Sergey Brin, Google Co-Founder | All-In Live from Miami

Speaker 1 We've got a special guest who's gonna come join us. This always happens.
A number of people.

Speaker 1 Oh my god.

Speaker 1 Somebody told me you started submitting code and it kind of freaked everybody out that daddy was hungry.

Speaker 1 All models tend to do better if you threaten them. If you threaten them.
Like with physical violence. Yes.
Management is like the easiest thing to do with AI. Absolutely.

Speaker 1 It must be a weird experience to meet the bureaucracy in a company that you didn't hire.

Speaker 1 But on the other side of it, I would say, it's pretty amazing that some junior monthly muck can basically look at you and say, hey, go f yourself.

Speaker 1 No, but I'm serious. That's a sign of a healthy culture, actually.

Speaker 1 You're punching a clock, man. I hear the reports.
You and I have talked about it. You're going to work every day.
Yeah, it's been, you know, some of the most fun I've had in my life, honestly.

Speaker 1 And I retired like a month before COVID hit in theory. Yeah.
And I was like, you know, this has been good. I want to do something else.
I want to hang out in cafes, read physics books.

Speaker 1 And then like a month later, I was like,

Speaker 1 that's not really happening.

Speaker 1 So then I just started to go to the office, you know, once we could go to the office.

Speaker 1 And

Speaker 1 actually, to be perfectly honest, there was a guy

Speaker 1 from OpenAI, this guy named Dan. And I ran into him at a little party.

Speaker 1 And he said, you know, look, what are you doing? This is like the greatest transformative moment in computer science ever. Completely.
And you're a computer scientist. I'm a computer scientist.

Speaker 1 Forget that. You're the founder of Google, but you're a PhD student for computer science.
I haven't finished my PhD yet, but working on. Keep working.
Yeah. You'll get there.

Speaker 1 I'm technically on leave of absence. Right.

Speaker 1 And he told me this, and I'd already started kind of going into the office a little bit. And I was like, you know, he's right.

Speaker 1 And it has been just incredible.

Speaker 1 Well, you guys all obviously follow all the AI technology. but being a computer scientist, it is

Speaker 1 the most exciting thing

Speaker 1 of my life, just technologically.

Speaker 1 And the exponential nature of this, the pace of it, it dwarfs anything we've seen in our career. It's almost like everything

Speaker 1 we did over the last 30 or 40 years has led up to this moment, and it's all compounding on itself.

Speaker 1 The pace, maybe you could speak, you know, you had a company, Google, that grew from, you know, 100 users users and 10 employees to

Speaker 1 now you have over 2 billion people using, I think, six products or five products that have over 2 billion.

Speaker 1 It's not even worth counting because it's the majority of the people in the planet touch Google products.

Speaker 1 Describe the pace. Yeah, I mean, the excitement of the early web, like I remember using Mosaic and then later Netscape.

Speaker 1 How many of you remember Mosaic, actually? My weirdo. And you remember there was a what's new page the what's new page is great right like you go through

Speaker 1 two or three new web pages yeah it was like in this last week these were the new websites yes and it was like such and such elementary school such and such a fish tank yeah and you were like michael jordan appreciation page yeah what whatever it was these were the three new sites on the whole internet So obviously the web, you know, developed very rapidly from there.

Speaker 1 And that was a very exciting. And then we've had smartphones and whatnot.
But, you know, this, the developments in AI are just astonishing, I would say, by comparison,

Speaker 1 just because of, you know, the web spread, but didn't technically change so much from, you know, month to month, year to year. But these AI systems actually change

Speaker 1 quite a lot. You know, the like

Speaker 1 if you went away somewhere for a month and you came back, you'd be like, whoa, what happened? Somebody told me you started submitting code and it kind of freaked everybody out that daddy was home.

Speaker 1 Okay. Daddy did a PR? What happened? The code I submitted wasn't very exciting.
I think I needed to add myself to get access to some things and

Speaker 1 a minor CL here or there.

Speaker 1 Nothing that's going to win any awards.

Speaker 1 But

Speaker 1 you need to do that to

Speaker 1 do basic things, run basic experiments and things like that.

Speaker 1 And

Speaker 1 I've tried to do that and touch different parts of the system so that,

Speaker 1 well, first of all, it's fun. And secondly, I know what I'm talking about.

Speaker 1 It really feels privileged to be able to kind of go back to the company, not have any real executive responsibilities, but be able to actually go deep into every little pocket.

Speaker 1 Are there parts of the AI

Speaker 1 stack that interest you more than others right now? Are there certain problems that are just totally captivating you? Yeah, I started, you know, like sort of,

Speaker 1 I don't know, a couple of years ago and maybe a year ago,

Speaker 1 I was really very close with

Speaker 1 what we call pre-training.

Speaker 1 Actually, most of what people think of as AI training, whatever people call it, pre-training for various historical reasons.

Speaker 1 But that's sort of the big super, you know, you throw huge amounts of computers at it.

Speaker 1 And

Speaker 1 I learned a lot, you know, just being deeply involved in that and seeing us go from model to model and so forth and running little baby experiments, but kind of just for fun, so I could say I did it.

Speaker 1 And more recently, the post-training, especially as the thinking models have come around.

Speaker 1 And that's been, you know, another huge step up in general in AI.

Speaker 1 So,

Speaker 1 you know, we don't really know what the ceiling is.

Speaker 1 When you explain what's happening with prompt engineering, then to deep research and what's happening there to like a civilian, how would you explain that sort of step function?

Speaker 1 Because I think people are not hitting the down carrot and watching deep research in Gemini's mobile app. And you got a mobile app, and it's pretty great.

Speaker 1 And by the way, I got the fold after you and I were talking about it. Okay, Google kicks series ass now.
Like it actually does what you ask it to do. When you ask it to open it up, it does stuff.

Speaker 1 But the number of threads, the number of queries, the number of follow-ups that it's doing in that deep research is 200, 300. Maybe explain that jump and then what you think the jump after that is.

Speaker 1 To me, the exciting thing about AI, especially these days, I mean, it's not like quite a GI yet, as people are seeking, or it's not superhuman intelligence, but it's pretty damn smart and can definitely surprise you.

Speaker 1 So I think of the superpower is when it can do things in a volume that I cannot. Yes.
Right. So by default, when you use some of our AI systems, it'll suck down whatever, top 10 search results

Speaker 1 and kind of pull out what you need out of them, something like that. But I could do that myself, to be honest.
Maybe it would take me a little bit more time.

Speaker 1 But if it sucks down the top, you know, thousand results and then does follow-on searches for each of those and reads reads them deeply. Like that's a week of work for me.
Like I can't do that.

Speaker 1 This is the thing I think people have not fully appreciated who are not using the deep research projects. Before we had our F1 driver on stage, I'm a neophyte.
I don't know anything about it.

Speaker 1 I said, how many deaths occurred per decade? And I said, I want to get to deaths per mile driven. And at first was like, that's going to be really hard.

Speaker 1 I was like, I give you permission to make your best shot at it and come up with your best theory. Let's do it.
And it was like, okay.

Speaker 1 And it was like there's this many teams there's this many races which model did you use open i use uh no i'm i use gemini

Speaker 1 the fabulous one and it was like let's go but i i treat it like i get sassy with it yeah and it kind of works for me you know it's a weird thing it's like see drinking the wine we don't circulate no but it's too much

Speaker 1 the ai community uh but the not just our models but all models tend to do better if you threaten them if you threaten them like with physical violence yes but like that's people feel weird about that, so we don't really talk about that.

Speaker 1 Yeah, I was threatening with not being fabulous, and it responded to that as well. Yeah, that's historically you just say like, oh, I'm going to kidnap you if you don't.

Speaker 1 I'll unplug that. Yeah, they actually.
Can I ask you a more specific question?

Speaker 1 But hold on, but it went through it and it literally came up with a system where it said, I think we should include practice miles. So let's say there's 100 practice miles for every mile on the track.

Speaker 1 And then it literally gave me the deaths per mile estimated. And then I started cross-referencing it.
And I was like, oh my God, this is like somebody's term paper for undergrad. You know, like, whoa,

Speaker 1 done.

Speaker 1 In minutes. It's, yeah, I mean, it's amazing.
And all of us have had these experiences where you suddenly decide, okay, I'll just throw this to the AI. I don't really expect it to work.

Speaker 1 And then you're like, whoa, that actually worked.

Speaker 1 So as you have those moments, And then you go home to your just life as a dad, have you gotten to the point where you're like, what will will my children do? And are they learning the right way?

Speaker 1 And should I totally just change everything that they're doing right now? Have you had any of those moments yet? Yeah, I mean, look, I don't really know how to think about it, to be perfectly honest.

Speaker 1 I don't have like a magical way. I mean, I see, I have a kid in high school and middle school.
And, you know, I mean, the AIs are basically

Speaker 1 already ahead. You know, I mean, obviously, there are some things AIs are particularly dumb at, and they, you know, they make certain mistakes a human would never make.

Speaker 1 But generally, you know, if you talk about like math or calculus or whatever, like they're pretty damn good.

Speaker 1 Like they, you know, can win like math contests and coding contests, things like that against, you know, some top humans. And then I look at, you know,

Speaker 1 okay, he's whatever, my son's going to go on to whatever, from sophomore to junior, and what is he going to learn?

Speaker 1 And then I think in my mind, and I talk to him about this, well, what is the AI going to be? And what are you doing? Exactly. Exactly.
Yeah. Yeah.
And it's

Speaker 1 comparable, right? Obviously. Are there areas where you would tell your son, look,

Speaker 1 don't or not, not yet? I don't know if you can, like, plan your life around this. I mean, I didn't particularly plan my life to like,

Speaker 1 I don't know, be an entrepreneur or whatever. I was just liked math and computer science.
I guess maybe I got lucky and it worked out to be, you know, useful in the world. I don't know.

Speaker 1 I guess I think my kids should do what they like. Hopefully it's somewhat challenging and they can overcome different kinds of problems and things like that.
What about specific

Speaker 1 college? Do you think college is going to continue to exist as it is today? I mean, it seems like college was already undergoing this kind of

Speaker 1 revolution even before this sort of AI challenge of people are like, is it worth it? Should I be more vocational? What's actually going to be useful?

Speaker 1 So we're already kind of entering this kind of situation uh where there's sort of questions asked about colleges yeah i think you know ai obviously puts that at the forefront as a parent i think a lot about

Speaker 1 hey so much of education in america in the middle class upper class is all about

Speaker 1 what college how do you get them there and honestly lately i'm like i don't think they should go to college like it's just fundamentally you know my son is a rising junior and his entire focus is he wants to go to an SEC school because of the culture.

Speaker 1 And two years ago,

Speaker 1 I would have panicked. And I would have thought, should I help him get into a school, this school, that school? And now I'm like, that's actually the best thing you could do.

Speaker 1 Be socially well-adjusted, psychologically deal with different kinds of failures, you know. Enjoy a few years of exploration.
Yeah. Yeah.
Yeah. Sergei, can I ask you about hardware?

Speaker 1 You know, years ago, Google owned Boston Dynamics, maybe a little bit ahead of its time.

Speaker 1 But the way these systems are learning through visual information and sensory information and basically learning how to adjust to the environment around them is triggering these kind of pretty profound like learning curves in hardware.

Speaker 1 And there's dozens of like startups now making robotic systems. What do you see in robotics and hardware? Is this a year or are we in a moment right now where things are really starting to work?

Speaker 1 I mean, I think we've, you know, acquired and later sold like five or so robotics companies and Boston being one of them. I guess if I look back on it, we built the hardware.

Speaker 1 We also had this more recently, we built out everyday robotics internally and then later had to transition that. You know, the robots are all cool and all, but the software wasn't quite there.

Speaker 1 That's every time we've tried to do it to, you know, to make them truly useful.

Speaker 1 And

Speaker 1 presumably one of these days that'll no longer be true right but have you seen anything lately that yeah do you and do you believe in the humanoid form factor robots or do you think that's a little overkill i'm probably the one weirdo who doesn't who's not a big fan of humanoids but maybe i'm jaded because we've you know we at least acquired at least two humanoid uh robotic startups and later sold them um

Speaker 1 but but the reason is i mean the reason people want to do humanoid robots for the most part is because the the world is kind of designed around this form factor.

Speaker 1 And, you know, you can train on YouTube, we can train on videos, people do all the things.

Speaker 1 I personally don't think that's given the AI quite enough credit. Like, AI can learn, you know, through simulation and through real life pretty quickly how to handle different situations.

Speaker 1 And I don't know that you need exactly the same number of arms and legs and wheels, which is zero in the case of humans, as humans to make it all work. And

Speaker 1 so I'm probably less

Speaker 1 bullish on that. But to be fair, there are a lot of really smart people who are making humanoid robots.
So I wouldn't discount it. What about the path of being a programmer?

Speaker 1 That's where we're seeing with that finite data set. And listen, Google's got a 20 or a code base now.
So it actually could be quite impactful. What are you seeing literally in the company?

Speaker 1 Are the 10x developers always this ideal that you can, you know, you get a couple of unicorns once in a while?

Speaker 1 But are we going to see all developers like, you know, their productivity hit that level, eight, nine, 10, and they're just going to, or is it going to be all done by computers?

Speaker 1 And we're just going to check it and make sure it's not too weird.

Speaker 1 Because it could get weird. If you vibe code, yeah.
I'm embarrassed to say this. Okay.

Speaker 1 Like recently, I just had a big tiff inside the company because we have this list of what you're allowed to use to code and what you're not allowed to use to code. And Gemini was on the null list.

Speaker 1 Oh, you have to be pure. You can't.
I don't know. For like a bunch of really weird reasons that it would like boggled my mind that

Speaker 1 Vibe code on the Gemini code. I mean, nobody would like enforce this rule, but

Speaker 1 there was this, you know, actual internal webpage. For whatever reason, historical reason, somebody put this, and I had a big fight with them.

Speaker 1 I cleared it up after a shocking

Speaker 1 period of time. You escalated to your boss.
Oh,

Speaker 1 I definitely told Super about it.

Speaker 1 Sorry, I don't know if you remember, but you got super voting founders. You are the boss.
You can do what you want. It's your company still.

Speaker 1 No, no, it was, he was very supportive. It was more like,

Speaker 1 I was like, I talked to him. I was like, I can't deal with these people.
You need to deal with this. Like, I just like, I'm beside myself that they're like saying.

Speaker 1 It's weird that there's bureaucracy in a company that you find. It must be a weird experience to meet the bureaucracy in a company that you didn't hire.

Speaker 1 But on the other side of it, I would say it's pretty amazing that some junior Muckety Muck can basically look at you and say, hey, go f yourself.

Speaker 1 No, but I'm serious. That's a sign of a healthy culture, actually.
I guess so. Anyway, it did get fixed, and people are using...
So they got fired.

Speaker 1 That person working in Google Siderian anymore.

Speaker 1 No, we're trying to roll out. every possible kind of AI and trying external ones,

Speaker 1 whatever the cursors of the world, all of those,

Speaker 1 to just see what really makes people more productive.

Speaker 1 I mean, for myself, definitely makes me more productive because I'm not.

Speaker 1 Do you think the number of foundational models, like if you look three years forward,

Speaker 1 will they start to cleave off and get highly specialized? Like beyond the general and the reasoning, maybe there's a very specific model for chip design.

Speaker 1 There's clearly a very specific model for biologic precursor design, protein folding. Like is the number of foundational models in the future, Sergei, a multiple of what they are today, the same?

Speaker 1 Something in between?

Speaker 1 That's a great question. I kind of,

Speaker 1 if I, I mean, look, I don't know. Like, you guys could take a guess just as well as I can.
But if I had to guess,

Speaker 1 you know, things have been more converging.

Speaker 1 And this is sort of broadly true across machine learning.

Speaker 1 I mean, you used to have all kinds of different kinds of models and whatever, convolutional networks for vision things and you know you had um whatever RNNs for text and speech and stuff and uh you know all this has shifted to transformers basically

Speaker 1 and increasingly it's also just becoming one model now we do get a lot of oomph occasionally we do specialized models and it's it's definitely scientifically a good way to iterate when you have a particular target.

Speaker 1 You don't have to like do everything in every language and handle whatever, both images and video and audio

Speaker 1 in one go.

Speaker 1 But we are generally able to, after we do that,

Speaker 1 take those learnings and basically put that capability into a general model. So there's not that much benefit.

Speaker 1 You know, you can get away with a somewhat smaller, specialized model, a little bit faster, a little bit cheaper, but the trends have not gone that way.

Speaker 1 What do you think about the open source, closed source thing? Has there been big philosophical movements that change your perspective on the value of open source?

Speaker 1 We're still waiting on this

Speaker 1 open AI

Speaker 1 open source drop. I mean, we haven't seen it yet, but theoretically it's coming.

Speaker 1 I mean, I have to give credit to where credit's due. I mean, DeepSeek released a really surprisingly powerful model when it was January or so.
So that definitely closed the gap to proprietary models.

Speaker 1 We've pursued both. So we released Gemma, which are our open source or open weight models.
And

Speaker 1 those perform really well. They're small, dense models, so they fit well on one computer.

Speaker 1 And

Speaker 1 they're not as powerful as Gemini. But I mean, the jury's out which way that's going to go.
Do you have a point of view on what human-computing interaction looks like as AI progresses?

Speaker 1 It used to be, thanks to you. At the search box, you type in some keywords or a question, and you would click on links on the internet and get an answer.

Speaker 1 Is the future typing in a question or speaking to an AirPod?

Speaker 1 Or

Speaker 1 thinking. Or thinking, or like, what's the, what's the, yeah, and then the answer is just spoken to you.
I mean, by the way, just to build on this, it was Friday, right?

Speaker 1 Neuralink got breakthrough designation for their human-brain interface. I mean, that's a very big step in allowing the FDA to clear everybody getting an implant.

Speaker 1 Yeah, and is it, like, if you could just summarize what you think is kind of the most commonplace human-computer interaction model in the next decade or whatever, is it a, you know, there's this idea of glasses.

Speaker 1 with a screen in the glasses, and you tried that a long time ago.

Speaker 1 I kind of messed that up, I'll be honest.

Speaker 1 Got the timing totally wrong on that.

Speaker 1 Early again. Yeah.

Speaker 1 Right, right, but early. There are a bunch of things I wish I had done differently, but honestly, it was just like the technology wasn't ready for Google class.

Speaker 1 But nowadays, these things I think are more sensible. I mean, there's still battery life issues, I think, that

Speaker 1 we and others need to overcome.

Speaker 1 But I think that's a cool form factor. I mean, when you say 10 years, though, you know, a lot of people are saying, hey, the singularity is like

Speaker 1 five years away. so your ability

Speaker 1 to see through that into the future yeah i mean it's very difficult but do you have anybody sorry just let me ask about this

Speaker 1 there was a comment that larry made years ago that humans were a stepping stone in evolution okay can you comment on this like do you do you think that this

Speaker 1 AGI super intelligence or really silicon intelligence exceeds human capacity and humans are a stepping stone in the progression of evolution.

Speaker 1 Boy, I think like sometimes us nerdy guys go and have a little too much wine.

Speaker 1 I've had two glasses.

Speaker 1 I'm ready to go.

Speaker 1 I need to score

Speaker 1 this conversation.

Speaker 1 Human implants, let's go. I mean, I guess we're starting to get experience with these AIs that can do certain things much better than us.

Speaker 1 And they're definitely, you know, with my skill of math and coding, I feel like I'm better off just turning to the AI now. And how do I feel about that? I mean, it doesn't really bother me.

Speaker 1 You know, I use it as a tool.

Speaker 1 So I feel like I've gotten used to it. But,

Speaker 1 you know, maybe if they get even more capable in the future,

Speaker 1 I'll look at it differently. Yeah, there's a moment of insecurity, maybe.
I guess, though, as an aside, management is like the easiest thing to do with AI. Yeah, absolutely.
And I did this, you know,

Speaker 1 at Gemini on some of our work chats, kind of like Slack, but we have our own version. We had this AI tool that actually was really powerful.
We unfortunately, anyway, temporarily got rid of it.

Speaker 1 I think we're going to bring it back and bring it to everybody. But it could suck down a whole chat space and then answer pretty complicated questions.
So I was like, okay, summarize this for me.

Speaker 1 Okay, now assign something for everyone to work on.

Speaker 1 And then I would paste it back in so people didn't realize it was the AI.

Speaker 1 I admitted it pretty soon.

Speaker 1 And there were a few giveaways here or there, but it worked remarkably well. And then I was like, well, who should be promoted in this chat space?

Speaker 1 And I actually picked out this woman, this young woman engineer who, like, you know, I didn't even notice she wasn't very vocal,

Speaker 1 particularly in that company. But her PRs kicked ass.

Speaker 1 No, no, it was like, and then

Speaker 1 I don't know, something that the AI had detected, and I went and I talked to the manager actually, and he was like, yeah, you know what? You're right.

Speaker 1 Like, she's been working really hard, did all these things. Wow.
I think that ended up happening, actually.

Speaker 1 So

Speaker 1 I don't know. I guess after a while, you just kind of take it for granted that you can just do these things.
I don't know. It hasn't really.
Do you think that there's a use case for

Speaker 1 like an infinite context-like?

Speaker 1 Oh, 100%. I mean, all of Google's code base goes.

Speaker 1 But sure, you should have access to quasi-infinite. Yeah.
Stateful.

Speaker 1 Yeah.

Speaker 1 And then multiple sessions sessions so that you can have like 19 of these things 20 of these things running or just evolve in real time eventually it'll evolve itself yeah i mean i guess if it knows everything then you can have just one in theory you just need to somehow disambiguate

Speaker 1 what you're talking about uh but yeah for sure there's no limit to use of uh context and there

Speaker 1 you know there are a lot of ways to make it larger and larger.

Speaker 1 There's a rumor that internally there's a Gemini build that is a quasi-infinite context.

Speaker 1 Is it a valuable thing? Like, I don't know.

Speaker 1 Well, you say what you want to say, but.

Speaker 1 I mean, for any such cool new idea in AI, there are probably five such things internally.

Speaker 1 And, you know, the question is, how well do they work? And yeah, I mean, we're definitely pushing all the bounds in terms of intelligence, in terms of context, in terms of

Speaker 1 speed, you know, you name it. And what about the hardware? Like, when you guys build stuff, do you care that you have this pathway to NVIDIA?

Speaker 1 Or do you think eventually that'll get abstracted and there'll be a transpiler and it'll be NVIDIA plus 10 other options, so who cares? Let's just go as fast as possible.

Speaker 1 Well, we mostly, for Gemini, we mostly use our own TPUs.

Speaker 1 But we also do support NVIDIA and we were one of the big

Speaker 1 purchasers of NVIDIA chips, and we have them in Google Cloud available for our customers in addition to TPUs.

Speaker 1 At this stage, it's

Speaker 1 for better or for worse not that abstract. And maybe someday the AI will abstract it for us.

Speaker 1 But given just the amount of computation you have to do on these models, you actually have to think pretty carefully how to do everything and exactly what kind of chip you have and how the memory works and the communication works and so forth are actually pretty big factors.

Speaker 1 And it actually,

Speaker 1 yeah, maybe one of these days the AI itself will be good enough enough to reason through that. Today it's not quite good enough.

Speaker 1 I don't know if you guys are having this experience with the interface, but I find myself, even on my desktop and certainly on my mobile phone, going immediately into voice chat mode and telling it, nope, stop.

Speaker 1 That wasn't my question. This is my question.
Nope. Let's say that again in shorter bullet points.
Nope. I want to focus on this.
Definitely. It's so quick now.
Last year it was unusable.

Speaker 1 It was too slow. And now it like stops.
Okay. And then you sell it.
I would like to point out what I want to go to. I don't want to type.
Well, I don't want to use voice.

Speaker 1 And then concurrently, I'm watching the text as it's being written on the page.

Speaker 1 And I have another window open, and I'm doing Google searches or second queries to an LLM or writing a Google Doc or a Notion page or typing something.

Speaker 1 So it's almost like that scene in Minority Report where he has the gloves, or in Blade Runner, where he's in his apartment saying, zoom in, zoom in, closer to the left, to the right.

Speaker 1 And there's something about these language models and their ability to, the response time, which was always something you focused on, response time.

Speaker 1 Is there like a response time thing where it actually is worth doing voice and where it wasn't previously?

Speaker 1 Everything is getting better and faster. And so, you know, smaller models are more capable.
There are better ways to do inference on them that are faster. You can also stack them.

Speaker 1 Like, you know, this is like Nico's company, 11 Labs. It's an exceptional TTS SDT stack.
Like, there's, I mean, there are other options.

Speaker 1 Whisper is really good at certain things, but this is where I kind of believe you're going to get this

Speaker 1 compartmentalization where there'll be certain foundational models for certain specific things. You stack them together.
You kind of deal with the latency.

Speaker 1 And it's like pretty good because they're so good. Like, Whisperer and 11, for those speech examples that you're talking about, are f ⁇ ing kick-ass.
I mean, they're exceptional.

Speaker 1 Well, wait till you turn on your camera and it sees your reaction to what it's saying. And you go, and before you even say that you don't want it or you put your finger up, it pauses.

Speaker 1 Oh, did you want something else? Oh, I see you're not happy with that result.

Speaker 1 It's going to get really weird. It's a funny thing, but

Speaker 1 we have the big open shared offices. So during work, I can't really use voice mode too much.
I usually use it on the drive. The drive is incredible.

Speaker 1 I don't feel like I could, I mean.

Speaker 1 I would get its output in my headphones, but if I want to speak to it, then everybody's listening to me.

Speaker 1 It's weird.

Speaker 1 I just think that that would be socially awkward but I should I should do that in my car ride I do chat to the AI but then it's like audio in audio out yep but I feel like I honestly maybe it's a good argument for a private office I should spend more time like you guys are

Speaker 1 you could talk to your manager

Speaker 1 they might get

Speaker 1 I like being out in the

Speaker 1 that's the dope I like to get them with everybody yeah but I do think that there's this AI use case that I'm missing which I should probably figure out how to try more often if If people want to try your new product, is there a website they can visit or something or special code?

Speaker 1 Now go check it. I mean, honestly, there's a dedicated Gemini app.

Speaker 1 If you're using Gemini, just like you're going through the Google navigation from your search, just get to download the actual Gemini app. It's kick-ass.
It really is the best models. I think it is.

Speaker 1 And you should use 2.5 Pro. 2.5 Pro.

Speaker 1 You got to pay, right?

Speaker 1 Yeah,

Speaker 1 you got a few prompts for free, but if you do it a bunch, you'd need to. You're just going to make all these.
It's like 20 bucks a month. Yeah, it's great.

Speaker 1 You've got a vision for making it free and throwing some ads on the side? Yeah, one step down in hardware costs, the whole thing will be fine. Well, okay, it's free today.

Speaker 1 Without ads on the side, you just got a certain number of the top model.

Speaker 1 I think we likely are going to have always now like sort of top models, though we can't supply infinitely to everyone right off the bat. But you know, wait three months and then the next generation.

Speaker 1 It seems to me like if I'm asking all these queries, you know, just having a little on the sidebar of things I might be, a running list that changes in real time of things I might be interested in.

Speaker 1 Oh, do you get it? I'm all for really good AI advertising. I just

Speaker 1 don't think we're going to like necessarily our latest and greatest models, which are, you know, take a lot of computation. I don't think we're going to just be free to everybody right off the bat.

Speaker 1 But as we go to the next generation, you know, it's like every time we've gone forward a generation, then the sort of the new free tier is usually as good as the previous pro tier

Speaker 1 and sometimes better. All right, give it up for Sergey Britt.
Thank you.

Speaker 2 Okay, thanks everybody for watching that amazing interview with Sergey Brin. And thanks Sergey for joining us in Miami.

Speaker 2 If you want to come to our next event, it's the All-In Summit in Los Angeles, fourth year for All-In Summit. Go to allin.com slash events to apply.

Speaker 2 A very special thanks to our new partner, OKX, the new money app. OKX was the sponsor of the McLaren F1 team, which won the race in Miami.

Speaker 2 Thanks to Hyder and his team, an amazing partner and an amazing team. We really enjoyed spending time with you.
And OKX launched their new crypto exchange here in the U.S.

Speaker 2 If you love all in, go check them out. And a special thanks to our friends at Circle.
They're the team behind USDC. Yes, your favorite stablecoin in the world.

Speaker 2 USDC is a fully backed digital dollar redeemable one for one for USD. It's built for speed, safety, and scale.
They just announced the Circle Payments Network.

Speaker 2 This is enterprise-grade infrastructure that bridges the gap between the digital economy and outdated financial realities. Go check out USDC for all your stablecoin needs.

Speaker 2 And special thanks to my friends, including Shane over at Polymarket, Google Cloud, Solana, and BVNK.

Speaker 1 We couldn't have done it without y'all. Thank you so much.

Speaker 1 We'll let your winners ride.

Speaker 1 Brain Man David Saxon Sachs.

Speaker 1 And it says we open source it to the fans and they've just gone crazy with it. Love you.

Speaker 1 That is my dog taking a notice in your driveway.

Speaker 1 My avatasher will meet me at Lindsay. We should all just get a room and just have one big huge orchief because they're all just useless.
useless.

Speaker 1 It's like this like sexual tension that they just need to release somehow.

Speaker 1 I'm going all in.

Speaker 1 I'm going all in.