right things, right, like good things will happen.

Like you have a shot.

A lot of other places in the world don't give you that, by the way.

You know, you're, you're kind of told you have to stick in this lane or you don't have any opportunity.

I do think, you know, at the core of this place is the sense of opportunity.

Yeah.

Right.

And I, by the way, in some ways, looking at the layer, but, I think about with AI,

how do we as a country give, you know, expand the opportunity set, give people way more opportunity than they had before.

So that's one of the things I think about when I think about my current job.

Yeah.

Where did you go from Microsoft?

Did you go to Meta or was it Toronto?

So my wife and I,

we idolized Silicon Valley, the culture of Silicon Valley.

You know, we, when we grew up, you know, our first date

was, I couldn't afford anything.

I had this tiny, you know, slightly smelly one bedroom.

Um, and we had to see each other.

And the parents didn't know we were seeing each other.

So she would kind of sneak in.

And we would watch movies about Silicon Valley, right?

One of the greatest movies about Silicon Valley, by the way, is this movie called Pirates of Silicon Valley.

It's a movie about Steve Jobs versus Bill Gates in their young heyday and how they competed with each other.

And we would be like, man, someday we want to be there.

And we were like, you know, by that, that was, I think, it was a bit-torrented CD.

Like, we didn't exactly pay for that.

Like, we were like, we couldn't afford the actual real thing.

Hopefully, I don't get in trouble for like 24 years later.

But, you know, we were like, someday you wanted to, because Silicon Valley was a land of opportunity.

You went there, you know, you were good at computers.

You could make something of yourself, right?

So for me, like, you know, like, for example,

if you, if you're playing football, what do you dream?

You you want to play in the super bowl right you're a pro wrestler you want to main event wrestlemania hopefully at madison square garden but for me right like well i also want to main event wrestlemania but right i wanted to make something else in silicon valley so anyway So in 2011, 2012,

we decided, okay, Microsoft has been great for us and we did great.

My wife and I had fantastic careers there.

We made a lot of friends.

We did very well for ourselves.

We were like, we want to take a risk and go down to Silicon Valley.

We just got mad at two, by the way.

And the way we did it is we said, okay, there are two of us.

So, you know, we're going to sort of hedge risk between us.

And one of us is going to take a chance and build a startup.

And one of us is going to get like,

go make some regular paycheck and job.

And so one of us is paying the bills and the other person can.

kind of follow this entrepreneurial path and we can kind of take the pressure of each other.

And the deal we made with each other was that we will kind of alternate.

Like somebody will go start a company first, somebody will go get like a regular job, and then maybe we'll switch it on.

Like we didn't know what we were doing, right?

We were like, we just wanted to be part of Silicon Valley.

And I will say Silicon Valley is a magical place.

And I think it is one of the

unique advantages America has over a lot of other parts of the world because the combination of capital which flows in, the combination of talent there, the density of the companies there,

the idea of anything.

It's not perfect.

A lot of issues with it, which we can talk about, but it is magical and it is unique.

So we wanted to be there.

So we quit our jobs at Microsoft

and we

flew down to the San Francisco Bay Area.

I'd be like, all right, what do we do?

And so a year later,

my wife, do you know what Y Combinator is?

Yes.

Okay.

So Y Combinator is this very popular startup incubator.

It's maybe one of the most popular startup incubators.

And at the time, they were maybe not as popular as they are now, but they're still a bit popular.

And what they would do is if you had an idea, you go to them, you apply, and you know, they pick maybe 20, 30 companies a batch.

And some amazing companies have come out of that.

Airbnb, Coinbase, Brian Armstrong, I think talked about Y Combinator here, Dropbox, lots of great companies have come from there.

And so, you know, so my wife, you know, had this idea, she applied, she got into YC.

And YC, by the way, doesn't give you a ton of money.

I think at the time they gave you, for the entire company, maybe like $80,000 or something.

So it's not a lot.

And I was like, okay, I need to figure out

how to

just get a paycheck, get some regular money.

And so I wound up joining what was then Facebook.

And Facebook, now called Meta.

And some of the older people here might remember this, Facebook then had just gone public.

And they were in a dark hole.

because number one, the IPO had gone terribly poorly.

They had gone public, I think, at like $45.

The stock price had plummeted.

Second is there was this big question about the whole world is moving from desktop computers to mobile.

And Facebook is only making money on the desktop.

So there's this big question of, first of all, the idea of social networks making money was

seemed laughable, right?

Like people would just laugh you out because people had seen MySpace, they had seen all these other companies fail, they were like, I don't even know why this is a thing.

Second was they're like, nobody can make money on mobile.

So they were in a bit of a hole.

And I had some friends there and

I told myself, look, I want to do something which is very different from Microsoft.

I want to do something which involves consumers because I really was interested in consumer psychology, you know, what makes

human beings use products, how they interact with products, how to build the technical algorithms.

Now maybe AI, you you know, didn't have the degree that word then, which kind of interacts with them.

I was very interested.

I just want to do something different.

So I got a job at Facebook and I wound up working on Facebook advertising.

Now, now it's a monster, you know, I don't know, like the older $10

company.

At the time, it was like the stock was down.

And again, I got very lucky.

You know, I wound up building this

ad ecosystem product called the Facebook ad network and with some amazing smart people.

And we went from $0

to a billion dollar business in three months.

In three months?

Yes.

I remember like, you know, I think $2.7 million a day is billion dollar run rate.

And it was a rocket ship.

And

I think, look, again, when you look back now,

I think we were lucky for two things.

One,

people were starting to buy things on their phone, right?

Because the iPhone had come out in 2008.

I think the App Store came out maybe a few years later.

And one of my mentors tells me,

there is no difference between being wrong and being early.

They're just the same.

But in 2012, 2013, people are starting to buy things.

So there was commerce happening.

So when there was commerce happening, people wanted to advertise and push their products, Target, Amazon, mobile games.

Second, Facebook at the time, you know, had actual authentic people, not like bots, which is a huge problem on the internet.

And third was we were able to marry that with these algorithms and products.

And

the big lesson I learned at Facebook is just like the power of working with great people.

So because I had this small team,

this guy, you know, named Vijay and others, and, you know, who were just fantastic engineers, right?

These are kind of people who would go off on a weekend and they would rewrite an entire system, which had taken a year for for a team, and they do it over a weekend.

Right?

Like, um, Palmer Lucky, you know, and I, we shared a common sort of hero figure, a guy named John Carmack.

Did he talk about John Carmack when he came on this?

I believe he did.

He did, right?

So, John Carmack, you know,

I think, by the way, one of the idols of the 20th century, John Carmack was the guy who built Doom, the video came Doom, right?

Oh man, I used to love that game.

Yes, yes.

So, Doom, you know, so do, and so Carmack is a programming god, right?

What he would do is he invented basically what is called the engine,

which ran under Doom and then under Quake and all these engines.

And then eventually he met Palmer because he was very interested in VR and they wound up doing Oculus together.

And then Carmack got hired into Facebook, right?

But the reason I bring up Carmack is that

there's this great story at Facebook where they realized Carmack individually was doing the work of entire 200-person teams.

Holy shit.

Just one person,

guzzling Diet Cook, right?

Like, I think he now lives in Dallas, right?

Like, sitting by himself, just like doing the work of 200 people.

At one time, you know, Facebook HR realized like, you know, they had nowhere else to promote him to because they just run out of levels to give him.

And he was just a machine.

And so the reason I bring this up is

it is very hard to make sort of get yourself to the top of an industry unless you know what greatness looks like.

So I was lucky because when I joined Facebook, I was surrounded just by sheer serendipity by some great engineer, just like I was at Microsoft, right?

So now, even though these guys are, by the way, to be clear, they were thousand times better than me.

They would run circles around me with anything technical, like without even batting an eyelid.

It's like me playing like a pickup game against LeBron or something, right?

But I saw what greatness looks like.

So which meant that many, many years later, when I was starting doing investing or when I meet entrepreneurs now, I now have a rubric in my mind of, okay, I know what elite.

talent looks like.

I see the work they put in.

I see how they talk, how they think, how they spend their free time.

So now I can sort of like, you know, if you know how like Steph Steph Curry shoots trees, and then you know how, you know, the kid you play with

at the gym shoots trees, you know, I kind of see what greatness looks like.

So I was exposed to Facebook.

I was exposed to some real greatness at Facebook.

So I wanted to bring ads.

It became a huge hit at Facebook.

And I think Silicon Valley is one of those places where it does a lot of good things, but everyone's kind of looking for, you know, what is the win you've had, right?

What is the thing which kind of like kind of says, okay, you are somebody who's capable of something.

And that whole thing gave me that.

Like I started to just get known as, oh, you know, Shiram's guy who kind of built all this stuff at Facebook.

And if you go Google me from back then, I would start showing up in all of these press pieces.

It's very important.

I think it put me and my wife on the map in Silicon Valley.

And so I'm very, very grateful for that.

Wow.

Wow.

You had mentioned something earlier

about five minutes ago.

I think you said there's no difference between being early and being wrong.

What do you mean by that?

So

I stole this from somebody we should talk about, Mark Andreessen.

Mark Andreessen is the inventor of the web browser.

He was the founder of Netscape.

Did you use Netscape going?

Oh, yeah.

Okay, great, right?

So the spinning logo with the stars and all of that.

So Mark Andreessen was kind of one of the original boy wonders of sort of technology world.

He built this browser called Mosaic, which then started this company called Netscape, which was kind of this darling child of Silicon Valley in the 90s and then got crushed by Microsoft.

But then, 10 years later, him and Ben Horowitz started this venture capital firm, Edrix and Horowitz, which we can get to.

I wound up joining later.

But for many years, he was a mentor, is still a mentor

for me.

And he has great, many sayings.

And so,

when you have an idea as an entrepreneur right like i think you know there are a lot of things which can go wrong and one of the things that you have to think about is that is this the right time for this idea right uh and like history is filled with examples of companies that had the right idea but were too early and die let me give you an example do you know what the company uh instacart does

right it's it's a a grocery shipping service, right?

Or DoorDash.

What does DoorDash do?

You buy a product, they bring it in from the nearby restaurant, or deliver you groceries, right?

Exact same company as Webband in the 90s, right?

One of the most famous dot-com bus.

People ask you, oh man, what was one of the biggest things in the dot-com era, which lost money, be Webvan.

They were right.

They were just too early, right?

Or pets.com, right?

Like another famous dot-com bus, but people have figured out later.

MySpace, right?

Like MySpace was our Friendster.

You remember Friendster?

Right?

Like, I don't remember Friendster.

But all these social networks, but MySpace, I'm sure you were on, right?

Oh, yeah.

You know, it was okay for a while, you know, and they sold to, I think, Murdoch, but Facebook did so much better.

And I think as an entrepreneur, you know, you have to think about, is this the right inflection time for my idea?

Because when you connect the right idea, the right entrepreneur, and the right time in history magic happens i'll give you an example you know if you look at youtube right so people think of youtube as you know um just obviously these days the de facto way to have videos online right but when they first came out it was uh other people had tried it right like um you know uh google had this effort called google videos that tried to get videos online others had tried it but none of them had really worked but youtube captured this moment in time because digital cameras were starting to explode and i think you started you started to see the increase of original mobile phones which had reasonable quality right and in 2008 the iphone comes out so one is you're starting to see more video production right like uh by regular people right without needing a camcorder or doing those home videos or needing a bulky camera you're seeing video production go up second is broadband around the united states was getting better Super important to basically get these videos to show up.

Like, I don't know, maybe remember the 90s, you open up a real player and like buffering, buffering, buffering, buffering.

You watch a minute, buffering, buffering, right?

Like, you know, in 2008, most of those issues are pretty solved and you could watch a video without it, you know, buffering.

And then, so these guys, like the YouTube founders, like Steve and Javad and all these guys, built this product, you know, which more than anything, just captured this right moment in history, right?

Like, and they rode that wave.

And I think a lot of times the difference between a

$500 billion

iconic company and some company which runs out of money, you know, is not the persistence or the heart or the effort of the entrepreneur, right?

It is just they were the wrong time.

And so when you're an investor, which obviously, you know, I kind of can get that, I spend a lot of time as, I often I was trying to think about, is this the right time

for this idea to happen?

Palmer is another good example, right?

Like, so a lot of people had tried virtual reality.

In the 90s, there was this thing called VRML where you were like, oh, let us embed virtual reality

in your, you know, in your computer.

And there are all these movies and TV shows which had virtual reality in it.

The Matrix is the most famous one, but there was a Piers Brosnan movie.

There were all these things that had virtual reality.

But the challenge was that the hardware was too complicated.

Nobody could figure out the hardware.

And there was no internet bandwidth to kind of show you these experiences, right?

So what Palmer, you know, and through his genius, through his sort of, you know, he told you this amazing story, you know, him sort of like figuring this out by himself.

He sort of captured the right moment in time with the camera gear, trying to figure out all the low latency interfaces so that the image that the camera sees is now, or the image that is being projected is kind of reacting with you in near latency.

So that was the right moment in time.

So I often think about like you need the right time.

The other thing you need is you need some luck and some magical lightning in a bottle.

And especially with consumer products.

I think with businesses and enterprises, it's a bit different.

Like you can go call up your customers and you can be like, hey, you know, you know, what do you guys want?

I can build that for you.

But with consumers, I do think you need lightning in a bottle.

so youtube you know they started taking all these videos they put it up i think an snl video once went viral they went off to the races facebook has a you know interesting history everybody knows about the facebook history about harvard they've all seen the movie with you know the social network movie but one of the other untold pieces of facebook history is that how did videos become a thing on uh facebook uh because for the many many years facebook only did photos right you fit you yeah by the way this all seems like ancient history, and anybody under the age of 30 is like, hey, folks, what are you talking about?

I'm on TikTok, Instagram.

But for a long time, you posted a photo on Facebook of your friends and you tagged them.

No videos.

Until,

do you remember this thing called the ice bucket challenge?

Yes.

Right?

Okay.

This is internet history.

So the ice bucket challenge was basically people raising money.

And what you would do is you would take this bucket of cold water, dunk it on yourself, right?

Like with a video camera in front of you.

And then most importantly, you would then shout out four or five people.

You'd be like, hey, I'm going to, you know, challenge my celebrity friend to go do the ice bucket challenge, right?

It would spread.

So I was at Facebook at this time.

And,

you know, and Facebook had just launched video, but they could not really get people to upload video or what is going on.

But the ice bucket challenge had this remarkable couple of properties.

One was that, you know, it was video and people had to create it on their own phones.

So it was personal.

But second, you need to tag your friends because you're tagging some friends.

Facebook just happened to have a platform where you could post a video and you could tag a friend.

You could not do it on YouTube.

So I remember being in this meeting

where with Cheryl Sandberg, where there was this vertical straight line and that was usage, right?

Because everybody was uploading videos onto Facebook.

And so every platform has one of these stories.

With AI, I would say it's Chat GPT, for example, which has a story.

But I think my point is that with consumer products, you need writing in a bottle and you need the right timing.

And often, you know, when I talk to an entrepreneur, I often ask them, what makes you so sure that now is the right time?

Not four years ago, not four years from now.

Why is today the right time?

Interesting.

I never thought of it like that.

And your explanation makes a hell of a lot of sense.

What,

you know, you went to work at Facebook and created the ad network and had a big part in the videos and

it sounds like you had a very big part in making it tremendously successful.

Your wife went into entrepreneurship.

What did she do?

So she started this.

I always tell people my wife is the more impressive person of the pair because it is true.

She's a multi-time entrepreneur.

You know, she's actually been through the journey so many times.

And so she started this company, which was about renting electronic gear.

The idea, which by the way, I think she would say was maybe a bit ahead of its time going backwards, our sort of theme.

The idea was that instead of renting, like, for example, you're surrounded by several high-end, you know, camera gear, but imagine you'd want to buy it.

You know, could you just rent it and then try it out?

Because you're going on a trip or you're going on a photo shoot or maybe you're renting a drone.

That was a big deal because drones are very expensive.

somebody was doing an ad shoot or somebody was doing like i just want to do this one you know scene for a day and they would rent out this gear uh you know to them so she raised money um you know uh from y combinator from a bunch of people and they did very well for a period of time you know they you know i think uh they are like a you know

a couple dozen employees maybe uh they are a lot of customers they love them but i think you know the challenge that they ran into is she would say is they were a bit early because now you're actually seeing other companies do that at scale because so many other consumer product categories have exploded, which need that dynamic.

And at the time, I think she was doing cameras and drones.

So yeah, she had a reasonable outcome, you know,

and I think

she had a great experience, but she was also like a bit early.

But also at the same time, my wife and I, you know, this is when we started to do some angel investing together.

And And she's a fantastic investor.

That's what she does now, you know, full-time.

But, you know, we had tiny bit of money.

We had a little bit of money we had made from Facebook.

And

one of the things about Silicon Valley is that

you just start meeting people who are starting companies all the time.

And we started to learn how to do angel investing.

And we would write like incredibly, I would say small amounts of money compared to what a lot of like other angel investors are.

are.

Sometimes we wrote like a couple of thousand dollars, right?

Like, and uh, uh,

and just because we wanted to support someone who was a friend, but I think that over the next four, five, six years taught me a lot about investing.

It brought me in touch with fantastic entrepreneurs,

actually,

some of whom have actually been on your podcast before.

And then, in a way, it kind of led me and her to our investing careers much later.

Interesting.

Yeah.

Very interesting.

And so, why did you wind up leaving Facebook?

I was bored.

I was a bit like Facebook is,

I think there's a pattern through my career where once I've sort of felt comfortable and settled in, I want to be like, okay, I want to find my next thing which really challenges me and push me.

So I think they were great.

A lot of friends there at the time, some have left, etc.

I could have probably stayed, you know, I was making decent money.

I'd have made more money.

But I was just like, I just want a different adventure.

I have that problem.

Yeah, yeah.

Like, I mean, if you look at my, you know,

when you're reading my bio, I was like, man, there's a lot of stuff in there, right?

Like, you know, there's like

this podcast, bro.

And part of it, I think, is just I just, you know, I've seeked out different adventures over time.

And so I was very comfortable there.

And also, there's a part of it, like I'm very suspicious if I'm very comfortable because I'm like, man, am I stagnating?

You know, do I need to push myself?

Like, I'm also very competitive.

So I would be like, am I not pushing myself hard enough?

Because I'm just showing up.

in this job where Facebook at the time has become a big company.

They don't really need me.

Because that's how we build these big companies.

You shouldn't have to need anyone.

That's how these companies are built.

So

I just, I get very restless when I'm comfortable.

One of the good things about my current job, you're never comfortable.

But I would just like, I was just bored.

I wanted an adventure.

And I was kind of, I was advising a few entrepreneurs.

I was doing some investing.

And,

but I would say what eventually that path led me down to is the first of two times at Twitter.

Right.

And so Twitter at the time, you know,

you know, there's a guy named Jack Dorsey who was running it, who was a founder, and they had been through a lot of really bad like turns as a business.

And one of the things I like to compare is like Facebook and Twitter as companies, because at a time in 2008 or 2009, Twitter, by the way, of course, now X, run by Elon, which we can come to had some little model there.

But Facebook, there was a time in 2008, 2009, Twitter was seen as the potential $100 billion, $200 billion

company.

And Facebook was like, oh, just this toy social network that just will never spread outside colleges.

That obviously flipped.

And part of the reason, you know, you know, I think is that

Facebook had a very methodical way of using metrics and data and numbers and experimentation.

Like one of the lessons I really learned from some of the people there was to always you know be distrustful unless you have the numbers and the experiments to prove it.

And the numbers back it up or the experiments back it up.

You should be prepared to change your line of thinking.

One of the things I think Facebook has been very good at is changing how they believe what they believe about things when they have new data.

At least the time I was there, very different company now.

You know, I don't really spend any time with them now, obviously.

So I kind of learned that mentality about like, okay, if I run this experiment, if I try something, if I learn something different, I'm going to change my worldview, right?

They were very good at that.

Twitter was very different, right?

They had this product, 140 characters.

It had worked.

And then one day it wasn't really working.

And they were a public company.

They weren't making enough money.

They had a CEO change.

So it was a little bit of a spiral, right?

Like you're a public company.

You know, people are comparing you to the other companies.

You're getting like a new CEO every year or two.

So it was a bad place to be.

And they were spiraling and spiraling.

And at the time, you know, I love.

Twitter and now X as a product.

I use it all the time, right?

Like, you know, it has given me so much.

A lot of my personal relationships have come from that.

Professional relationships have come from that.

I think it's just a fantastic product for the world in terms of, you know, just what it has done.

And, you know, somebody reached out to me and said, hey, would you want to help?

And I was like, yeah, sure.

Like, you know, it seems like a challenge.

The company is like a bit of trouble.

It was not glamorous, right?

Like, you know, it was not the sexy company to work in, but I really like it and seems like a challenge.

So I wound up.

joining there.

And that was quite the thing because one of the things I did not realize at Twitter was how insanely political, you know, in many different ways, you know, it was on the inside, right?

So that was quite the adventure, but that was, yeah, so I joined Twitter, I think, in 2017.

2017.

Yes.

You know,

before we go farther, I'm just curious.

I mean, what are your thoughts about

just social networking

in general?

I mean,

It's caused a lot of problems in the world.

I think it's also connected a lot of people in the world.

I mean, I've made a lot of contacts off X, Facebook, Instagram, not so much TikTok, but,

you know, but

I feel like it's a double-edged sword.

You know, it's also a great way for

government, anybody to kind of map out who you are.

It's immediate.

I mean, I use it when I get messages on any one of these social platforms and it seems like an interesting message.

The first thing I do is I go to the friends list, see who they're see who mutual connections are.

And, and so it's, you know, I mean, you're basically what a lot of people, myself included, I mean,

your life

goes onto these social networks.

It's easy to map you, it's easy to map your connections, everybody you're connected to, who they're connected to.

I mean, I'm just curious, you know, what, what are your thoughts on all of it?

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It's such a complicated question, right?

You know, first of all, like as somebody sort of worked in a few of these things,

I have some biases.

When you're a part of an institution,

I've been part of multiple of these institutions.

You sort of have an affinity.

You want to defend it.

That's number one.

But the second part is I've also seen the abuses that happen

when social media has real power.

I've seen the censorship.

I've seen the centralized control that can happen.

And

I've seen the harm that it can do for kids, for example.

You know, when we grew up, I didn't have to worry about, you know, was I a popular kid?

Would I get bullied if I said something?

I have a lot of friends with adolescent

daughters, sons, and they have to worry about that.

It is a very complicated topic.

I think the thing which I often think about is, and one of the things I saw on Twitter was

how censorship or nudging political agendas

can happen, sometimes deliberately, sometimes even not deliberately,

and how they can have huge impact, right?

So for example, people

think of like the Twitter files and all these examples of censorship happening at Twitter, right?

And I was there when some of this happened.

And one of the things I always sort of fought back on was

the influence of politics inside the social media algorithms.

Okay.

So often people kind of often know, I think, the easy ones.

They are like, oh, my account got shadow banned.

Right.

Like, or

I said something, like, for example, in COVID, you know, I said the virus came from a lab and you know, my account got blocked, which is, by the way, you know, the NIH director, Jay Bhattacharya, he said that his account got blocked.

And think about his story now.

You know, he's now like running the NIH, but Twitter deleted his account, right?

Like for basically saying, hey, maybe the virus came from a lab and, you know, maybe I'm not totally sure about the mass thing.

And it deleted his account.

And, but what I also saw was like how easily algorithms can be used to shape all things.

I'll give you a story.

I was Twitter one day and I wake up and I'm scrolling the internet and I see this story.

And I won't say who, but it is this famous Hollywood actor.

And it says that this Hollywood actor has this movie project that was just announced, but the internet is mad at him for getting this movie project and he might lose it.

And the reason it caught my eye was, you know, all these stories would embed the same two or three tweets inside.

And I worked on that.

You know, I ran a lot of the algorithms and I was like, hmm, these tweets look a bit weird.

Like, there's no followers, like, there's no likes, retweets.

How did these get found?

Why are these kind of getting surfaced up?

So I had some free time and I sent some emails and I poked around.

And it turned out what had happened is, do you know what

trending on Twitter is?

Yep.

So

at the time, you know, the trending algorithm on Twitter had all sorts of issues, all sorts of bugs, right?

And what it would do is sometimes it would try and tell you, hey, this is what people are talking about right now on Twitter, right?

It's trending.

Sometimes we just kind of pick a random arbitrary thing and say, it's not trending, right?

I mean, it couldn't find anything.

And what happened one night, that previous night, was it had found a random set of tweets.

And because it could not find a legitimate trending topic, this algorithm, by no one's fault, or someone's fault, but it's not

any deliberate agenda, right?

It said, these tweets by total unknown people about this actor is important.

Okay.

So this happens maybe at like 2 a.m., 3 a.m.

And then in the morning, right, like what winds up happening is on Twitter, there was this product called, there was a way where they could highlight these tweets and kind of give big imagery.

So one of these people wakes up.

And some of these folks are, you know, just sometimes had a political agenda.

But I think they were just like, hey, I just want to do my job, you know, and this thing is trending.

They did not know this came from an error.

So at 5 a.m.

or 6 a.m.

New York time, they take this and they go say, this is a thing which is happening on the internet.

Okay.

A couple of hours later, all these editors of all these media publications pick up.

They're like, oh, there's a thing people are talking about in the internet.

Hey, can you chase this story down and write about it?

And by the afternoon, I think that whole thing,

the guy's agent was getting calls and be like, oh my God, what is happening?

It's the internet is talking about this.

And the reason I bring up this story is, first of all, it's kind of silly, right?

It's like a Hollywood movie.

Nobody really cares.

But it tells you

how almost easily, inadvertently, you could

shape the discourse, right?

Shape the arc of something, you know, so easily, right?

And the combination of the algorithms, the metrics,

and some of the people inside Twitter meant you could really influence the world.

Like, I often call Twitter,

you know, a memetic battleground.

You know what memes and memetics are, right?

So

Twitter is a place where all these ideas fight.

And if you win, you get to spread all over the world a little bit.

And so one of these things that people wound up doing was finding ways to sort of inject their idea into this memetic battleground and try and fight everyone else.

Now, this was rewarded by the algorithm because what the algorithm was doing was it was looking at, okay, what is getting the most attention, likes, retweets, right?

And these were often things which were provocative, like had like made people angry, right?

Like and then those people would get followers, okay?

So there was this kind of the system which is being created where if you said something provocative and you made people angry, right?

Like one, you could kind of shape the discourse.

Second, the algorithm would be like, oh, this is what people on Twitter want because it's getting more attention.

I'm going to send you more followers.

I'm going to bump you up in the algorithm, right?

And this had two, I think, catastrophic impacts, right?

One was that the people who were sort of exhibiting some of the worst behavior, right, like were getting rewarded, right?

Like the more you get people angry, the more, you know, you get people outraged, the more attention you are getting.

But the second more subtle thing which was happening was when somebody new signed up on Twitter, right?

Imagine you walk into a restaurant for the very first time, okay?

You walk into some fancy, spancy Michelin restaurant, and you're like, okay, everyone's here in a suit or dressed up, right?

Like, and you're like, I gotta look the part.

Or let's say you go to, you know, a sports bar, right?

Like late night, you're watching a game, you know, it's a bit rowdy, you know the vibe.

The thing which Twitter was doing was it was shaping the vibe to be one where anger and provocation was rewarded as opposed to kindness, as opposed to education.

I'm not saying it wasn't exist.

There was a lot of it.

And obviously, you and I and others have had great experiences.

We're sort of pushing the ball over in one direction, right?

And when new people signed up, they were like, oh, I don't know what this place is.

Oh, but who's doing really well here?

Oh, it's that guy who's getting people angry.

By the way, this happens on YouTube.

This happens on platforms all the time.

What do people do?

They're like, what are the videos that are doing really well?

What are they doing on the thumbnail?

What are their, you know, the titles look like?

Let me copy that.

So, one, you're kind of giving people who are exhibiting

more wealth, certain literal wealth.

Second, you are training everybody new at Twitter.

Those are the icons, those are the people you should follow, right?

So, there was kind of this whole system which evolved.

And so, anyway, my point of this sort of roundabout explanation is: one, it taught me the absolute power of social media.

Second, that how these systems, when centralized, can have real power, right?

And real censorship.

And how it is important that you have absolute transparency.

Number one, we need to know what algorithms exist in these platforms.

We need to know that there is no ideology in these platforms.

So it kind of really was an awakening moment for me.

It kind of really shaped me.

Think of me as somebody on the inside, like, oh my gosh, like, you know, we need to sort of fix these things.

And this is why every platform, by the way, I'm not picking anybody.

Everybody,

every platform.

The second thing it kind of really sent me down the path of was decentralization.

This idea, which I think is kind of a lot of the crypto people, you know, would really resonate with is like we as people need to have ownership over how these things work.

We need to have a say.

We need to know what is happening behind the curtain.

And maybe we just don't have like one big thing.

We need to have a lot of other small things competing.

So it made me very distrustful of top-down centralized control.

And it made me feel like, okay, I need to find a way to bring more decentralized systems into the world, which kind of why I wound up in crypto for a while.

But yeah, so social media, I think, shaped my career.

It's given me a lot, but I also saw a lot of sides of it.

My Twitter time was deeply formative for me.

And when I left,

you know, I went up investing, but part of it is like, okay, I need to find ways to battle some of the negative things I saw over there.

That makes a lot of sense.

You know, that makes a lot of sense.

I mean,

it's just such a powerful tool.

I mean, back to,

you know, 2020

election timeframe.

I mean, we saw, we saw what appeared to me, you know, from the out from an outsider is, you know, we saw a sitting president get banned on X, get banned on Facebook, get banned on Instagram, get banned on YouTube,

banned on all of these networks.

And so, you know, the way it appeared to, I think, everybody is that these top guys, you know, that own these companies are controlling

the entire narrative, everything that's going out.

And, you know, it appeared, and I didn't know, I don't think it appeared it was that way.

Everybody leaned one way.

And, you know, that was,

you know, obviously towards the left.

And, and, and it, it,

I mean, they depoli, what was that one platform?

They, they just pulled it a AWS puller.

Parlor.

Yeah, they just pulled it.

I'm not, I'm not sure why.

I don't know what is going on down there.

But, you know, it was like, holy shit, like, now there's an entire party

with zero voice to include a sitting president.

And

that really,

I think, opened everybody's eyes immediately of how powerful and

dangerous that this could be.

The deplatforming was huge.

I think in a way, like, I had sort of seen the building, I had seen what was building up.

So I was not terribly surprised when all of that happened but if you think about that era right number one was you had the previous administration putting pressure on the social media platforms to take down content right like they would send these angry emails this is now all documented and it's come out in you know depositions and lawsuits and hearings and whatnot but they would send all these angry emails to say hey you you need to take this tweet down right like we don't love this tweet about hunter biden like we don't like this tweet about uh you know mask mandates or whatever the case may be so they would send this down the second thing i think what is happening was uh this was the peak of the culture wars right and these platforms where like there was this domino effect where if one person you know took down a video a piece of content,

you know, downranked something, shadow banned, for example, then every other platform immediately felt pressure.

Because what would would happen is all of a sudden you would get an email from the former White House, a member of

Congress, or a New York Times hit piece, which would be like, hey, those guys have taken down this thing.

You guys are leaving this up and you are responsible for all these crimes.

And so they try to enforce the overturn window.

of conversation and they try to really shrink

of what can be said.

And I think

in some ways, I think the platforms, I think the turning moment,

in my view, and some people may disagree, is when,

well, obviously before this election would be when Elon bought Twitter.

Okay.

Because I think that totally changed how free speech on the internet works.

Because all of a sudden, you had one platform.

And by the way, I was there.

I was there on the first day.

We're kind of jumping ahead a bit, but

I had spoken to Elon and he told me he was going to do this.

I had left Rita at the time for a couple of years

and I joined this venture capital firm.

But Elon said, look, I'm going to do this thing.

Can you come help me out?

And for me, it is a little bit like getting a do-over.

because I could go back and this is not an official capacity.

I was not an employee, but like maybe I can go back and I didn't have the power to do some things and I didn't have $45 billion dollars to spend on a social media company.

By the way, that was a problem I had, uh, but now I have a chance to put some things right, okay.

So, uh, do you remember when Elon bought Twitter the Let It Sink In Dave when he bought the sink in?

So, I showed up that same day, uh, kind of snuck in, making sure the TV crews didn't see me.

And that was such an experience, uh, just watching Elon work and trying to sort of clean up the company, finding all the ways that, uh, you know, sort of these progressive levers had been hidden.

And for me, it was a chance to kind of like put right some of those things.

And I would say that moment changed how free speech on the internet works, right?

Because all of a sudden you had a major platform, Twitter, 10X, which was trying to live by free speech,

which brought back the president, right?

You know, which brought back a lot of people who had been taken down for just asking simple questions like: hey, what is the origin of the COVID virus?

Are masks effective?

Or

how can you say that we can't sit together in a restaurant, but a protest is okay?

Like, how does that work?

But even just the ask a question, just get your account bland.

And here's a platform that was bringing it back.

And look, people have a lot of complicated views on Elon or the company, but I do think that moment was huge in changing how

free speech on the internet works.

And

I think even today that is not appreciated for how important that moment was.

I mean, I think it revolutionized everything

immediately.

And I don't know.

Were you on Twitter?

Were you active then?

You must have been.

Yes, I probably wasn't very active.

That's probably the,

I don't know, that's maybe the platform.

I used to be least active.

I'm a lot more active on it now, but

I really pull away from,

I go on there mostly to see how our content's doing

because I do think that there is a lot of toxicity.

I know there's a lot of toxicity that comes out of all these platforms.

So

I try not to fall into that.

But I mean, I think it was,

well, I don't think I know it was instrumental in what Elon did because

from an like, once again, from an outsider looking in, what I saw was he would have capitalized on the entire market and taken the entire market share by providing an actual free speech platform where you don't have to worry about asking questions.

You don't have to worry about calling out corruption and you're not going to be censored.

And I think that all these other companies, Meta, Google, you know,

maybe Amazon, I'm not sure.

But, you know, I think that they saw that happening and they thought, oh, shit,

if we don't loosen the reins up a little bit here, we're going out of fucking business.

And I think they would have gone out of business.

And with some of them, I'm actually surprised that they didn't just because of the repercussions of what they did to half the country.

Oh, yes.

But I think that they saw that gaping hole in their business when Elon secured Twitter.

and turned it into X and everybody else had to follow suit.

What do you think?

Am I wrong on that?

I think you're very right.

I think there's another dynamic, which is courage,

which is he just took a lot of the arrows back then.

And so when he did that,

some of these companies, you know, they just want to stay out of trouble.

Like they would love it if there was nothing political like ever said on their platform.

Like they really don't want me in the business of navigating where the COVID virus came from.

They just want to look, come here, have a great time, have great content.

We want to sell some ads against it.

Let's go home.

Okay.

But that's not the choice, obviously, when you're running a major platform.

It's almost like running a country.

So they got sucked into it.

And I think, you know,

one of the,

there's an amazing book you should read from the 50s, a bit hard to get on Amazon.

It's called Private Truths, Public Lies.

Private Truths, Public Lies.

Sounds interesting.

Yes, and this idea, and I think it's out of print or something, but it's a very simple idea.

It's a very simple idea that sometimes in society, everybody starts to pretend to believe in a lie just because it is the convenient, expected thing to do.

During COVID, right?

You would somehow have to wear a mask into a restaurant.

and be asked to do so, but you could take off the mask once you sat at the table.

You're like, okay, hold on a second.

How does like these two logically, this kind of like totally make sense?

There's something wrong here, right?

But you can't really speak out against it.

Or if you did, there were consequences.

Okay, so what this book says, the second part of this book, and it's a great book, please I'm oversimplifying, is what it takes is it takes one person or an entity to point out the emperor has no clothes.

Okay, all it takes is one.

But when you have that one person do so at usually like sufficient like kind of like risk to themselves, everyone else starts to fall in line.

Makes it okay.

Makes it okay.

You had two guests on your show who've done this, right?

Like, you know, Brian Armstrong with his mission-oriented company statement.

Like, did you talk about that when you had him?

We did.

Right, right.

So that's such a great story.

So Brian,

please go watch it episode because he talks about it, but

he basically gets bullied.

into having to put out a statement, right?

Like, which he doesn't want to.

And he doesn't like the fact that he's being bullied.

right?

And he says, listen,

we are not a political social company.

We are in the business of making, you know, crypto available safely, securely to everybody.

That's the job.

That's the job we are in, right?

So he puts out this blog post, which was hugely controversial because he was accused of being racist.

He was accused of fronting the times.

And he says, like, okay, we are a mission-oriented company, which sounds crazy that it was controversial.

But he says, if you work here, you are signing up as a part of this mission,

which is to make

crypto available safely, securely at scale.

If you don't like this mission, don't work here.

No harm, no foul, okay?

Go find a job somewhere else, right?

If you care about something more than this, that's also fine.

We just ask that you do not bring that into the workplace.

Because in the workplace, we care about this mission.

It's a big mission.

We have competition.

The stakes are high.

The rewards are high.

It's going to take a lot of energy, right?

And as long as you focus on this, we don't care about anything else.

But that was so controversial.

Because at the time,

I was watching inside these tech companies the rise of DEI, right?

Like I remember.

You know,

my wife at the time had a little bit of a stint at

Meta and you would have these employees who just totally hijack meetings.

And they would ask people to issue apologies.

They would say, We have to comment on literally everything happening in the world.

And a lot of Silicon Valley executives were just scared.

Maybe they should not have been scared.

Maybe they were.

Scared of their workforce?

Yes, they were scared of their own employees.

They were absolutely scared of their own employees, right?

Like they were terrified of, man, I don't want to seem, you know, pick andist

sexist racist whatever it is like I don't want to seem that right and they would get attacked all the time I spoke to some really famous people who are like

I don't want to hire this exec but I'm being forced to because if I don't I'm going to be accused of discrimination in some shape or form

And then it's going to piss a lot of other people off.

Then it might piss some of my investors off or the media off.

I don't know what to do.

And there were so many many people.

And I think, look, if you're harsh, we can see they didn't have enough courage.

But also, look, they had a lot of employees.

They were trying to make sure like the business doesn't get into trouble.

They had customers.

And they're like, we don't want to be the political game, but I'm scared.

And this was a thing all over Silicon Valley.

It was almost, I would say,

a rising infection, which just spread by 2020.

A virus.

Yes.

Like, I remember kind of going, jumping back a bit, the original moment when I felt the rise of DEI in Silicon Valley I think this was in 2013 2014

and there's a company called GitHub they are a popular developer company they build like source code products for developers and at the time they had actually a funny a replica of the Oval Office okay that's kind of a thing and they had a carpet like instead of you know the presidential like seal you know with the bald eagle there was a carpet which said with their logo and it said in meritocracy we trust okay

and that you would think that's safe meritocracy you know if you work hard you know um you're the best at what you do you win that was hugely controversial at the time and I remember a lot of us going that's weird right like you know can you imagine like an NFL draft combine where if you say hey you run a 4-4 you know

you know you're pretty good at maybe being a wide receiver

and they're like well you can't talk about that.

It's just like racist.

But that became a real thing.

And then I saw over the years, quotas,

you know, me, a lot of other people, we would get into hiring situations where you'd be told, hey, unless if your entire team, you know,

is a

male white, pick your thing, you're being racist

or sexist.

And you are like, well, look, I want to hire amazing people, right?

I don't care where they are.

You know, I don't care what they look like.

I just want to hire the best people to the job.

But there was a lot of pressure I know on Silicon Valley execs to be like, okay, my board has to look a certain way.

My exec team has to look a certain way.

Otherwise, the New York Times is going to come after you.

And you might lose your job.

And some people did lose their jobs, by the way.

So this was

a bad space to be.

And I think...

A lot of people outside Silicon Valley don't recognize how bad it got.

Like I was at this venture capital firm, and you know, we used to get calls from all these founders, being like, I'm just so terrified of my own employees.

I don't want to deal with this.

Like, I'm just building, I just want to build a company.

I want to build a product, serve my customers, help my employees, you know, hopefully we all make some money.

I am not interested in weighing in on the latest social issue, but they were forced.

And so, the reason I bring this up is when Brian Armstrong did that, right, like he was taking a huge risk.

And I'm not sure he kind of took enough credit for it when he did your podcast, but he was taking a huge risk, right?

He could have been fired, right?

They were a public company.

He could have been ousted.

You had all these ESG firms.

You had all these firms kind of stopped doing it now in some ways, thanks to who won the recent election.

But his idea that, hey, unless you kind of check off all these boxes on the environment, on diversity, we won't invest in you.

And if we are on your board or we're on your cap table, we are going to put pressure on you to do these things right uh and uh so he took a lot of risk and i think it was not easy for him but when he did that um so you know one i have a lot of respect for him because he to do that he could have just played it safe he could be like yeah i'm just going to say the things which everybody wants me to say and you know i'll be in the cover of time and i'll be happy right but he took on the crowd, right?

He took on all these folks who are trying to bully him.

So number one, he deserves some respect for that.

second but when he did that it sort of opened the Orton window people like oh wait I can do that right like I can now start like saying oh wait maybe we just need the best hire I don't want to just fill a quota

and Alex Wang who you had

you know he did this thing where he said instead of DEI

you know I want M-E-I

where

meritocracy, excellence, and I forget what I stands for, but it's the idea that we focus on things you kind of want in a workforce, right?

You know, you want people who work hard, you know, you want the best of the best, right?

Like, you want,

and, you know, and you don't care how they look like or where they are from or what they do in their private lives.

So Alex took some heat for that, Alex Mang, when he did that, but that set the tone.

So I have a lot of respect for some of these people.

I worked with some of them.

We spoke about

folks like Balaji Sinivasan, who I think are similar,

who took these arrows when they didn't need to and then opened the Overton window for a lot of people to follow them.

I mean, I think Silicon Valley listened.

Well, maybe they didn't listen, but I mean, it seems like, you know, talking to, you know, talked to a lot of innovators in the tech space recently this year, and

a lot of these guys moved down to El Segundo, it seemed like, for a different culture.

And so now, now we see, you know, and I'm not terribly familiar with it.

I've never been to Silicon Valley or El Segundo, but it seems like El Segundo is rising up as is

like Silicon Valley 2.

Yes.

I think, yes, for a certain class of companies.

El Segundo, that part of

that whole community, they have a lot of ties to sort of the defense establishment, to making hardware.

And so, which is why you're seeing a lot of these American dynamism companies come out of there.

They can pull talent from elsewhere.

And I think the other places which I've done start doing really well.

Austin, Texas has started doing really, really well.

I always have a soft spot for like Raleigh, North Carolina.

I think they have a great ecosystem there, which is awesome.

Sometimes you have these ecosystems outside Silicon Valley, which is great because you get these people who

don't have a huge ego.

They want to work hard,

and they're not going to switch your company every year and go join somebody else.

But I would say Silicon Valley is still still really important,

just because if you think about a lot of these AI companies, for example, a lot of them are in Silicon Valley.

And

so one of the things, you know, just

a few plugs in, one of the things we've done in this administration to combat a lot of these things about wokeness, about politics and platforms, is we released this executive order.

President Trump signed this executive order three weeks ago, which is called like stopping woke AI.

And I was, you know, I played like a big role in this along with David Sachs.

And the whole idea behind the executive order is that,

you know, it's not that we want you to pick a left versus right ideology.

We just want no ideology in AI, right?

Like we don't want employees to put their thumb on the scale and sort of

embed their beliefs into such a crucial piece of technology.

And this is kind of sometimes accidentally happened.

Like, for example, last year, there was this sort of infamous incident where if you asked a leading large language model, show me a photo of George Washington, it showed you a black George Washington, right?

And it was sort of an accident.

And it's kind of, you know, and I think it's not like super deliberate, but there are other cases which are way more insidious.

And

I think given that, and given the fact that a lot of these AI companies are in Silicon Valley, right, which often just have a very left-leaning ideology, you know, I think it's super important to figure out, okay, how do we make sure we don't have a repeat of what I was talking to you about what I saw at Twitter?

How do we make sure that?

And by the way, with AI, it's going to be so much more important than social platforms.

It's going to be so much more important.

It's going to be so much harder to find things.

So what the executive order says and a lot of other things we have done says is, number one, no ideology.

We want no thumbs on the scale.

Number two, we want transparency.

We want to know, you know, if you say a certain answer, a certain, you know, even example, a political comment, that's fine.

Just tell us where you got it from.

Tell us what your sources are, right?

Like, you know, let the audience, let the viewer, let the person interacting with you, let them make up their own minds.

Like, don't hide it, right?

Because I think if you go back to my Twitter story, right, that story about this Hollywood movie, if somebody could tell how the algorithm was working, right, they'd be like, oh, wait.

Something's weird.

Let me go investigate.

So I think sunlight is the best disinfectant, right?

I am a transparency maximalist when it comes to technology.

So, with this work AI EU, with other things we have done, we are like, all right, these things are so important for our economy, for the world.

And we want to make sure there is one, no politics, and also we know what's happening behind the scenes.

How does an ideology get inserted into an AI platform?

Is that from the engineers?

Or, I mean,

she's processing so much data.

I mean

i'm probably way off but the way i understand it the way i took it from alex wang is that you know

you've you have these enormous data centers and that's that's what the what that's what the ai model you know pulls from and processes and you know gathers the data processes it and presents it to you and so i mean i would imagine you know and i don't know what all goes into that but i would imagine it would be fairly easy for a rogue engineer to to insert his own ideology and then it goes unnoticed by the rest of the company.

Is that how that happens?

There are many, many ways how

ideology can be inserted.

Like the word ideology is so broad and vague.

So I'm an engineer.

Let's make it very specific.

Okay.

Let me give you actually maybe a non-AI story and then we come to AI.

So when I was at Twitter, right, for a while, there was this phenomenon where left Democratic congressmen would sometimes, or Democratic political figures, would get ranked higher in the algorithm.

They got shown more.

Like in the YouTube algorithm, you know, like the algorithm bumps you up, just like on Twitter, than figures on the right.

And the reason that it happened was

when you train the Twitter algorithm, you give it examples of good and you give it examples of bad and you tell the algorithm, hey, go find more things like this.

And the people who were sometimes giving these lists, and

I'll just give them the benefit of the doubt, right?

I don't think they were trying to put a thumb on the scale, but they had certain beliefs.

They stuck the news organizations they followed.

They stuck the political figures they liked.

They maybe didn't know or didn't approve of people on the other side.

So the algorithm kind of learned good to mean a certain class of views, a certain class of publication.

Okay, and so those guys start getting more traffic, you know,

more attention.

And so it kind kind of spirals.

So I bring up that story.

So very easily, and sometimes even without any mal intent, sometimes there is like mal intent, even without mal intent, you can slide these systems.

Okay.

Now with AI, right?

So

very simply, you know, just kind of like levels it a bit, right?

The way a modern AI model works is there are kind of like two steps.

One is a process called training.

And the way I would think about it is you take all of human knowledge, all of the internet, imagine this sort of massive, like kind of witch's cauldron, you know, but imagine the cauldron spanned like multiple data, you know, football fields.

You dump it all in, like every book ever written, every movie ever made, all of Wikipedia, right?

If you're Google, all of YouTube, you know, every bit of human knowledge ever gathered, you stick it in there, right?

And then you have this algorithm, which I really want to talk about.

Try and make sense of it, right?

You know, so for example, right, you know, it says that the word Sean,

what should the word Sean be followed by?

Okay, let's say I say, okay, word Sean followed by Ryan.

Then you're like, okay, Ryan, and then what comes after that?

Well, the Sean Ryan show,

operator, military, intelligence, CIA.

Makes sense.

Okay.

Let's say after Sean I say Michaels okay then you get title wrestling heel face stone coal so it is kind of training and trying to make sense of all of this knowledge okay so that's called training then

there is a separate step where you you know you kind of take this kind of this large blob and then there is a step called post-training where you are basically trying to make the model better in specific ways.

For example, you're trying to make sure it gets better at, say, coding, or you're trying to make sure it gets better at science, and you're trying to make sure it gets better at these, you know,

in these kind of these very targeted ways, right?

Like you might have heard of this phase called fine-tuning.

You're trying to make it better in these very targeted ways.

And so that's, at the end of this, you kind of get this fully cooked model.

And then you have inference, which is you go to ChatGPT or you go to Grok or you go to Gemini on Google or you go to Claude, you type in a question, right?

And then it starts giving you letter by letter, word by word.

Like that is inference.

Like you're basically giving, getting back answers.

So the point, I want to kind of explain this whole thing, just kind of ground a lot of the other conversations we're going to have.

But also every step of this, right, like could be infected by ideology, right?

Number one, let's go to

the step of this big cauldron.

What if you only stuck

left-leaning left-leaning content in there?

There's this data, gosh, I wish I could remember this off the top of my head, that a lot of the written internet is left-leaning in nature.

And so if you just dump the internet in there, you could just get a leftward bias just right there.

So just by sort of the sources of data, your model

could wind up learning

just a certain ideology.

Second is when you fine-tune these things, right?

Like, you know, for example, DeepSeek, which, you know, we'll probably wind up talking about this Chinese model, right?

There's a lot of evidence that it was fine-tuned to add

Chinese ideology, okay?

You know, say nothing happened in Tiananmen Square, right?

Like, or, you know,

or, you know, what China thinks of Taiwan.

That happened in that part of the process.

You know, another part of the process you could add things are, is when the model is trying to react and give you a token and it is thinking, right?

A lot of these models have instructions on how they should think, rules they should follow.

You could set up a rule which says pick the answer which optimizes,

if you're me, I would say optimize for truth.

Or you could say pick the answer which optimizes for equity.

in the DEI, right?

And it's going to slightly slide the model some way, right?

Or pick the answer which is least offensive, rather than pick the answer which is intellectually honest, right?

These are incredibly oversimplified examples, but you could see that, right?

And so any one of these steps could have either deliberate or accidental ideology inserted.

Now, in the Google case, and I could be wrong, you know, because I only sort of read some press reports later.

I don't know what actually happened.

I think what had happened is somebody by accident had added this idea that whenever the model is trying to generate photos of human beings to try and generate people of every race.

But then you're like, wait a minute, if you get a photo of a Nazi, right?

Like they're probably not Asian.

That's not what the average Nazi in Germany looked like in 1940s.

Or if you have a photo of a Viking warrior,

they probably didn't look like me.

That's not what Vikings looked like

when they flew, you know, shipped out from Norway.

But this little thing was like, oh, whenever we ask for a human being, I'm just just going to spread the human race out there.

So, what happens?

You get the black Pope, the Black George Washington, right?

So, so, and

I hope I'm not making this too complicated, but this idea is that

these things can be very subtle, they can be hard to find, they can be deliberate or inadvertent.

And for me, you know, in this role, I think, look, one of the things we really care about is making sure that

there is searching for truth and that there's no ideology of any kind.

And if you look at the executive order, it doesn't say you need to optimize for the right.

It says you need to be truth-seeking.

Optimize for the truth.

And if you don't know the truth, express skepticism and tell us what you're reading.

And my hope is that

regardless of whether you agree with me and you on our political beliefs, you will probably agree that truth-seeking is a good thing.

So that's a hope.

Wow.

It's a great exploration.

Best I've heard.

Thank you.

Thank you.

Thank you.

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All right, Sri Ram, we're back from the break.

We were talking about Twitter, how you got into there when Elon took over and

basically eliminated the ideology of wokeness of Twitter.

But, you know, something that we didn't talk about yet is A16Z, Andreessen Horowitz VC firm.

And so I'm curious, you know, we've had some offline discussions about investments and things like that, but I'm curious, how did you get picked up for that?

How did you find your way into there?

So

A16Z stands for Andreessen Horowitz.

So

A, followed by 16 letters and Z and A16Z.

It's kind of a tech thing.

And

so they're one of the leading venture capital firms in the world.

I would say the leading venture capital firm.

I think they're the largest in terms of money they have.

And the founders are

these two iconic figures in Silicon Valley, Mark Andreessen, who we spoke about, who invented the web browser, and Ben Horowitz, who was with him at Netscape and is a best-selling author, among many, many other amazing things.

And

in a lot of ways, they

revolutionized, in my view, the way venture capital worked in Silicon Valley.

This is a little bit of history.

So when people sometimes think venture capital,

they think shark tank.

You know, you come in, you kind of kind of, you know, you pitch an idea, you know, some like rich person in a suit gives you some money or not.

There's some element of that, but it's actually a lot more complicated.

The history of venture capital actually goes back to whaling and fishing.

So back a couple of hundred years ago, when you would get these sort of sailors or whalers, I don't know what they did, they'd be like, hey, we're going to go out and we're going to go into these stormy seas and take a lot of risks and be out for a few weeks, maybe catch some whales and come back.

And it's an incredibly risky investment, right?

Like half the time they don't come back.

Let's just say

the hazard rate was pretty high.

And so they go around and they would go to people with wealth and they'd be like, you know, why don't you stake me, you know, on this journey and I will give you a percentage of the whale I carry back, right?

Which is, by the way, the word carry in venture capital comes from that.

It was literally sort of, you know, the whale and sort of the thing that you carry back.

You would get a percentage of that carry.

So even 200 years later, that word has kind of stayed on in sort of the risk capital discourse.

And so the history of venture capital is super fascinating.

And I think it's an essential part of how American innovation and Silicon Valley have existed.

So in the 70s or 80s, what would happen is

before venture capital, if you're an entrepreneur, right?

How do you, you have an idea, how do you go get money?

You go to a bank, you get a loan.

Maybe you have some friends and family, you know, they give you some money.

But it was very, very hard to go to a bank and say, I have a really risky enterprise and technology, which you may not understand, but I need a few million dollars.

And by the way, you may never see it again.

And

you may not have friends and family who can do that.

So I'm going to say in the 70s,

there was a set of folks who wound up forming Sequoia Capital and Kleiner Perkins, who kind of developed the modern venture capital industry.

These were folks that made some money from Silicon Valley, sort of the original silicon in Silicon Valley.

They had kind of been part of these big chip companies.

And, you know, that's where the word

Silicon Valley comes from.

They made some money and they basically said, okay, we are going to stake these entrepreneurs, you know, fund them on their journey, not out of sort of the goodness of their heart, because we know that when these companies do really well,

we stand to make a huge return on our investment.

But the thing, which I think is very different from the rest of the world, is they were willing to lose their money.

They didn't love it, but they're willing to kind of take bets on these risky enterprises.

So I think if you look at a lot of these amazing companies in Silicon Valley, Apple, right, for example, or Google or Netscape, they all had one of these venture capital firms who are essentially taking bets on a totally unknown person and saying, I'm going to give you some money.

Famous example is Google.

So Google comes by, I think, in 1998, right?

And again, I'm dating myself here, but Google was not the first, the second, the third, maybe the fifth or sixth search engine.

Do you remember using like Ask Jeeps?

Like us?

Yeah.

Yeah.

Right?

Like or yahoo.com, like Yahoo was another famous one.

And, you know, and back then, you know, you would use these search engines and people like, well, look, search is really not a business, right?

We don't have to make money off it.

It's been solved.

And then these two guys, Larry Page and Sergei Brin, basically come out with a new algorithm, right?

They were the Stanford computer science guys.

They came with this new algorithm called PageRank.

By the way, PageRank is super interesting.

It basically says that I'm going to think you are important if a lot of other people who are trustworthy also think you're important.

And that, in one oversimplified sentence, is kind of how the origin of Google worked.

But they were like, I don't have any money.

They actually went to a lot of other companies and they said, do you want to buy our algorithm for a million dollars?

So they went to all these existing search engine companies.

Imagine, by the way, you just bought like original Google algorithm for like less than a million bucks.

And everyone just said, no.

So they didn't know what to do.

And so they, I think they came to two essential parts of the Silicon Valley ecosystem.

First is angel investors, and the second is venture capital.

So they went to basically kind of these wealthy Silicon Valley guys, this guy named Andy Bechterstein, and

they said, listen, I have this idea.

We need some money.

And Andy, I think, kind of gave them $100,000.

They didn't have a bank account, so they didn't know what to put the money, so they kind of kept it and started building Google.

But so think of this construct: two guys, crazy idea, nobody thinks it's going to work, but the ecosystem and the culture of the valley was like, okay, if we think that you have a shot at this and you've done some work, right, there are probably enough people, capital, going to take a bet on you and probably going to assume that 90% of the time this money is not going to come back.

Every once in a while, you're going to create an iconic company.

So Google then, of course, gets funded by another iconic firm called Kleiner Perkins.

And then, you you know, they go IPO.

They obviously kind of become the huge giant they are.

So all of Silicon Valley has these stories of these amazing companies, but these venture capitalist firms who are at the heart of it.

So this story is very interesting because Andreessen Harvard's totally revolutionized, in my mind, and, you know, this ecosystem.

Back in the day, venture capital firms were sleepy.

You know,

they were kind of behind the scenes.

They would never say anything in public.

They didn't want any attention or controversy.

The idea was you come in, you pitch us, you know, go on your way.

The other thing was strategically, what would happen is you would go pitch a person at the venture capital firm, a partner.

Usually they had like five to eight partners.

And that person would be assigned to you.

So, and that person, if you needed some help, like maybe like, hey, man, my company is failing.

Like, I need some advice.

You had to go to that one person for advice.

If you're like, hey, I need a contact in the Pentagon, like, do you know somebody at the DOD?

That person better have a roll on X, right?

But you're essentially the one person.

So anyway, so Mark Andreessen and Ben, they had their own experiences with bad venture capital forms and a lot of bad ones, right?

They, you know, they do a lot of bad things to founders.

They, you know, throw CEOs out.

And they also were like, listen, why is it that

when we go, we have to rely on this one person and we need all this other help?

And they met Mike Owitz.

You know who Mike Owitz is?

I don't.

So Mike Owitz is the founder of Creative Artists Agency, CAA, right?

I would say along with WME, the two iconic Hollywood talent agencies, right?

He's a guy who's represented like every Hollywood, I think he's retired now, but he's representing every Hollywood celebrity, best-selling author, founder CA.

And CAA had this amazing strategy.

to win the market, right?

What they did was like, number one, they said, we're going to be very loud, right?

Like, we're going to make sure everybody knows our name.

We're going to be brash.

We're going to use these red binders, which are color attention grabbing.

We're going to get people to pay attention to us.

The second, and this is very interesting, they said, if you sign up with us, you are a A-list actor, right?

You are with an opposite.

The way the reason you should sign up with us is you're not just getting me, Mike Owitz.

You're going to get the entire firm's Rolodex.

And this firm is going to maintain Rolodexes.

just for you.

We're going to maintain a list of actors.

We're going to maintain a list of producers, directors.

you know, and so if you come in and you have an idea, you know, we don't need to go find the right editor.

You don't need to hope that I have a friend, you know, who can, you know, direct your movie.

We have entire teams whose whole job is to maintain a roster for you at all times.

And they would go and win all these clients because you would go, what is your image of a Hollywood agent?

A guy in a sharp suit, right?

Like, you know, on a phone, quick talking, maybe as a Rolodex.

CA industrializes.

They had some of that for sure, but they industrialized it because they're like, you come in, we can plug you into this machine, which is going to make great movies for you, make you famous, right?

So Michael was Mark and Reese's mentor and friend.

So Mark and Ben heard this and they were like, why don't we do this for venture capital firms?

Because let us say a typical entrepreneur, you know, we spoke about some, you're in your 20s, 30s.

You often don't know what it means to build a business or you're good at one thing.

Let us say you're good at building technology.

You're great at computers like I used to be, right?

Or maybe you just know your product area very well.

You're great at making ice cream.

You're great at building rockets.

But are you the best CFO?

Are you the best marketer?

Do you have a Rolodex of government officials?

Something goes wrong.

You need all these other things who these young CEOs didn't know.

Or let us say you run into trouble.

You're running out of money.

How do you restructure a deal?

How do you close a big customer?

How are you supposed to know these things?

So what Andreessen Horbitz said, Mark was like, we are going to copy and replicate the CAA model, but for technology venture capital.

Okay, so we are going to have a roster.

We're going to have a roster of every single amazing CFO in Silicon Valley, every single amazing marketer.

We're going to maintain a roster of potential board members.

So when you come in, you know, 25-year-old with this idea, who has something working, We are going to plug you into the system.

You want a CFO?

We have everybody on speed dial.

We have done them favors.

So they will pick up our call.

We can get you in.

By the way, they can also help you hire a CFO.

So often for young founders, they don't know how to hire executive talent.

How do you hire a 50-year-old head of sales if you've never met a great sales leader before?

How do you even know how to do that?

We have the team who've seen every great sales leader help you do that.

So that was a different product, right, from classic venture capital.

So number one, instead of one person Solar Decks, we're going to give you the whole sort of system.

The second thing, they were loud.

They were brash, right?

They had press articles.

You know, Mark Andreessen wrote this famous blog post called Software is Eating the World,

which basically said that

every business on planet Earth is going to have software underpinning it.

And I think in some ways, I think he's been proven right.

Anyway, so there's a lot of backstory.

And this is kind of some of the tactics A16Z used to, I would say, become one of the most famous powerful firms in Silicon Valley.

So how do I come in there?

So Mark has this great strategy, which he calls harpooning.

In the venture capital or tech business, right?

Like if you sleep, if you are not paying attention to what the next generation is building, time will pass you by.

You have to stay current.

You have to stay always on the edge of what people are doing.

And Mark, and there are many others who are very good at this, like Peter Thiel, Lonsdale, who I think has been here, amazing people.

Mark was extremely good at it.

And he would have this tactic he called harpooning.

Okay.

And what he would do is if he saw anybody online who had written or done something interesting, he would send them an email.

And getting an email from Mark Andreessen is like, he's a very notable technology figure.

So you're just like sitting here like, wow, what is that?

And the reason you do that is like, I want to get to know this person before they become famous, before they build this next 3D.

It's a little bit like, you know, you see, I don't know, a 15-year-old who has amazing skills and, you know, I don't know what the legality of this as a coach is.

You're like, okay, I'm going to make sure I'm like building a relationship with this person because then someday, if they want to pick a school or a team, I have a relationship with this person.

So Mark was very, very good.

I'm pretty sure even to this day, he starts sending out these emails in the blue.

And he harpooned me.

You know, I had written a blog post in, I would say, 2012, 2013.

And I get this cold email one day from Mark Andreessen saying, hey, I like this blog post.

And I was like, whoa, you know, and

this was a very different time in my life.

So it was quite shocking.

Another blog post.

Huh?

Blog post.

Yes.

Blog post to Microsoft.

No, I had left Microsoft and this was about.

Yes.

Yes.

There's a whole pattern here, by the way.

If you can take a slight tangent, which is, I think, one of the superpowers I think people can have with a lot of, with very little effort, is putting content out online, doing what you do right like uh or i used to write i used to do video because when you put out content online and if you're passionate and you know hopefully you know something about it that somebody learns from some of the best people in the world are paying attention right and i've noticed every sort of world leader in technology is always scoring for new ideas, new people.

And so there's been a repeating pattern in my career where I've written something and somebody has was at the right saw it and they were like, hey, this guy is doing something which I'm interested in.

Let's reach out and make something happen.

So one of the things I always tell people to do, especially young people, is write things, put things online.

These days, I would say get a YouTube channel, right?

Like talk about what you're passionate about and somebody will find you.

Like I know Elon, for example, has found amazing hires because he went on a YouTube rabbit hole.

He was like, let's get this guy.

He looks like really smart.

You and I talk about like you follow somebody on Instagram and next thing you know, you're like, hey, come on my show.

And so I think creating, writing what you do is such a great differentiator.

Anyway, so I wrote something, and Mark liked it.

He sent me an email.

We met up.

We built a relationship for many, many years.

That's one.

The second thing was, I started doing my putting my own money, a little bit of my own money, into various companies.

I put some into SpaceX, put some into Alex Banks' company, Scale AI, into a bunch of other companies, which started doing really, really well.

And Silicon Valley is an ecosystem run on reputation.

You know, if you are an investor who puts money into a founder and you are a jerk, you never show up, you never take the next phone call, you're not going to do really well because your reputation will spread.

That founder is going to tell his or her roommate, they're going to tell the next person and

you will not fare very well.

On the other hand,

if you

take the phone call if you wind up helping that person when they need you, if you're just not a jerk, right?

And you respond to every single thing timely,

karma starts accumulating in your favor.

And I just built up this portfolio of a bunch of these investments, which started to do pretty well.

So I'd made a little bit of a name for myself, is what I would say.

And so

I made a little bit of money.

COVID happened.

I was sitting at home, you know, collecting pasta and toilet paper like everyone else was.

You remember that?

You remember the whole era?

Oh, yeah, I still have socks, too.

Oh, my God.

What was your sort of, I can't believe we lived through that memory of COVID.

What's that?

What was your, I can't believe we lived through that memory of COVID.

What is, I can't believe it.

I can't believe it did that.

I can't believe we as a human race or you here, we did that.

Like for me, for example, the fact that we spent months stuck indoors, not seeing other human beings, just bizarre.

I can't believe it did that, right?

What was that for you?

A bunch of stuff.

I remember I fell for it.

I completely fell for it for about a month.

And then, and then I was like, uh,

this doesn't seem right.

But

I remember

spraying packages off at my front door with Lysol.

I remember we, so the multiple uh hand washing you had to do that you made washing

my hands were all cracking.

Here's a funny story for you.

So when we, when we, we moved to Tennessee

and

my wife wanted to start a farm.

So we bought, we went and got like six alpaca,

a bunch of goats, a bunch of chickens, and some ducks.

And did you have any experience in farming?

No, no.

Okay.

No,

we had just started this right before it happened.

And so, do you know what an alpaca is?

Of course.

My mentor in Seattle had an alpaca farm.

It's like a llama, right?

Very docile animals.

Anyways,

it gets hot here, you know, could get to, you know, 100 degrees here.

And so every spring, you're supposed to, you're supposed to shave the alpacas.

And I mean, that's what people raise them for, anyways, the fur, right?

So

we call this guy, or my wife finds this, this alpaca wrangler woman, and

She comes down and she shaves the alpacas.

Remember at the beginning, it was all these people in Italy italy were supposedly dying yes and in the february march of that year yeah that time

and they come down and i'm like hey make sure you wear a mask i don't we don't know where these people have been i go down there

after this is all going on and there's like four people on this alpaca my wife doesn't have a mask on they're shaving this damn thing And these, these two people that came with the, with the, whatever you want to call it, the groomer, whatever,

They go.

I was about to getting fancy.

These are like free-spirited people.

They don't, you know what I mean?

They just travel wherever and do this.

And

two of them were like, yeah, we just got back from this big trip to Italy.

And I grabbed my wife and I'm like, what are you doing?

You're going to fucking kill us.

These people just came from Italy and da da da da da da.

And she's like, holy, she got all upset about it.

And anyways, anyways,

about a couple of days later, you know, because I don't even, I don't watch the news.

I got tired of the news long before

people got tired of the news.

And I was just like, we're just being fed the same bullshit over and over.

Well, then COVID turns up.

I don't have cable TV at the house.

I really, I don't really watch anything.

Smart.

And I just, I don't want to be fed that shit.

You know what I mean?

Because I figured out, you know, I mean, I think everybody's figured it out that they're telling you how to think, what to think.

They're injecting thoughts into your head by that.

And it can manipulate the way you think.

So we got rid of cable a long time ago.

COVID pops up, and I was like, hey, let's just see what's on Air TV.

Only station we got was ABC.

You know, and so I was like, well,

let's just see what's going on in the world.

So we were fed, you know, that garbage for a while.

And then I started talking to some friends that still have news.

And

that's when I, you know, figured it out.

I was like, like, all right,

this isn't about a virus.

This is about something much bigger.

And so, but that was kind of, those were my moments.

Oh, man.

Yeah.

Lasted about a month.

Isn't it crazy that we all lived through that?

We just had our first.

I got to be honest, it's fucking embarrassing.

I mean, we didn't know better.

We were all told this, and nobody had gone through this before.

And

there was so much fear.

And you're like, is it spreading in the air, not spreading in the air like the number of feet uh everyone and we just had our first child like a little bit before that and i we spent so many months just not seeing any human beings yeah that was so bad uh in so many ways and uh

so bad for sort of elderly people i know who are just stuck and um just so it's both funny but also i can't believe we all did that but anyway so so i was sitting at home you know doing this you're not seeing other human beings and everyone was on zoom if you remember this was was the era where everybody was doing video Zoom meetings.

That was the thing.

And Mark Andreessen, you know, he reaches out and he said, what are you up to?

And I had left Twitter because I'd gotten tired and I just want to do something else.

And I was like, well, I'm sitting at home waiting for this pandemic to be over.

I'm sure it'll be over in a few weeks.

Little denominator.

I'm amazing at predictions, Sean.

And he said, well, just come help us out.

And what I did not know was, you know, they'd been talking about me for a while and they had you know somebody else who I think was going to step aside and so I became a part of the team.

I became one of the general partners You know along with Catherine Boyle and she joined after me But there's about I would say maybe 20 general partners for the firm I became one of them and started became a VC started investing while also doing my podcast.

But that's how my Andres and Horowitz journey started.

Wow.

I learned a lot by the way to Andreessen Horowitz about investing.

They

I think I learned a lot about how to be a good investor there, which in a lot of ways, I think, can carry over other things in life.

What is it that you see in a startup company that makes you want to invest?

I mean,

what are some of the points that you look for?

Good question.

At the heart of it, that is the job.

You are here

to figure out who the winners are and put as much money as you can inside them so the first thing is

you probably do not know what to look for until you have met hundreds of companies and founders so for example right like you know if I were to meet somebody from your world from your background right

I don't, without meeting a lot of people, I don't think I would know the difference between a amazing top-tier operator versus somebody who's not, just because I'm just not from that universe.

And I suspect that, you know, if you came into my world, right, you may not know the difference between a top-tier engineer, somebody who's maybe just good at not great.

And the only reason, the only thing that kind of sets that apart is have you put in the time and the effort to meet everybody.

So the first thing, if you want to be an investor, is you just got to talk to everybody.

You got to know, okay, who the great founders look like, who the great engineers look like, who the great great builders, marketers, whoever they may be.

I need to meet everybody.

When you meet people over time,

you build a spidey sense.

Like I'm sure when somebody reaches out to you,

just because of this podcast, you'd now have a little bit more of a spidey sense in terms of how to judge them.

Are they legit?

Are they full of shit?

Or somewhere in between.

And

the first thing is, unless as an investor, you've done your homework and met a lot of people, you will not know the difference between the next Google founder or these guys are just, they have nothing.

You should have done the homework.

That's number one.

The number two,

the belief I learned is that

technology is a sector where often the winners are outsized.

Peter Thiel talks about this.

Peter Thiel has his book called Zero to One, where he basically says that if you go to Palo Alto, right, there are in the Bay Area, there are probably like 20 Indian restaurants, 20 Italian restaurants.

If you invest in one,

there is no way that Italian restaurant is going to become the only Italian restaurant in the United States.

Just not possible.

At best, they maybe have a chain.

You go to a few cities, but that's it.

There is a cap

on how big those Italian restaurants can be.

No harm, no offensive Italian restaurant, but that's just the nature of the business.

Technology businesses are different, right?

If you invest in the right company, they may be the only search engine people use.

They may be the only social media network people use or pick your company.

So there is a huge difference in picking the winner in a category versus not picking the winner in a category.

For example, in 2005, Google dominated the world of search engines.

Who was the number two search engine to Google?

I don't know.

Exactly.

Nobody does.

Doesn't matter.

right like because google just dominated uh same with facebook right like or uh And so there are these winner-take-all patterns which often wind up happening in technology where, you know, have you seen the movie Glengarry Gandros?

No.

Oh, okay.

This is a classic movie.

And there is this classic scene where there's a bunch of sales guys and they're kind of running low on meeting their quotas.

And Alec Baldwin comes in and he's sort of this amazingly famous salesperson.

He gives them a pep talk, right?

And he basically insults them, insults their manlihood.

And he says, you know, the guy who gets, you know, the most sales, the winner gets this amazing car.

You know what second price is after this fancy car?

A set of steak knives.

Nothing, right?

So often in the technology investing world, you know, it's a great scene.

You should check it out on YouTube.

It's a very similar dynamic where if you invest in the winner, right?

Like you're going to be in Google or, you know, Microsoft or Apple or pick your amazing company or you're in a company where you're like, oh, I don't even know who the second guy is, right?

So how do you then figure out what the next goal is going to be?

Well, number one, you have to really, really, really do your homework.

And I think what the firm taught me is that you can get the category wrong of company wrong, but

you can't get the actual winner wrong.

What does it mean, right?

So for example, about like

VR is a good example.

Like Oculus was a big, it was a reasonable winner in VR, but a lot of other VR companies didn't really do do super well.

They might come back now, but people invested money in VR.

And

what some of the partners would say, like, that's fine.

You took a bit on the entire category.

You had the best company in the category.

That's good.

But what is not good is if you're investing in search engines and you did not invest in Google, because that is a difference between

being part of one iconic company.

and not being part of anything at all.

So we often thought a lot about how do we make sure that you're investing in the winner in a category versus somebody else, and you have to wait sometimes until you know who the winner is, right?

You have to be prepared, you have to, you know, you have to know all the founders, you need to be, they need to know you.

So, that was, I think, another big dynamic that they taught me.

The final, and I think the most important part.

I have a question real quick.

You know, when you're talking about trying to find the winner in a category, I mean,

would it not be wise to invest in several companies within the same

question?

Great question.

Let me ask you a simple question.

You had Palmer here, right?

Let's say you invested in Palmer.

Let's say you're also invested in Palmer's competitor.

What do you think?

How do you think it's going to feel?

That's the caveat to that.

Right?

And

so

we had a word called getting conflicted.

Like, I think the great entrepreneurs, right?

you know, don't want you in bed with the competition.

Now, of course, there are a lot of ways to kind of, sometimes people get around it.

You know, some people that I work, you know, in other places, they say, you know what, like we work with everyone equally.

But, you know, one of the prices is if you just back the winners and they don't want you often to work with everyone else.

So that is a definite dynamic.

But to be honest, there's ways around it where some people will say, guess what?

That's just the nature of me.

I just work with everybody.

That's a price.

You have to pay to work with me.

That's all fine.

But that was just the culture I grew up in when I was at Decent Harvard, which is you pick a person and that's the only person you work with.

And I believe a lot in that because I do think a lot of founders value loyalty.

Like they want you to work with them because they are in a knife fight every single day, not metaphorical, not a little one, with their, they're trying to win deals, they are trying to make sure that company is not like crushed or running out of money due to the other person.

They don't want you also helping the other person.

They want to know that you are the, you know, you are loyal to them.

And I I really believe in that loyalty.

I think that matters a lot.

And I also think

people are not loyal.

The great founders don't wind up working with them.

So that's a big dynamic.

But it's a good question.

But that's the answer.

I think the most important part I would say is you need to have a spidey sense for what a great entrepreneur looks like and not look like literally look, but how they operate, what they do.

And I was lucky here because I got to spend time with lots of many amazing entrepreneurs from the, sometimes working with them, like, um, you know, or sometimes from the outside.

And you sometimes see similar patterns across multiple great entrepreneurs.

Like, for example, I'll just pick one.

Every single great entrepreneur

is insanely fast.

You know, they are urgent.

I used to remember, you know, when I've been in teams which are not great, if you wanted to have the next meeting or a conversation about something, they'd be like, yeah, let's go meet in a week or two.

Maybe I put a PowerPoint deck together.

You know, whoever has been in corporate America probably recognizes this.

If you work for a great entrepreneur, they'd be like, well, let's talk in five minutes.

Let's find the answer.

Let's go, go, go.

We don't have time to waste.

They work 24-7.

They eat, sleep, and breathe this.

There is a real sense of urgency, of mission.

And I think that's one of the things that I've learned to pick up on over time.

And it's not the only thing.

I think it's table sticks, right?

It's necessary, but not sufficient, as they would say.

But you build a spidey sense over time.

Interesting.

Interesting.

How long were you there?

Four and a half years until this job.

What are some of your best investments?

Well, I'll pick one and because it ties to the theme of what we talked about in social media.

I just became convinced that centralized social media platforms are not good for all of us.

You know, because if you have the team which doesn't agree with your politics running them, they can just issue orders top on down.

And that's how I really got into crypto.

I became a fan of this idea that crypto is a way to decentralize these platforms.

And instead of having one central company or algorithm which does everything,

you know, you can have people have a say in this, right?

So while personally, I'd invested in companies like SpaceX with Elon or Scale AI with Alex Bank from the firm.

One of my companies I'm really proud of is is a company called Farcaster.

And Farcaster is a decentralized social network.

And I did this like a few years ago.

And it is done by this ex-Coinbase

product builder named Dan Dramoro, who's awesome.

But the idea was that imagine if, you know, with Twitter,

if Twitter was someday, let's say you like Elon, you agree with his politic.

Let's say someday in the future, Twitter is run by somebody who doesn't agree with you, right?

Or says like, I just hate Sean Ryan.

I want to see his account disappear.

Maybe YouTube does that to you.

In Farcaster, they've built a

cryptographic protocol,

sorry, a protocol on, you know, on top of the blockchain where you own your social graph and anybody can build a client on top of Farcaster.

So what does it mean?

Like right now, if Twitter decides to ban you, YouTube decides to ban you, you're told, you're done.

You're toast.

In Farcaster, you're like, you know what?

You can't ban me.

I'm just going to go over using the same client to this other person.

I'm going to take my photograph.

I'm going to take my followers.

I'm going to take my content.

I'm going to go elsewhere.

By the way, the interesting thing is, this is how the internet used to work.

Let me ask you something.

What was your first email?

Don't tell me your first email.

What provider did you sign up for your first ever email address?

Hotmail.

Great.

Okay.

And then you probably switched, right?

You probably went to Gmail, et cetera.

But when you switched, there are a lot of ways to take your email to other places.

You could forward your email to other places.

If you wanted to access your email, you could do it on your phone, right?

You could do it using the official hotmail.com website, or later on, you could use it on the iPhone or on your own desktop client.

So

you signing up with the service was not tied to the actual application you were using with it.

And you're not tied to it.

You could sometimes even take your email address elsewhere.

And your social networks, we've lost that, right?

If you want to use Instagram, if you want to use TikTok, you have to use the official app.

And there's a lot of reasons as to why advertising as a business model.

But what Forecaster is trying to do, and I think others are trying to do in crypto, is let's bring that original internet wipe back where you own your handle.

Like, so for example, I want a world where even if

Neil Mohan, who runs YouTube, gets really pissed off at Sean Ryan, you can take your audience and your subscribers and just go elsewhere.

And they can just follow you elsewhere.

And that's a possibility now it is a possibility now it's early days and and the reason you know i i i and so you had to figure out how to make it happen right technically economically so they built this kind of cryptographic crypto protocol um um which make it happen and they built all these alternate clients it's very early days right but i love the idea because for me that is the spirit of the internet i grew up in like late night because imagine in a world where i was late night in my computer back in chennai like 21 years ago and i was told oh wait before you can write any bit of code code, you need to call up a salesperson in Microsoft before you can write code.

Like I would never had anything.

And so I think this harkens back to an original ethos and spirit of the internet and I think of crypto, which is that you own these things.

You have a say.

You have a stake.

Let me ask you another example, right?

How many subscribers do you have on YouTube right now?

Almost 5 million.

Great.

How much money do you think YouTube makes per year?

How much money do I think YouTube makes a year?

In ad revenue for Google.

Man, I have,

I've never

say it's $5 billion, right?

Again, I don't mean to pick on YouTube.

I think they're amazing, right?

How much of that money do you think you are owed?

Or how do you have even thought of that, right?

And, you know, because you are a stakeholder, you're contributing to this platform.

If you use another social media platform, you are contributing to this platform.

And I think one of the promises of crypto, right,

is that, well, let's give you know everybody it could be somebody with five million subscribers could be even five subscribers a stake in the platform a stake in two ways one financially if you know if youtube instagram tick tock make money you get money second is stake in terms of how you want to experience it if you want to use instead of youtube.com you want to use another app you should be able to go for it if you want to use a different algorithm on the right side or if you want to have use a tick tock with a different algorithm you should be able to go for it right like i want a world for example where one day you open up twitter or uh TikTok and you're like, well, you know what?

I want to pick this algorithm.

I don't want to pick just the algorithm they give me.

Imagine you have like a shopping market of algorithms you could pick from.

Crypto makes all of this possible.

So, anyway, so that is one of the things

I was a very deep believer in.

I was lucky to work with some amazing founders and entrepreneurs, some of the best, deepest relationships.

These are friendships I'll have forever because they took a bet on me as much as I took a bet on them.

And I'm grateful for all of them.

Wow.

Very, what's that?

Forecaster?

Forecaster.

That's interesting.

That's very interesting.

I've not heard of that.

Yeah.

Well, it's early days, but you know, it's one of those things where I think, you know, them or somebody like them, I think it's one thing that just needs to exist.

Yeah, yeah, that sounds genius.

Every day I go to bed, I'm like, oh, this could all end.

Well, you should be like, Neil Mohan is a nice guy, right?

You should be like, you know what?

I put in some work.

I deserve a little bit part of of this.

I have a say in the algorithm.

And right now, I'm sure they listen to you.

You can get a call and they'll probably listen to you, but you don't have an actual say.

And I think that's the promise of crypto.

Yeah.

Wow, that's genius.

I love that.

Yeah.

So let's move into AI.

How did you get picked up for the position?

Man,

senior White House advisor on all things AI.

It is a pure,

I would say, accident in a lot of ways.

So, going back a bit,

I had

a lot of people in DC, you know, have long careers in public service.

They have a lot of aspirations to be here.

I was not one of them.

You know, I was happy, as can be, back in Silicon Valley, back in the technology world, investing.

I was thinking of starting a company.

I was thinking of starting my own firm.

I was just off doing

my thing.

Just because I'm sure a lot of people will agree, DC just felt like this other universe, right?

Like you're like, well, a lot of crazy things happening here, but I'm here doing my thing.

And but what wound up happening is about a year and a half ago, you know,

like everybody, I had gotten really involved in AI, I was investing in AI, but there was this narrative that picked up about AI just killing us all.

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I don't know how much you paid attention to the whole like doomer arguments on AI maybe a year and a half, two ago, but there was a whole school of thought which picked up.

I'm going to say in late 2023, sometime on that frame, which basically said that, oh, we should just stop working on AI

because this is

going to become this superhuman intelligence which just takes over all of humanity.

And I disagree with that, which we can really get into.

The other thing that they started doing was a lot of these folks started influencing government,

influencing the Biden administration, influencing various legislators,

including California.

And what they said was, let's find a way to stop or slow down AI in any number of ways.

And I was paying attention to this, but the one thing which really kind of struck me as very wrong was they tried to ban this thing called open source.

Open source, by the way, just for history, is the software world through the last 30, 40 years has had two camps.

One is closed source, which is somebody like Microsoft Windows, they build it in Redmond, they ship you a product or Apple's OS X operating system, you use it.

The other is open source.

The classic examples would be Linux, which I'm sure you've heard of, or the Android operating system, where there is source code which any of us can go look at, modify, and then contribute back to.

And open source is very important for a couple of reasons.

One is it is kind of part of the spirit of the internet.

It is how people kind of innovate, build on, you get kids, you get academics, you can download the latest and greatest and you can build on it.

It's kind of this spirit of how all these engineering ecosystems at the heart of Silicon Valley.

The second is open source is safer.

There is this great law called Linuses Law, named after Linus Torvals, the founder of Linux.

It says,

with given enough eyes, all bugs are shallow.

It's a different way of saying sunlight is the best disinfect.

And it says, like, if you have the world looking at your code, you can't hide a security vulnerability in there.

We're going to find it, right?

Because one smart person might miss it, but a thousand smart people looking at it, somebody's going to find it.

So what has happened over the last 20 years is if you look at the heart of the things which power your phone, things which power security software, a lot of it is open source, right?

Because people like I trusted it, a lot of its engineers working on it.

It was very important.

And in AI, there was a growing effort to build open source, open weight models.

And again, bear with me because some of these, I think Chat GPT is probably the first time people heard of these model AI models.

AI as a,

and you know, there's been a long history of AI development.

AI started in the, I'm going to say in the 40s.

40s?

Yes.

AI is one of the reasons computation was invented.

There's this guy, Alan Turing.

You know, you might have seen

in the imitation game with Benedict Cumberback.

He invented the Enigma machine, or is a big part of it, which helped the British with the Nazis in terms of ciphers.

He was a mathematical genius in the 40s and 50s, and he invented a lot of modern computation.

He invented two really

important ideas which underpin all of computing.

One is called the Turing machine, which basically says that anything can be a computer if it can decide to between option A, option B, or it can follow an instruction.

It is at the heart of every computer.

But the second, which is even more interesting AI, there's something called the Turing test.

Have you heard of this?

No.

The Turing test is, okay, I'm sitting in front of you.

Imagine there's a door in front of us.

I couldn't see you.

There's another door.

There's one of, behind one door is a human being.

Behind another door is an AI, right?

The Turing test is, can I, as a human human being, tell the difference and know who's the human and who is the AI, right?

And it's kind of, it was always seen as sort of this theoretical, hypothetical test, right?

But the thing about AI development, it started in the 40s and 50s and it has always been, I'm going to call it the holy grail, right?

It has inspired people.

They came into the industry.

For example, in the 60s, There was this guy, you know, John McCarthy, you know, he invented these amazing programming languages called Lisp, all because he wanted to build AI, right?

And in every decade, there were people trying to figure out AI.

And in the 80s and 90s, people started really interesting in the idea of neural networks, okay?

This idea was like, let's figure out how the brain works, okay?

And then let's try and mimic it in a computer, and maybe we get AI, right?

Like for some different definition of AI, right?

Maybe you think Terminator and Skynet.

Maybe you think 2001 is Space Odyssey.

Sorry, Dave, you know, I can't do that.

You know, you think data from Star Trek, whatever it is that's some form of ai now so basically people have been trying for years now the challenge the ai has been over the last 50 years you would see these ups and downs somebody would get really excited about a particular idea right it would show promise for a while people would build phds they would build companies and then one day it'll run out of steam because what would happen is this piece of ai that worked for one idea would not work for another idea maybe you can detect cats but not dogs maybe you can translate English, but not French, right?

It doesn't, it wouldn't scale.

And so all these ideas were happening.

They have this little kind of hill and you know, kind of this momentum and energy and then disillusionment.

And people would leave the industry, companies would go out of business.

And this was happening time and time and time again.

Even in the 2000s, neural networks, which were super interesting and hard.

Every academic was interested in the 80s.

In the 2000s, people are like, I don't know about neural networks.

We've been stuck for 20 years.

We haven't made a breakthrough.

Instead of that, let's figure out alternative mechanisms.

Like the support vectors, the other things that people are doing.

Now, there are two really key moments that happen in AI, which one of the questions I think people should ask is like, why is AI interesting now?

Why not in 2010?

Why was ChatGPT not built in like 2005, right?

Like, why is it being built now?

So I think there's a long history of technical accomplishments happening and the two very important moments.

One was there was something called AlexNet, which was helped built by this guy, Ilya Satskewer, one of the founders of OpenAI in 2012.

But the most important thing I would say, and

this thing should, I think, someday win a Nobel Prize or something, is this paper that came out of Google in 2017.

And the paper is called, Attention is All You Need.

Okay.

I think this is going to be a historic paper.

I think this is going to be as important as Einstein's theory of general relativity.

It is iconic.

And the reason why it is important is that for the first time, you know, we found a mechanism that just continues to scale and work, right?

With neural networks.

Remember what I said?

Until then, there are all these stop and start-stop attempts.

You start somewhere, you chose some promise, you would stop.

With transformers and attention, these bunch of Google engineers figured out this thing, and they didn't know what they had at first.

But it turns out like it just kept going.

And it had this magical property called the scaling loss.

And what that said was that if you give this more data and more GPUs, more computers, it just kept getting better across the board.

And it won't stop.

So far, it has not stopped.

And the reason why this, why is this important?

Every AI algorithm in the past had stopped.

It worked for a while and then it did not scale.

People tried to be smart.

They'd be like, can I detect the human face in a particular way?

Well, yes, but then people have different faces.

Well, you can detect the face, you can detect the bicep, right?

And it just kept failing.

But this algorithm, right, as long as you gave it more data, more to learn from, and then more computers, more data centers, more energy, it just kept getting better.

And so

it was built by Google, but OpenAI, which had been

started by Sam Altman and Elon Musk and a bunch of others,

they kind of ran with it.

And a few years later, came out with ChatGPT, which I think is probably the real moment where people are like oh wow like this is really powerful and so on so just a lot of history in terms of how we got here why are we even here at this moment okay now with chat gpt it's a closed model when you use chat gpt rock anthropic google what does a closed model mean you type in a question uh or maybe you you give it an image you give it a video and it then generates an answer for you.

But you can't really see what it is doing behind the scenes.

You can't run it on your laptop or you can't like run it on your own data center.

It is closed, not open.

But that's perfectly fine because they have a business model.

They spend hundreds of millions and billions of dollars on this.

They want you to pay a subscription fee and use ChatGPT, right?

But a set of companies started building open source models.

And these are models where like you could take ChatGPT or a smaller version of it, but run it on your laptop, right?

You could run it on your phone.

Meta was one.

They had this model called Lama.

Why was this interesting to how I got in here?

Why this whole roundabout thing?

A set of people got really convinced that open source was dangerous.

They were convinced themselves that it is going to help the Chinese, that somehow it is going to make the world unsafe.

And they tried to get California as a state to basically ban.

open source.

So I was sitting here, right, you know, minding my own business, and I was like, man, this is just wrong, right?

Like, because this is the way the internet should work.

This has been the heart of innovation.

this is how you get multiple small entrepreneurs and not just a few big guys not that i have anything against big guys they're awesome but i need multiple entrepreneurs this is just wrong so me as somebody who had no interest in policy i started getting involved in these battles okay so i started joining the right groups i started putting my hand up and uh i was in the united kingdom at the time i was helping andreess and horror grow internationally i had a meeting with the then UK government.

They had a bunch of people.

And they asked me,

hey, they asked the whole group, can we make this open source model public?

This was two and a half years ago.

It was super safe, obviously.

I said, I was the only person in the room who said yes.

And when I said yes, this person next to me looked at me and said, you have just killed all of our children.

I was like, whoa, like,

that's a bit much.

But I remember thinking, wow, these people have infiltrated the highest reaches of government.

And they have sort of scared the world into thinking that this AI is going to take over the world

and

just kind of take over humanity for reasons, by the way, which I can sort of dispute and why I think is untrue.

But that kind of got me personally motivated.

So fast forward, the election happens.

And I was very, you know, I was close to David Sachs, the AI czar.

And I said, listen, I have all these ideas for you because I think this is one of the most existential questions.

The Biden administration has taken so many wrong turns.

They have hurt the American AI ecosystem.

They have cost us to almost lose the race to China

in a bunch of different ways.

And I think there's an existential issue.

And David tells me, well,

come to the White House and help fix it.

And I was like, whoa, like, I didn't know that was an option.

And

for me,

This country has just given me so much.

And I was like, here's a moment in time where I have the chance to give something back.

And I've been incredibly fortunate where, like, imagine you have some skill set in some area, right?

And all of a sudden, you get a chance to help your country with that particular skill set.

I was like, I don't know when this chance will ever come again.

I was convinced the country was going down the wrong direction on AI.

I thought the stakes were incredibly high.

Like, if we get this wrong, which I thought the Biden folks were, we would lose this race to China with catastrophic consequences.

And here I was with this opportunity to, well, step up and try and do something about it.

So

I flew to Mar-a-Lago and I got a call saying, hey, you know what?

You're on the team.

This was, I'm going to say mid, early December, a little bit after the election.

Fast forward a bit more.

The president gets sworn in and a couple of days later, and I suspect this was time, China comes out with this model called DeepSeek.

Have you heard of it?

Oh yeah.

Oh yeah.

So DeepSeek is super important because it is an open source model.

Okay, so first of all, a lot of the people who wanted to stop open source said, well, one of the reasons we want to have open source is because we don't want to help China.

It turns out that the Chinese are actually way ahead.

And they actually had a genuinely a fantastic model that surprised the world.

At the time, it was the only reasoning model, a model which can think and reflect on itself, which was not OpenAI.

It was ahead of so many other models that America had.

It captured everyone's attention.

And I don't want to take any credit away from the team that built DeepSeek.

There was this team of basically hedge fund guys who had, you know, who were very, very good with building on top of GPUs.

And it turns out that a lot of the skills that you need to build great models is programming GPUs very well.

So they built some innovative, cool stuff.

So I always tell people, people, like, DeepSeek has some great ideas that we haven't seen before, but it is, I think, a sputnik moment.

Wow.

Because it showed us that not only are we not like...

Scared everybody.

Yes.

And because not only are we like not like far ahead, we are super close.

And we are on this wrong trajectory where we could just wind up losing.

So we talked about all these companies, Google, Apple, et cetera.

Imagine if in 1998, China built Google, and that's all we use every single day.

China built the iPhone.

That's all we use every single day.

And AI could be a much, much more important technology platform than those things.

And we were off to the races, right?

I remember the very first day coming in.

I hadn't even been sworn in yet.

So they had to give me a badge and do all these things, briefing everybody.

And then the president comes out that evening and he says, like, we need to compete.

We need to unleash American entrepreneurship.

So that was my, I think the day before my first day, the next day I started, and we were off for the races, man.

Well, congratulations.

Thank you.

Late congratulations.

But, you know, you had mentioned, I want to talk about, you know, you were talking about the doomers in AI.

What is, what is, I mean, I know a lot of the concerns, but I want to hear them, you know, what do you think the concerns are?

What is the concept?

So let me sort of try and be intellectually honest and steel, man, what some of the concerns are on AI are.

There are, I think, several classes of concerns.

The first, maybe the most important one, and this is not from the doomers, is AI is going to take my job.

That's important, but that's not what the doomers are talking about.

There is another set of concerns, which is AI

could build maybe

a new kind of biological weapon, a new kind of

nerve toxin.

And those are some very legitimate, serious threats in there.

But the real doomer argument was this idea that

as AI keeps improving, that at some time AI models will start improving themselves.

So instead of a human being being like, all right, I'm going to control this AI.

I'm going to try and make it better every single piece of time.

At some point in time, a model will start to improve itself.

And there's this word in sort of this sort of this AI debate, which is called takeoff or foom, which is kind of the sound of a rocket taking off.

Whereas it is like if you hit that moment of improvement instead of AI just getting becoming better better better better right it just goes

boom

and and so their belief is if that happens what are the results well you might get AI they would say that is not aligned with our hopes and beliefs not because AI is evil like if you see an ant you're not aligned with this interest we just not like we are particularly against ants but we just don't care as much and they worry that AI AIs might think of us as ants.

Maybe there's this famous thing called paperclip maximizing.

Have you heard of this?

No.

Oh, so paperclip maximizing is this idea that the AIs may not want to kill us, but they may not really know what we like.

So they may put us in a job where they say, you know what, make just amazing paperclips.

Because they think humans are happy.

And we are like, no, no, that's not what is the emotion satisfying job.

So it is kind of used as a way to say AIs might become this all-powerful, all-knowing intelligence, which then is going to be smarter than any one human or any one country.

And then just given its knowledge and power,

could just control us and may not have our best interests at heart.

I think I've done a reasonable job of conveying the scenario.

And so

if you believe that, and they had some other concerns, especially the Biden people,

they believe that, well, if you believe this, you need to to make sure that we slow down, we don't get anywhere close, and we need to make sure that only America can build these AI models, no other country.

Because why would you risk some other country having this superhuman intelligence?

They would often compare it to a nuclear weapon, and they would often compare a GPU, a graphics card, one of these thousands of GPUs, which are in a data center or hundreds of thousands.

to plutonium.

They would say, it's like collecting plutonium and

you don't want to have another country, even an allied country, having a nuclear weapon before you.

So they had this thought, I would say, fear of we need to make sure that if we hit AGI, I'm sure you've heard of the word AGI, artificial,

like it needs to be us first, and we kind of scared of it.

They also, and I think, so this was, I would say, some of the school of thought around the doomers.

And I just didn't buy any of it.

And the reason I didn't buy any of it is that we are so many years into these AI models.

And there are absolutely a few things.

There are absolutely no signs of takeoff.

In fact, we're recording this in September 2025.

I would say for the last several months, every model has slightly leapfrogged over another.

And there is no sign that any one model is taking off.

There is no one model take all that.

And in fact, what is happening is these models are increasingly specializing.

You have one company which is building amazing models for code.

You have another company which is building amazing models for maybe friendship, right,

or companionship.

Another company into other models which are great for scientific discovery and thinking.

So instead of having this one model which is becoming the superhuman intelligence and searching ahead, you're having this cluster of models, you know, all sort of giving people great benefit, but not showing any signs of take-offs.

That's number one.

The second reason why I disagree with a lot of the doomers

is that it fundamentally underestimates human ingenuity.

Human beings through history have been able to harness technology, right?

The wheel, fire, right?

Like electricity.

Have you seen these videos of, you know, when people would try and scare people over electricity by, you know, by killing elephants?

Like, you know, there was a whole thing where there was a lot of fear-mongering about certain, like one form of electricity versus another.

So they would do these incredibly barbaric things.

They're like, look, we're going to electrocute this elephant.

This is why electricity is not safe for you.

There was a lot of fear-mongering, right?

And time and time again, human beings found a way to harness technology.

Even with nuclear weapons, right?

Human beings found a way to harness nuclear energy.

And of course, there was a lot of doomer thought against that, which we can get to.

Same with the internet, right?

We've a lot of downside.

we have found a way to harness it.

So I think if you think about AI, it fundamentally underestimates human ingenuity.

Humans are not going to allow one all-powerful model to become superhuman intelligent.

You know what?

Without being like, you know what?

We're going to have a say in this.

We're going to try and stop it way, way before that happens.

They're probably going to have a bunch of other AI models which stop it.

So I think just

fundamentally underestimates humans, all of us.

You know, our human spirit, our our creativity, our ingenuity as individuals and as a race.

That's number two.

The third piece is that, you know, instead of having, you know,

what I think AI has become is we apply, and I want to come back to this later into the jobs question, we absolutely need humans at both ends of the AI model.

We need a human being to give it context and input.

Like I was telling you before I showed up today, I went and asked a model, hey, I'm going on Sean Ryan's show.

I am the White House AI advisor.

What should I talk about?

It's pretty okay, but it didn't know me really well.

It didn't know you pretty well, right?

But if I'd given a lot more input and had worked with it,

it would have done a lot better.

The second thing, which we absolutely need humans for, you know, is on verifying the output, which is when an AI model gives you an answer, be it a diagnosis to a doctor, be it a suggestion to an accountant, or maybe a suggestion to somebody manning a drone, you will absolutely need a human being to check it, to verify it, to specialize in it.

So when I think of AI, I think of like the Iron Man suit.

It amplifies you.

It is a fantastic assistant.

It does not replace you.

So, but anyway, so all of this, I think, I think, disproves the doomers and their version of this takeoff risk.

But along with this, I think the Biden folks made a bunch of key errors.

They felt that one, we have to stop this AGI from happening anywhere else in the world.

Second, they were convinced that there was going to be a shortage of AI chips and GPUs forever, and that China just can't innovate, that they just can't build amazing models or amazing chips.

They were just wrong on all of it.

And

if you think about today,

people can just get AI GPUs from Nvidia, from AMD.

There's a bunch of other companies you can just get them.

There's no more shortages, no no more supply constraints, because the semiconductor industry is very, very good at reacting to shortages and honestly finding a way to make money.

But the second thing is they really underestimated China because since they really believe these AI models can be constructed only by a certain number of people in San Francisco, they did not think that some smart set of people around the world could build a deep seek.

And it totally shocked them, right?

And nobody predicted deep seek.

So as a result of all this, I just think the whole doomer narrative, you know, set the country on a wrong path.

I think almost really hurt us in the race against China.

And a lot of what we have done in this administration is try and undo that.

Interesting.

I mean, a couple of questions going all the way back to different AI-specific models.

You had mentioned one for friendship and companionship.

What is that?

Well, I mean, I would say it's more of a use case.

But I think if you look at Grok, there are all these sort of characters with certain personalities people use,

sometimes not safe for work.

But I think when GPT-5 came out recently, a lot of people were upset because they felt like they had built a friend in the previous model with GPT-4.

It had a certain tone, it had a certain way of speaking to you.

And I do think, you know, and they kind of projected this idea of a relationship.

And sometimes some of these AI companies, what they're doing is they're specializing in tone.

Are we the friendly model?

Or are we going to be just very clinical and cold in how we respond?

So that is one dimension in which you can differentiate.

But a lot of other differences in which you can differentiate are, for example, capabilities.

Coding is by far one of the most lucrative, most interesting capabilities in models right now.

Have you heard of the phrase vibe coding?

No.

Oh, okay.

So

when I wrote code and everyone wrote code, the way you did it is you type in a piece of code, a program, you gave it to the computer, whether it worked or not, and then you took it back and they wrote a more piece of code and that's it, right?

These days, vibe coding is basically this idea, and if you want to learn, say, a new programming language, right, you went and learned how it sounded, how it looked like.

You went to various corners of the internet, you figured out how to use it idiomatically, just like you learn a new language, right?

It's one thing to look at the French dictionary.

it's another thing to be able to speak in French idioms where you know people are like, Oh, I think this person knows French.

And you have the same with programming languages.

But AI models are incredibly good at coding.

There are a couple of reasons for this.

One is that there's a lot of code on the internet, so AI models are just trained on a lot of code.

The second more interesting reason, in my mind, is that coding is a way where the models can actually

get better by just by themselves.

They can basically generate some piece of code and they be like, is it good?

Let me run it.

Oh, it was not good.

Let me make myself better.

So, coding is one of these things where they can just learn much better without having to have human input.

If they wrote a poem, it's much harder

to basically, hey, is this poem better than that poem?

But with code, there is an objective answer.

Now, I'm oversimplifying, but there's a couple of reasons why coding has gotten just

dramatically good on these models.

So, vibe coding is this idea where you ask these models to to essentially generate code for you you can do this right now have you ever written code at all no oh amazing okay let me let me get you into this is one of the most you know you're gonna teach me guns and I'm gonna teach you code right okay let's do this right

one of us is gonna look way more badass than the other but

well but but historically even five years ago I was like well I'm gonna send you a book or I'm gonna send you a YouTube video because somebody would say well let's say Give me an example of something you want to do.

Maybe an do you have do you have an does this show have an app or a website?

You have a website.

We have a website.

But you have an app?

We have no app.

Great.

Let us say you want to build an app for the Sean Ryan show, right?

It notifies you when there's a new episode, collects email addresses, right?

Like, you know,

you can sort of sign up to get early access, all these kind of things that app might do.

Now, we should build that.

Please, you should, right?

Like, you know, or somebody watching should build it and get your attention.

But, you know, now what you can do is, I can teach you to do it right now.

Like, what you would do is you would open up one of these models, you would say, I know nothing about computer science.

I have no background in writing code.

Take this YouTube channel and build me a mobile application on running on my iPhone, run it on my Android, which does all the things I just said.

That's it.

And what it is going to do is it's going to start generating code for you.

It might ask you some questions, like how do you want the screen to look like?

Maybe you say, look, I want the screen to have this color, have this functionality.

It's going to generate that for you.

And then it's going to maybe even run that for you right and without maybe even you individually writing a single line of code yourself you could have today a fully functional mobile app people actually build much more sophisticated experiences and whether you should try this right now or after this you know what like i'm going to show you maybe a demo and you should try this right now and i think This is such a superpower because computers are often sort of this arcane thing where you're like, well, I'm going to go to school.

I have to teach myself this.

But with models, anybody and everybody can just get into it and they can amplify themselves and you can focus on the thing you want to do building a great app for the genre and show so wipe coding is this idea where you know instead of spending a lot of time trying to think of what the right code to do uh you basically tell the model here's the code i'm trying to build and what are the models says you're like all right i'm yes yes yes just keep going keep going keep going and it's sort of a little bit of a tongue-in-cheek idea if the idea is like you don't get perfect code you obviously if you're writing this in production if you're writing this for running in inside of

a bank or a nuclear reactor, you absolutely want to make sure you check it and you know exactly what it is doing.

If you're doing it for fun, it's great, right?

You can explore things, try out a new idea,

maybe build something as a hobby.

So Vibe coding is ideas that you can just sort of go with the model.

So that has fundamentally changed writing code where I don't know the exact stats, but a lot of tech companies,

I would say, like

30, 40, 50% of their code is now written by AI.

Anyway, so my point is to kind of going back a little bit,

AI models, instead of having this one model which takes over everybody and becomes this sort of this gigantic

terminator brain, you now have multiple models which have specialized.

Like I'm the great coder model, or I'm the great, you know, one of the great personality.

And so we see no signs of takeoff happening.

So I think the doomers in my mind have been completely proven wrong.

Is takeoff a, I mean, would you say it's a possibility?

Well, theoretically, absolutely, right?

But for me, you have to come back to science, right?

You have to come back to the scientific method.

So I would say you have to show me proof that it can happen.

And every data point we have now is pointing the opposite direction.

And what we were doing is in fear of, in my mind, this theoretical scenario, which has had no existence proof of, we were basically shooting ourselves in the foot we were trying to stop ai we were trying to ban open source ai we were trying to stop our ai from being used by other countries our allies we were trying to stop our allies from using our gpus and chips because we were worried they would build a gi at the same time china was just surging ahead building these models and building this uh chip capability so If you ask me, like, is it a possibility?

Anything is a theoretical possibility.

But we live in the world of reality where you have to be like, you know what?

Show me the empirical evidence that we have any proof of this happening when I have so much evidence of things in the opposite direction.

One of the things I heard the president say is, I'm not sure you've heard this, he says he hates the word artificial intelligence.

He hates the word AI.

And he's very funny about it.

But I think there's some kind of truth to it.

Because the word AI, I would say, almost oversells the space a little bit because in my mind I just don't think of this as this thing where we are getting to into some sci-fi future I think of it as the next great computer platform this is like the internet right this is you know on this Peter Thiel has says on the scale of this is a nothing burger or this is you know some sentient AI sci-fi race I'm somewhere in the middle and I think I agree with him this is like the internet this is like the mobile phone maybe bigger Is this going to fundamentally shape humanity?

Yes, the internet did.

Mobile phones did.

AI is going to.

But I have not seen the evidence that this is going to be some all-knowing, all-powerful God that takes over all of us.

Makes sense.

Makes sense.

I mean, so,

you know, for the doomers, I mean, I've listened to all these things and all these different theories on what it could do, what it could turn into.

I mean,

what would it take to kill it?

I mean, wouldn't it just take removing the power source?

It's a good question.

Let me ask you, though, what are the theories you have heard?

Everything that you've just said.

Okay.

It's going to take everybody's job.

It's going to turn into the Terminator.

It's going to kill everybody.

It's going to wipe out humanity.

Yeah.

Everything that you had stated above.

Let me ask you, well, let me ask you.

I would say one of the challenges of some of these questions is they are almost a theoretical thought exercise where it is so hard to disprove something which is so theoretical.

Okay.

But let me give you an answer.

Imagine tomorrow there was this idea that, you know what?

Shiram was wrong.

He came on the genre and show, he was wrong.

We are actually seeing signs of these models taking off and maybe wanting to do bad things to human beings.

If that happens tomorrow, what do you think you, me, all of humanity is going to do?

Do you think we're going to sit still?

No.

Yeah.

Do you think you're going to allow that to happen?

Like, do you think, you know, all these other people, companies, engineers, do you think that, well, that's it then for the human race?

Let's pack it up and go on home.

No.

They're going to stop it.

Way, way before it ever becomes a thing.

Like, we talked about social media, right?

Like, you know, social media, you know, today versus 10 years ago is so different.

There's so many checks and balances and laws and regulations.

So this idea that

you go from this sort of what we have today into this all-knowing God without reasonable people, you know, whether it be in government, technologists, just regular human beings, without being like, hey, you know what, let's hold up a second here.

Let's just stop and think about it.

Let's put in some safeguards.

Let's have ways to counter these AI models.

That will definitely happen.

There is no way we just get from here to there without a bunch of things in the middle.

So when sometimes when people say, how do you stop this all-powerful AI, which is taking over a data center?

I'm like, how did it take over the data center?

What are the 25 steps which happened before then?

How did it amass all this power?

I'm pretty sure somebody stopped it when they took over the

second data center.

So that's my first sort of like instinctive reaction to when people post those questions.

The second thing I would say is the best answer against models is other models.

And I think it's very true, by the way, in what I think sometimes the future of cyber warfare might look like, where

the best way to defend against maybe a model which is showing this crazy capability is have another model, you know, which is looking for these capabilities.

So look, I hear the sci-fi.

I grew up on sci-fi.

I grew up on Star Trek.

I grew up on 2001 a Space Odyssey.

I've seen the Terminator movies.

I know all the risks.

I know all the theories.

The thing is, we have no proof, no evidence.

We are anywhere on the track.

Second, we have a lot of evidence.

We are in the opposite direction.

This is is an amazing platform.

There are some questions in terms of how do we benefit humanity, but there are no signs of takeoff and sci-fi behavior yet.

And

most importantly, China is searching ahead.

So if we rest, if we stop ourselves, the other side is not.

I understand that.

Before we move into China, I do want to ask you one question.

I mean, do you have any concern about

people in their relationships with AI?

So we're starting to see people ask very personal questions.

Use AI as a therapist.

Should I get divorced?

How should I discipline my kids?

You know, and they're asking AI very,

very

personal questions.

And the, I don't do this, but, but.

the AI will spit out an answer.

And then

I think that

we've seen manipulation with social media to an extraordinary extent.

And so, you know, I think that the

manipulation through the potential of manipulation through AI could be even bigger than what social media has done.

I mean, do you have any concerns about

absolutely?

I would say this is at the heart.

of why we made that executive order happen.

Exact heart.

Imagine

some

young kid, you know, influence, ask AI a very personal question.

We don't want ideology to influence an answer.

We want the honest truth.

So one of the things executive order does is to basically say,

if your model is not truth-seeking, the government will not work with you.

And I think that I absolutely have

that concern.

There's another very interesting concern, which I think is going to come up more and more, which is the idea of privacy.

So, or confidentiality.

If you go to your doctor, your lawyer, or your priest, what are you promised?

You know that nothing you say can ever kind of get out of that context.

There are laws, there are social conventions where you have attorney-client privilege, right?

Like you have doctor-patient confidentiality, right?

Various religions have this construct where what you say is sacred, except

if you do something like really, really crazy.

Now, with AI, we are starting to see people ask very deep personal questions.

They say, look, here's my medical report.

Like,

what does this mean?

Like, you know,

give me a sense of what my blood test means.

Or

maybe I'm not feeling great about myself.

You know, what should I do?

Or maybe just basic career advice.

I know a lot of people ask AI for career advice.

I would think...

it would be weird for all of those to be public.

Imagine if somebody could say, you know, if you gave a piece of AI your medical history and somebody could just say, you know what, just like I can get access to your emails, I want to get access to every single thing you're asked, a piece of AI.

So I don't know what the right answer is, but I do think the way we work with these AI models is a little different than other pieces of technology.

And I do think we're going to have this.

public conversation about what are the right legal constructs to kind of protect that.

But yes, I absolutely do have concerns about ideology, and that is at the heart of why we did this.

Yeah, I'm not just talking about privacy.

I'm talking about actually, I mean, what if somebody were to, I'm just pulling something out of thin air.

What if somebody were severely depressed, you know, and

they're asking an AI a series of questions that ends up with, you know, should I, should I kill my partner?

Cause they upset me.

Should I kill myself?

And I mean, the AI is going to respond to that.

Oh, yes.

You know, and so that's kind of what I'm getting at: is when I'm talking about manipulating population,

privacy

is another concern.

Yeah, but I wasn't there yet.

But, you know, it has the potential to manipulate entire populations.

Absolutely.

The entire population.

Absolutely.

And there have been these very tragic incidents, I would say, in the last few months where

AI has encouraged people down a very, very bad path, where a regular human being would have been like, hey, man, like, maybe you need to get some help.

Maybe you should have a conversation.

And so, I think one of the things which a lot of the leading model companies are working on is addressing sycophancy.

This idea that you just don't want an AI which just agrees with you, but you want an AI which spots patterns of, you know what, this person may need some help.

Or maybe we need to alert law enforcement and say, like,

there are kind of precedents for this, by the way, in other places.

One of the things I'll say about social media platforms is they just see a lot of very dark things in humanity.

And, you know, people wanting to do things to themselves, people trying to do really terrible, bad things to others.

And they build a lot of systems over time to try and kind of deal with that.

And most social media platforms, if you, I'm not going to say every single time, but they try and like, if you try and do something where you might be harming yourself, or maybe you express a desire to harm someone else, they try and find ways to decrease.

They're not perfect, obviously.

And I think AI companies, this is going to be an existential question for them.

They need to find ways to figure out how to spot it when people are going down dark paths and make sure either they're alerting someone or they're kind of coming out of it or you're just not saying, hey, man, yes, you're absolutely right in everything you believe.

And I think this is going to be a key, key topic for all of AI.

Okay,

let's talk about China.

I mean, that's the big concern.

I mean,

Xi Jinping has said, you know,

the winner of the AI race will dominate the entire world.

I mean,

I have a general idea of how that would happen, but how does, I mean,

how far ahead is China than us?

Well, I think we are ahead right now.

But maybe it's more useful to break down a little bit of a scoreboard.

I would say, let's start with the basics.

What AI needs is, number one, is infrastructure.

Infrastructure in terms of

energy.

Energy

which powers data centers.

Because again, the scaling loss, more energy, you get better models.

You can use more AI.

And there, I think one of the fundamental challenges the United States has had is for many, many years,

our energy usage as a country has been fairly flat.

I think it's improved by a small percentage every single year.

And then all of a sudden, AI shows up.

And you need a lot more energy.

You need a lot more data centers.

And then all of a sudden, you have this spaghetti bowl of issues which suddenly come up.

Like the first one is, you know, where do we get the energy from?

And, you know, and that is where I think the current answer is absolutely natural gas.

That's where I think it's going to power a lot of these

AI along with what the president would call clean, beautiful coal.

But also the future is definitely going to be nuclear.

That's going to be a big part.

On this, I would say China is ahead because

they've just invested in building out their energy grid, building out generation.

They've done a lot of work on nuclear and building out the grid that transmits power.

We, on the other hand, one is we have work to do across all these fronts.

I'll talk about what we are doing as this administration, but one, we need more energy.

Second is

we have all these outdated, broken rules and laws which stop data centers from being constructed just from a lot of I would say completely nonsensical climate concerns.

And we need to get rid of the red tape.

We need to get rid of the red tape and we need to, to, what the president call build, baby, build.

We need to build these data centers, we need to build energy

and we need to also figure out a way to upgrade our energy infrastructure.

And we have this peggy mess of issues.

So this administration,

we did a bunch of things to attack this.

There's an executive order which has come out,

which is tackling nuclear, which is said, I forget the exact number of years, but I think for 30, 40 years, the NRC, the Nuclear Regulatory Commission, hasn't approved a single reactor.

And I think there's a whole future between, I know you had folks from the nuclear industry here with SMRs and so on.

I know it's like a little bit of time away, but I do think we had an executive order which basically says, look, you know, we kind of believe

the nuclear definitely has a strong future in America.

In terms of the present, though, we need energy now.

And this is where

the president set up something called the National Energy Dominance Council, the NEDC, which brings together the Secretary of Energy, the Secretary of the Interior, and

we've been working closely with them, which basically tries to attack all of this.

We basically say, how do we remove the red tape on building data centers, on permitting, on regulation?

What are all the things that we can do to just get more data centers built, more energy going?

So just on the scoreboard front, though, this is one where China is ahead.

And we had obviously done a lot to catch up.

And I think we're going to search ahead.

But for the last four or five years, they've just been on a great trajectory.

And I think we have a lot of great work here to catch up and obviously exceed them.

The second part is chips.

So chips are super interesting.

And we should spend a lot of time.

I see on your shelf, you have Chipwar by

Chris Kelly out there.

On chips, we are ahead.

But maybe not as much as people think.

So

when I talk about chips, there are multiple layers.

But essentially,

for AI right now, the most important ones are the GPUs, which are built by people like Nvidia and AMD.

And then, of course, you have Google, which has built their own hardware in terms of TPUs.

And then Amazon has their own hardware.

But NVIDIA, AMD, all these companies are obviously ridiculously important.

And they are right now really far ahead of what the latest and greatest from China, which have companies like Huawei, which builds a product called the Asense, or other companies called Cambricon have.

Now, why are we ahead?

There's multiple answers, but part of it is because we have access to better technology from TSMC in Taiwan,

which I know you're very, very familiar with.

We have access to much better software, which runs these GPUs,

and we just have like a lead on them.

Now, it turns out, though, on this case, China has done a lot of work on catching up.

And instead of having a multi-year lead, I think our lead is much, much smaller.

And right now, what China has been doing with companies like Huawei and Cambricon is really worth paying attention to.

A few months ago, and this is, I think, a very interesting one to look at, Huawei came out with this product called Cloud Matrix 384.

And it's worth Googling and looking up.

And the reason why this is important is if you think about these data centers, right?

If you take, say, for example, OpenAI or Grog, they have a bunch of NVIDIA GPUs inside them and they have them in these clusters, right?

Like if you have a H100, which is what a lot of people use, you have eight of them clustered together and you have maybe several hundred thousand of them.

Or more recently, NVIDIA has come up with this product called the Blackwells, where you connect 72 of them, but you kind of cluster these.

And the idea is the more of these you bring together, the better it is for training a model or inferencing from a model.

Cloudmatrix 34 is interesting because people believe that China was way behind innovating GPUs.

And what they did was they built a cluster where you take 384 GPUs, ascend Chinese GPUs.

Now each of those use way more power than NVIDIA.

They are not as fast, but it doesn't matter because guess what?

China has more power.

They don't care as much as we do.

Second, Huawei has really good networking technology.

They're a networking company.

So they're able to basically connect, if I'm oversimplifying, a lot of

not as great GPUs, but to try and compete with much more powerful GPUs.

And I think of this as an interesting example, just like DeepSeek, of when we try and say, we are not going to let the world have our technology or let China have our technology, they're often been very good at working around in other very creative ways.

So that's number two.

But I think on the chip side, we still have an advantage in the performance of each GPU and also how many we can make.

For a lot of reasons,

we can just make several million of these.

And China is definitely a lot more hamstrung in how much they can make.

But we are ahead.

Models is very interesting.

On models, if you talk to somebody on January 15th or January 18th, they would say, oh man, American models are way ahead.

We have OpenAI at the time 01.

we have Cloud

3, or we have whatever Grok2, I think at the time.

And China doesn't have anything.

DeepSeek totally, in my mind, demolished that idea because all of a sudden they were not ahead, but they were very close.

And

one of the phenomenons that happened in AI is this idea of distillation, which is you can take a really powerful model and you can distill it to make a smaller, not as powerful model but just slightly close behind tldr what happened is china proved to us that they can build really really good models in some ways surpassing what we have uh i was at a developer event in san francisco recently and i asked the crowd what are you guys how many of you using a chinese model like deep seek quan uh kln there's a bunch of others and almost everybody in the room put up their hands and i was like whoa like this is not good why is this not good right number one it it is soft power right like China having a technology platform which is now running you know inside American infra hopefully not American infrastructure but like American companies definitely not even global companies where instead of our models second these models also communicate culture like think about my story I grew up on the internet I grew up on the English internet I absorbed a lot of American culture just because of the prevalence of,

you know,

America winning the internet.

But if China dominates the model race, like if you look at deep seat, it doesn't really share our ideology.

And we don't want that to be the dominant ideology and values around the world.

You asked about people asking models very personal questions.

Think about a world where people ask a Chinese model very, very personal questions.

I'm not sure I would want that.

So one, on the model side,

I think they've caught up very close behind.

I think they are ahead on open source.

We are catching up quickly.

There's been some great new launches recently.

We are still very much ahead on closed source models.

The latest and greatest, GPT-5,

Gemini, Grok,

we are still ahead, but it is a much closer race.

The last and maybe most interesting part of the race is what I would call diffusion, which is how are people using AI?

Because end of the day, AI needs usage to be better.

One of the reasons ChatGPT became really good is because when people used it, you could use that feedback system and become better.

This is very important, not just for AI today, but important for the future, like robotics.

One of the things which is going to be key to getting robots, American robots all over the world, is can we get that robots like data of usage, either from a simulation or real world, and make it better.

So I think there's a race right now, which is who can get their AI to spread faster, to be used faster.

Okay.

And historically,

when you grew up, did you use Windows laptops or Windows computer when you grew up as a kid?

Do you know who Windows' competitor was in the 90s?

No.

Nobody remembers.

There are companies like IBM's OS2 and others, they all got crushed because Microsoft, Windows, along with Intel, dominated.

Why?

They got everybody to use it first.

And they got all the developers to build applications on it first.

They probably built Office, used Office, games that you used.

Netscape, now everyone used Windows.

So when you get everybody to use your stuff, you get this ecosystem flywheel, right?

More smart people start building on your stuff.

Your stuff gets better.

More applications make your platform better.

And on and on and on, right?

And right now, we have a window of time where we can make American AI the default here around the world.

And if we don't, China will try and make their AI, their chips, their models, you know, future, their robots, the default around the world.

And that for me is the heart of the race.

So if...

With all the concerns and all the different sectors, I mean, it sounds like we're ahead on chips, software, but we're behind on energy.

And energy seems to be, I mean,

with the little I know, you know what I mean?

Energy seems to maybe be the most important factor in AI and data centers and all this other stuff.

And so what are we doing

specifically to unleash, I mean,

I've doven into the power grid, the vulnerabilities.

I mean, it's, it is a, it's atrocious of, of

neglect for our energy system, our power grid, and for, for, for years, maybe, I mean, years and years.

And,

you know, if China's ahead, I mean, what are we going to do to unleash nuclear power?

I mean, it seems like that is, that's the key.

Yeah.

And we have all these innovators that are, you know, we talked to Isaiah Taylor, who's building the mini reactors.

We talked to Scott Nolan, who's, you know,

enriching uranium.

And, and,

but

we need to go faster.

We need to go faster.

And all these guys are very impressed with the current administration and getting rid of some of the red tape, but

I still don't feel like, I mean, if China has zero red tape,

how the hell are we going to compete with our power grid?

I mean, we talked to

Baji Bhatt, you know, the founder of Robin Hood, and

he's...

trying to beam solar energy in from space to receivers that are going to that are that are going to get averted into the grid.

I mean, we've got all these amazing ideas, but it's just not going fast enough.

In my opinion.

Well,

I think I totally agree with you.

Like, this is one of those things where

we just need to move as fast as we can.

So I would think about it in a few layers.

I absolutely think nuclear is the future, but I think we're still a few years away from getting there.

And we have data center needs right now, like today.

Like what is stopping the training of the next large model well we need to have a larger data center and we are seeing entrepreneurs all the time like elon for example um if you see how we built colossus um it's in memphis right and so he builds this old uh he buys his old i think electrolux factory and then he

drives in all these generators on all sides and then uses tesla solar packs to basically even it you know kind of augment it uh write some code to even it all out.

And it's, it just is one of these amazing speeds of engineering.

But the point being, we need energy right now.

So just on the nuclear front, it's absolutely the future.

So administration has an executive order out, which basically, you know, tries to clear the red tape on the permitting for all things nuclear.

But my sense, and I'm not like a deep nuclear person, it's my sense from talking to the best people in this is like, we're still looking out like a few years.

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The game right now is gas and gas turbines.

And the challenge there, well, on the energy production side, then you have on the energy grid side, to your point, we have a very old grid from one in infrastructure capacity.

And second, we have all these local state utilities and monopolies which have weird regulation, which makes it very, very hard to take power from one state to another.

There's a whole cluster there.

So we came out with this document a few weeks ago called the AI Action Plan, which kind of, which is the entire AI strategy for America in my mind.

I spent a lot of time on it.

A lot of others have spent a lot of time on it.

You know, the president announced it.

And in that, one of the top priorities we talk about is one, removing the red tape for data center construction, right?

With things like, how do we make sure there is the NEPA, the National Environment Protection Act, how do we find carve-outs so that we can get data construction just going, right?

Let's just get the red tape out of the way.

Let's go build, build, build.

There are

directives in there on figuring out what to do with our grid capacity, figuring out incentives on energy.

I think the president in his first week announced this large project

called Stargate

in terms of just getting more investment and getting more of these data-centered construction going.

So, in my mind, nuclear is the future.

I think we've done a lot to clear out the red tape, but I have a race to win right now.

Like every entrepreneur is like, look, I need to get 100,000 more, 200,000 more GPUs unlocked.

What do I do?

So we need to unlock that.

And I think unlocking data center construction, grid capacity,

clearing of the red tape so the power can come to the data center.

How do we find smart ways to go do that, really innovative ways to go do that?

That's the game right now which i think you know and i i don't want to take credit for this because i do think the uh department of energy uh and interior have done a lot of great work on this they are very very focused on all centered around gas and coal

moving on to chips i mean you say we're ahead on chips i think it was was it april of

this year we said no no chip sales to china correct from nvidia

was that correct not really in august we said

i believe it was august right it was last month august we said nvidia can sell chips to china but we get 15 of the revenue correct the h20 chips which are the which are the high-end chips correct was that a mistake uh so actually there's a few corrections in there okay a little bit of history uh so nvidia makes a whole set of chips uh they and the latest greatest generation is called the black walls.

They usually start with the letters G and B.

The previous generation was called the hopper.

They started with the letter H.

The top of the line was the H100, which honestly is what a lot of people have right now, or the H200.

They're kind of the top of the line in America.

Now,

about two and a half years ago, the Biden administration came out and said, hey, we're going to Remember what I said, the Biden administration had all these mistaken beliefs.

And one of the beliefs I think they had was that China,

one, our allies can't have our AI chips and that China can't ramp up chip technology.

So because since they believed that, they said, number one, you know, we're going to put limits on the power of the chips, the flops of the chips that China can get.

And then we're going to slice the world into three categories.

This was called the Biden diffusion rule, where some countries like USA, UK, can get any number of GPUs they want.

About 100 countries couldn't really get many GPUs without going through this crazy amount of red tape.

And then some would just not get any GPUs at all, like Iran, North Korea, the countries of concern.

And

as a result,

a couple of things happened.

One was that a lot of our allies were like, well, we want to use American stuff, but you guys won't work with us.

And they were just left out in the cold.

A good example is like the Middle East, where the Middle East and countries like other countries, they were like, we want to bring AI to our citizens.

And

what is a way where we can get your GPUs?

And the Biden diffusion rule said, there is no way you can ever get our GPUs.

That's number one.

So we essentially kind of turned our back on our allies all over the world because we thought, number one, you know, there's a supply constraint in GPUs that if a GPU ever goes out of America, it means

one less GPU for an American company.

We thought China will not compete on chips.

Third, we thought AGI can only happen in America.

It's a scary, scary thing.

So we came in and we were like, this is just wrong, you know,

because number one, we're making a lot of GPUs, right?

Like if you want, you can go get a H100 like right now, an H200 like right now.

Because it turns out that all these semiconductor companies, when they find a supply constraint, they're very, very good at innovating and working on on it.

They're very capitalistic.

They want to make money.

So number one,

if we ship a GPU to somebody else, that doesn't mean one less GPU to America.

Number two, as I said earlier, I don't think we worry about AGI exploding anymore.

We talked about that.

I don't think we worry about takeoff anymore.

I'm not so much worried about an allied country building a super intelligent AI ahead of us.

I just don't think that is a realistic possibility.

So we said, first of all, to our allies, we're going to tear apart this 200-page crazy crazy document called the diffusion rule and the first thing you know of course I want to talk about the Middle East then I want to come to China we President Trump in this first state visit he went to the Middle East and we struck these deals called the AI Acceleration Partnerships and this idea was that we will

sell you these GPUs in return for investment in America and with ironclad security provisions to make sure that those GPUs are going to stay where we ship them.

They're not going to go to some other country and they're going to have somebody we don't like accessing them.

And the idea behind all of this is like, we want our chips, our models to be used the world over.

We want to be like Windows, we want to be Intel, and we don't want to risk competition.

Because in the meantime, what wound up happening is Huawei has been ramping up chip production.

So we now have a competitor who has a good product.

They built Cloud Matrix.

They are building a sense.

There is a story in Bloomberg last week about Huawei exporting chips or trying to export chips to multiple countries around the world.

So if you think of American AI as a product, we have a competitor who's out there selling a competing product out there.

So our stance is that when it comes to our allies, we want them to have American AI, our chips, our models.

in return for

investment in America and with the right security safeguards in place.

I always, always underscore that.

It is in the terms that we signed, for example, a couple of these Middle Eastern countries.

Now,

hopefully that's kind of clear on why we want our allies to have our technology.

China is an interesting different case.

There are two schools of thought on China.

One school of thought is what you said, which is

we should just deny them any chip.

any GPU, right?

And the idea there is that, hey, if we deny them anything,

number one, they're not making their own GPUs, they're not really making their own model.

That was the original thinking.

So we will just make sure we get this race to AGI.

We will be far ahead.

It turns out that was fatally flawed.

Okay.

Because number one, China's making chips, they're innovating.

and they're building great models and they're going you know knocking on other people's doors like hey america is not selling you the biden administration is not giving you any of their uh technology at all maybe you want to work with us okay and so we think the answer is we will always keep the latest and greatest GPUs for the United States in huge quantities.

That is irrevocable.

Like, you know, we will be the only country which can build these massive, massive superclusters of GPUs.

But on the other hand, you know, we want to make sure that we are not giving Huawei, Cambridge Con, all these Chinese competitors oxygen, oxygen of growth, oxygen of revenue and usage, right?

Because when somebody uses a GPU, they're writing code on it, they're finding issues, they're finding bugs, they are making it better.

So what is the answer?

How do we thread this needle between let's keep our big stuff, but let's not give the competition any auction?

And I believe the right answer is let's ship them technology that is ahead of what the competition has, but way behind both in individual performance and also in quantity what we had.

So that's the principle and the framework.

So if you kind of follow that, where does the H20 come in?

The first thing about H20 is because

some of these Biden staffers like to

talk about this is Biden never banned H20s ever.

They were completely allowed all the time through the administration.

Because what happened is when

Biden's team built out these rules, NVIDIA went out.

And by the way, NVIDIA has H20, but AMD has something called the MI308, which is the equivalent of the H20.

They said, okay, both of these companies, we are going to build a Nerfed version of our...

You know what Nerf means in

gaming lingo?

It's a less powerful version of our GPU, which is way behind what the latest and greatest America has.

And we are going to ship this only to China because it will keep us ahead of what Huawei has.

So we can get these Chinese customers using it, but but we are way behind what America has.

Nvidia built this,

AMD built this.

The Biden folks were completely okay with this.

So we came in and the first thing we said is one, we tore upon the diffusion rule for the rest of the world.

When it came to China, we said, okay, we need to know exactly what is going on.

when we ship GPUs to China, right?

So we said, we're going to bring in a licensing regime.

So every time you see a headline that says

President Trump banned H-20s in April, March, Not true.

We brought it under a licensing regime, which basically said, look, if you are going to start to export this, you need to ask us for a license first.

Actually, the technical term is called an ASIN formula.

We sent to these companies.

We need to come ask us for a license first.

So we know how much are we shipping and who's getting it on the other end, right?

And now, as you mentioned a couple of weeks ago,

these are my partners in the commerce department who are actually in charge of the licenses.

They take all the credit for thinking through all this.

You know, them, along with the president, said, okay, you know what?

We're going to get a great deal for the American people.

We're going to start approving some of these licenses of these much older, less performing chips, way behind what America has in way less numbers than what America has.

And we're going to get a great deal for the American people.

So that's the history.

But that's all the past.

I like to think about the future because, you know, every, the H20 is now two and a half years old.

And every company has a new generation roughly every single year.

And one of the amusing things for me is we are still talking about this,

even though since the time the H2D has built, we have been through two iPhone generations.

It's like we're talking about, I don't know what the latest iPhone is, we're talking about like the iPhone 11 and we are, you know, several generations behind.

This conversation is going to keep coming up again and again and again.

So what is the right long-term strategy, right?

In my mind, it is one, we need to flood the zone around the world with our allies, with American technology.

We're starting with American GPUs.

Why?

You know the whole old business model of Gillette, which is you sell them a razor, but you make money on the blades?

You know that?

GPUs and models are a bit similar.

If you are a country and you spend a few billion dollars buying American chips, guess which models you're going to use?

Probably American models.

You're going to make both those models and the chips better on using it.

When you build a next data center, you already have all these innocent American models.

What are you going to do?

Probably buy American all over again.

Now, if we refuse to do business with you, you're probably going to go to a competitor at some point in time because AI is just too important.

We just can't keep telling people to pound sand every single time they knock on the door and say, I want to bring my citizens AI.

So one, we should flood the world, our allies,

with American technology, with GPUs, with models.

Again, America will have an overwhelming lead in the quality and the quantity of these GPUs.

We'll be the only ones who are building, you know, Elon, I think, is going to build a million plus cluster this year.

I think Google has way more TPUs.

We'll be the only country which can build these massive ones.

But if another country is like, hey, I want to bring my citizens education, I'd much rather them doing it on an American GPU, running an American model, generating American tokens.

So that's for our allies, right?

And we can talk about who the allies are.

For China,

our belief is the right strategy is find a way where we keep the latest and greatest, but

ship technology.

So if they want to build a chatbot, if they want to build education, I would much rather have them use a older, nerfed, a lower quantity version of our GPUs rather than buy a Chinese company and then keep improving it.

And because the reason is if we do that, what happens?

Let's say we ban all American technology China.

We say you can't get anything.

Well, they are going to say we need to accelerate all of our indigenous chip making efforts because you guys left us no choice.

This has happened before, by the way, about 10 years ago, right?

Like we stopped exporting supercomputing chips to China.

And within a couple of years, Chinese indigenous supercomputing ecosystem just exploded.

And they have, I think within a few years, like much better supercomputers than the chips we were exporting them to.

So if we force their hand, they're going to now build out an alternative technology stack.

And then they're going to start exporting it.

They are going to go to other countries because we are being difficult to do business with in this Biden scenario.

We're like, you know what?

Buy a Chinese chip,

and it's going to come freely loaded with DeepSeek on top of it.

So that's the scary scenario.

So I think the right answer is we ship China older, smaller quantity chips in enough quantity so that we retain the latest and greatest, we retain these super clusters, but it is enough to make sure the competition there does not get oxygen.

Now, I understand everything you're saying.

You know, I mean, I know you're very aware of

the China-Taiwan conflict.

I mean,

so just the fact that we are sending them

older technology, older chips that aren't up to snuff with what we have, I mean, do you think that's more motivation for them to make a move on Taiwan

over?

I don't want to speculate.

It's hard to say.

Because then they cut us out.

Well,

my belief,

I'm not a deep geopolitical expert on Taiwan.

I'm much more familiar with the semiconductors.

I think the...

the motivation there is more about sort of how they believe history.

But I think it's a good question, which is

other motivating factors, right?

Like, and I'm not the expert, I think some of your, you know, you had a lot of great guests on.

Number one is the Biden rule definitely amplified that.

Like, because if we go tell people, pound sand, you're not getting anything, you sort of have to find ways to find alternatives.

We are relieving the pressure, right?

Like, you know, again, I keep emphasizing it because somebody went somebody, they like, they like, we have the latest and datas, and we are the, we'd be the only country who can build these million GPU clusters that you know any one of these model companies have but at the same time you know i want to make sure that they get enough to uh you know to stop them feeling like oh my gosh we're just going to go full-on out to build out our entire ecosystem and go talk to somebody else so uh does it take away the motivation i don't think so but it's definitely better than the previous alternative you know that we had last year i do think you bring up another interesting question which is the taiwan dsmc question question,

which is that we as a country, I guess the world, essentially has a reliance

on a couple of companies around the world

who are essential.

One is ASML in the Netherlands, who build

these lithography machines.

And the second is obviously DSMC.

And if something happens in Taiwan,

any number of situations could happen, but it probably means, you know, we don't get iPhones, you know, we don't get AI chips.

It's not going to be good.

And I think this is where the TSMC project in Arizona, all of President Trump's efforts to onshore these capabilities, the recent deal that President Trump and the Commerce Secretary did with Intel on this all kind of play a part, which is this is such an important

capability that we as America need to have on our soil.

And we need to find ways to bolster our entire chip manufacturing supply chain and not be so reliant on one single point of failure.

So, when I think about TSMC, I'm thinking about all things Intel, I'm thinking about all things in, you know, how do we get these fab construction in Arizona,

you know, going faster.

How is that factory going?

I mean,

from my interview with Bal Shikim, it sounds like, you know, the VP of Taiwan, I mean, it sounds like that the tariffs may have had some implications on the speed of that.

Well, I think they went a lot faster than the Biden regime, for sure.

But I think we...

There's always space to do more.

I would think that one of the things that we have really tried to emphasize is that we just need to accelerate our indigenous supply chain.

And I don't have the latest numbers on how these fab production is going.

I believe they've kind of increased their capacity in some way than what it was two, three years ago.

But we need to do more.

I believe even if the fabs are at the current rate or full potential,

it's not going to be sufficient to make up for all the things that DSMC winds up making.

So we need other answers.

We'll probably, we're going to need Intel.

We might need like other answers in there.

I think this is going to be one of those interesting questions over the next few years in how do we build out these sovereign chip making capabilities.

So that's for me is one.

But I want to kind of come back to the Chinese Huawei question because I do think it's important.

Like one of the things top of mind for me right now is how do I stop?

How do I make sure that somebody around the world is building an application, they're building a critical piece of infrastructure, they are picking our chips, our models, writing applications on top.

It's creating a smoot, and they're not picking the other team.

Like, that is very much on top of mind for me right now.

I have an idea on how to speed it up.

Please, yes.

Yes.

You know, and you'll have to fact-check me on this

through my other episode with Xiaobi Kim.

But, you know, one of the hurdles I think that frustrates them is, you know, they've bought, they're very concerned, obviously, about China taking them

either by cognitive warfare or actual kinetic warfare.

And they've purchased several planes, jets, military equipment from us, you know, but through our red tape and our bureaucracy, I mean, I can't remember.

I believe it was about, I think it was, somebody's just going to have to fact-check me.

I can't look it up right now, but they bought these weapons like five years ago, you know, and they just got their first F-16, you know, and that's created a lot of frustration over there.

And so if there was a way to, you know, get through the red tape and get

the stuff that they had purchased, you know, from us

in a faster way, I think that would help motivate them to help us build the

chip factories in Arizona.

Okay.

Not super familiar with that.

I need to go back and do some homework on this.

Yeah, yeah.

It's, I mean, I know that uh

they're frustrated about that and rightly so i mean shouldn't have to buy something five years in advance before you get it but i mean so how how far along are we in that facility

um

i wish i knew this off the the top of my head um i believe uh man

I think they had faced a few challenges in the first few years around permitting and workforce.

I believe they've just entered production recently,

but we just need to get a lot more going there.

So it's up and running.

I think so.

Okay.

Okay.

Well, that's good to hear.

Yeah.

That's good.

I think so.

That's great to hear.

But I don't want to get fact-checked on this.

Like, you know,

the way I understand it is that, and I'm going to be spending a lot more time on this because I've been spending time on some of these model questions, is that it was in this really slow phase for a little bit of time because they had a lot of issues with finding the right skill set.

I think at some time they had trouble finding enough electricians and other skilled technical people.

But

I think it's ramped up now.

But I don't have the latest and greatest on exactly where they are right now.

Could you paint a picture of what it looks like not only for the US but for the world if China does win the AI race?

What are we looking at?

Oh man.

Oh man.

Yeah.

Well, AI,

look, there are multiple timelines AI could take.

I think it's pretty obvious that AI is going to have profound impacts on the economy, on productivity,

just making people's jobs better on drug discovery.

Imagine a world where China just dominates drug discovery.

Imagine a world where

every Chinese individual is able to be smarter, more productive, get more done than what we can do.

Imagine Chinese companies being able to build faster,

being able to innovate faster, and that flywheel just picking up momentum.

Imagine a world where our allies are using Chinese technology.

This is actually, this has happened before with 5G.

where a lot of the world wound up running on 5G technology from China and

instead of something from a Western country, and that caused a whole set of issues.

So, imagine a world where AI being so much deeper.

You mentioned it knowing people's personal issues, it knows how your business works, it knows your numbers, it is helping you make critical decisions.

All of this being run on Chinese models and the influence and the power it would have.

So, imagine a world of robots

building inside factories, inside people's homes,

you know, which are all powered by Chinese software and hardware all over the world.

And again, this is for me a nightmare scenario.

We are not going to let this happen.

But that was, I think, in some ways the path we were on.

Yeah, I mean, I talked a lot about this with Alex Wang as well, and he had talked about the number of AIs against number of AIs.

So we would need more, you know, if they have, you know, 100 AIs and we have 200 AIs, then they could dedicate their, you know, allocate, you know, I don't know, 33 AIs to surface warfare vehicle.

And if we have 200, we could put 66 against 33.

I sometimes find those a little too theoretical.

Okay.

I often, when we talk about AI, I often want to ground it in terms of

how does it make the regular person's life better?

And I just think about an individual, you know, you know, who can just do more.

They are smarter.

The Iron Man suit.

They're smarter, they're better informed, they can get more done.

You know, because they're getting more done, they can work more effectively together.

They have an always-on smart colleague in an AI who can, you know, they can ask things to, their companies can innovate faster, build more.

So sometimes I worry that we get lost in a little bit of the theoretical elements of AIs versus AIs.

Maybe that's true.

It's hard for me to tell with high levels of confidence how that plays out.

But I do have a high degree of confidence that AIs will need human beings and need to augment human beings.

And I think about how do we make sure like we are augmenting every single American, we're helping every single American every day with AI in

going to work, you know, with their family,

with their hopes and dreams, much better than the other team are.

And I also don't want that to happen using Chinese technology.

Yeah.

Yeah.

You know,

I never thought about, you know, when we were talking about open source and

with DeepSeek, I mean, if that's the open source model, then the entire world uses that,

maybe except us.

And so they're using a Chinese model.

And so I understand that because

I totally understand that.

What I'm getting at is, I mean, what are we doing about open source to spread?

Is it

unlocked the fact that everybody can use our stuff, but where are we with the open source?

The first thing we did is we basically said, stop scaring people about this is a good thing.

And it's very important.

Like, if you go read the AI action plan that I mentioned, which is the official document, it is literally the first paragraph, which is, we want American open source to win.

And the reason this is important is when the government takes a symbolic tone, it sets a tone for everybody in terms of do we like this or not.

So that's number one.

So companies would talk to us.

We'd have companies who would tell us, hey, you know, I want to build this open source model, but I was, the previous regime, you know, or the, you know, other state legislators, they were scaring us.

They were like, if you guys do this, you'll have all these lawsuits and you'd get sort of business.

Like, what do you guys think?

And our message has been like, we want you to go out there.

We want you to win.

We want you to win on open source across the world.

And if you look at the last four or five months, again, I think China has done a great job.

I think their models are really innovative.

I just want to make sure like, you know, we give them props where it is due.

On the other hand, we now have

our own open source models.

There is OpenAI, for the very first time, launched their first open source model.

It's called GPT-OSS.

It came out three weeks ago.

There are multiple startups.

which are now building open source models.

Again, because when you have the government saying nobody should do this, it's very hard for a startup to go out and raise money.

It's very hard for an academic to work on this.

We have come in and said, no, we need this for America.

But look, I'm not going to

say it's all hunky-dory, right?

That is a place where I think we need to do a lot more.

So the action plan, it has a bunch of initiatives in there on how we are going to work with academia, on making open source more real,

and how we are going to work with industry.

So that's one.

I want to talk about something else here, which is about laws around AI, because it's very related.

So I mentioned when I was talking about open source, this thing called SB 1047.

And this was a legislation from the state of California, which would essentially destroy open source, all of American open source.

What it would say, it's a little bit like

gun liability.

Do you remember when some people said, you know what, if somebody gets shot of the gun, the manufacturer should be liable?

It tried to do the same with open source models where it said,

if somebody does something bad with the model, Mark Zuckerberg or Elon Musk or whoever should be personally, you know, that company should be held liable, which essence would have just destroyed open source because no company can really afford to take that risk.

And the challenge is we now have every single state now wanting to do their own rules around AI, but sometimes around open source.

So the president three weeks ago came out and I think said two important things.

The first thing he said was that AI is a national security issue.

So it is way too important to just like leave everything to the states.

So I don't know about you.

I don't want California setting the tone for how we use AI all over the country.

And

there's a Gavin Newsom joke in there, but I want to go there.

Sorry.

He did veto the last, but I don't want to go there.

But

sorry.

But if you don't want any individual state to set laws for the country, and how can that happen?

Because if you have a really important state make a law, the companies will be like, well, we don't have to abide by those guys.

We don't have to abide by those guys.

Let's just pick the lowest common denominator.

On the other hand, what is China doing?

No red tape.

Go, go, go, go, go.

So President Trump came out and said, listen,

you should listen to the speech.

He's like, this is a national security issue, and we need to make sure that we are doing this at a federal level.

So I think this is connected.

Very related is this idea of copyright,

where,

you know, remember what I said about models?

Models become better when you have more data and you have more infrastructure.

And the Chinese models are training on our data.

But if our American models are stopped from training

on this data, the other models are going to get further ahead.

So I know this is a complicated discussion, but in my mind, I think of the national security dynamic of how do we make sure our guys are allowed to do the exact same things as the competition.

Because if they are training on our data, our guys should also be allowed to train on our data.

Otherwise, we're going to fall behind.

So with open source, I think it's not just encouraging open source.

There is a cluster of issues which are all connected, which I think

for folks watching this, you should read the action plan and you should listen to President Trump's speech when he announced the action plan.

You know, I know you had a very important dinner last night.

In fact, three former guests have been on there.

Jared,

Isaacman, Alex Wang, Sham Sangar.

You were there.

What came out of that dinner?

Well,

I would say, so we had this big event yesterday, which is

we had this whole AI education task force meeting with the First Lady, which I think may be something we should talk about, which the First Lady and the administration, we really cared about how Americans get the skills to work with AI.

So there was a big event.

And as a part of that, there was a dinner with several really, really interesting people.

And I think, you know, the overwhelming tone, if you look at that dinner, which by the way, I was not there.

I was on a flight to get here.

Oh, shit.

Yeah.

By the way, folks, even though I had to cancel on you yesterday because I was like, hey, Sean's team, I'm getting pulled into something.

I'm going to have it move to the next day.

And

then I was like, see, Sean, like, this was why I had to move to the next day.

You know, you can, I'm not just making up an excuse.

I'm not being a jerk.

But if you look at the dinner, the overwhelming message from everybody

was like, we just love what the administration has done in cutting red tape, in being pro-innovation under the leadership of President Trump.

So you kind of see that overwhelming message, but it is fun and entertaining in a way only President Trump can be.

I saw that

I could be off on this.

Did Tim Cook say that he was going to put $600 billion into U.S.

manufacturing?

I think that was Zuckerberg.

Was that Zuckerberg?

I think so.

Okay.

I think there was definitely a big number from Apple, but I'm not sure whether it was yesterday.

I think that was Mark Zuckerberg.

I could be wrong, right?

Like, I was on a very late plane here, so I wasn't watching the videos, but I think that was Zuck

who did that.

But I think you're seeing this across the board.

Look, with President Trump and his administration, there's one very key message, which is

you need to invest and build in America.

Like you see this message through and through and through.

So if you, you know, there are so many examples.

You had TSMC come in and talk about their investments here.

You had Tim Cook go to the Oval and talk about investing here.

Zuckerberg yesterday, multiple, multiple companies basically talking about how they are investing tens of billions of dollars in infrastructure all over America.

And I think this is a key theme, which ties into some of the pieces we talk about.

Like the reason to do this is not just a chip sovereignty, but it's the idea of like we want to bring back investment and jobs and infrastructure in America.

But like there are so many examples from the tech world, not the tech world, of people announcing investments in the U.S.

Yeah, yeah, sounds so good.

I think there's a second comment.

I think after the event, I think the president looked at

Mark and he said, Mark, this is your start of your career in politics.

And Mark was like, I don't know about that.

It was interesting to see Elon didn't have a seat at that table.

I think he said he was.

I don't know.

I think he said he was invited.

I think he sent somebody else.

Don't know.

I wonder why.

But,

well, Sri Ram,

this was a fascinating interview.

And I think, I mean,

I'm excited for you and excited for the country.

And

I love your plan, everything that you just talked about here.

And,

man,

I got to hand it to you.

This is, you're probably, not probably, you are in one of the, if not the most important role in that right now.

I think that this is, this is, this is

a lot more serious of a race than most people even realize with the race with China.

And so I just, I just commend you for rising up and taking the opportunity.

And

we're all rooting for you.

And thank you.

Thank you for having me.

Such an honor.

And look, this is such a privilege.

It's such a dream to just even have this opportunity to be a part of the administration, to work for everyone watching this video.

And for me, I just think every day about

the time I have here, how do I make sure, one, we're winning against China, and two, how do I make sure that AI is working for every single American?

Like, I keep going back to we need to make AI work for every individual.

Like, whether it's to help you, like, I think about my dad, how will he use AI?

And, you know, how will he spend more time with his family?

How will it help him with this job?

And, you know, on all of the current versions of my father.

And I think about both those questions a lot.

And I also want to say, you know, I just want to hear from everybody.

Part of the reason I wanted to do this is because I think it's super important just to be like very, very transparent.

So if folks have thoughts and views, hit me up.

Like, you know, let me know.

I want to, we are open for business.

We want to hear from everybody.

But most of all, thank you.

I've been a fan for a long time.

I've been such an admirer of what you've done.

I can't tell people enough how much being in this room, seeing this story on these walls is a testament to the space you have created.

You've deserved all the success and you're just getting started.

And thank you.

This means a lot for me to be here.

Man, thank you.

That means a lot.

Cheers.

Thank you.