AI vs Human: The $1M March Madness Showdown | Alan Levy DSH #1246

Speaker 1 One in billions, right? Yeah, so I say that the most naive statement that I hear human beings make, the most naive, is AI will never be able to, followed by insert whatever the person says.

Speaker 1 Replace their job or whatever. Correct.
AI will at some point in time be able to do everything better.

Speaker 1 All right, guys, got Alan Levy here from 4C Predictions and got a big company in the making here. Thanks for coming on, man.
Thanks. I really appreciate you having me.

Speaker 1 As I said, I've been watching your content. Really awesome, and I'm excited to be here.
Yeah, it's not your first rodeo, right? You've built quite a few companies.

Speaker 1 Yeah, I started kind of straight out of school. And the first company I built was a meat pie company.
Meat pie. Yeah.
So I'm from South Africa. That's the strange accent.

Speaker 1 And we built a company. It was very similar to Mrs.
Field's Cookies, but instead of selling cookies, we sold meat pies.

Speaker 1 And we ended up being the ninth largest franchising company in Africa. Wow.
Yeah. And selling 8 million meat pies to a lot of hungry South Africans every month.
That's insane.

Speaker 1 And that was your first company you ever started? It was my first company. Literally started kind of with one shop and built it up and

Speaker 1 taught me some amazing lessons about business.

Speaker 1 The best one being, I think, deliver extraordinary value to your customers.

Speaker 1 And the second best one being no physical products. So

Speaker 1 margins are low, right? Margins are low. It's difficult to move around.

Speaker 1 You have to transport food in refrigerated containers, moving them around. Africa comes with its own set of interesting problems.
But

Speaker 1 digital stuff's much better. Yeah.
So you started a digital company after that one? I started a digital company.

Speaker 1 We were providing leads for forex and casinos and then got into the online casino business because we were bringing

Speaker 1 regulated casinos under United Kingdom Gaming Commission. And we were bringing them players.

Speaker 1 And then like good entrepreneurs, we thought, wow, why don't we just open our own casino? In those days,

Speaker 1 all gaming in the US was illegal. Like there wasn't betting in the US.
So everyone was doing it in Europe. And now I see America is opening up a lot.

Speaker 1 Yeah, that was before the DraftKings and FanDuel days, right? Correct.

Speaker 1 I heard the craziest stat literally before I walked into this interview that Americans bet more on sports than they have in their 401ks.

Speaker 1 Blew my mind. Wow.
I could see that, though, 100%.

Speaker 1 People are trying to make a quick buck, and sports are a very emotional thing, and they're also huge in the U.S. Exactly.
I haven't verified that.

Speaker 1 It'll be interesting to see if anyone wants to go look at that, but that blew my mind. I was like, even to put it in the same category is mind-blowing.
Yeah. No, I can see it, man.

Speaker 1 NFL is big out here. NBA, NLB, NHL.
We got a lot of big American sports. Yeah, it's crazy.

Speaker 1 And in the rest of the world, we play soccer. I played soccer at school, and then I came to America, and everyone says it's a girl sport.
Yeah, people, soccer players don't get respect in America.

Speaker 1 But in Europe, you're like the man. Exactly.

Speaker 1 They call it football there, but you play football. You're like a legend.
Yeah,

Speaker 1 so it was really fun. So everyone kind of grew up with that.
And when I moved to America,

Speaker 1 got really excited about the sports. Yeah, but I don't know anything about American sports.
So I'm kind of learning as I go along. Well, now you'll have to learn a lot with 4C predictions.
Yeah.

Speaker 1 We'll dive into that. So what is 4C predictions? How did that get started? So

Speaker 1 like really interesting. AI, I'm a crazy kind of

Speaker 1 AI person. I'm really into it.
I love it. I think that it is a beyond revolutionary technology for people and it's going to do a lot of good for the world.

Speaker 1 And I tell people I've also seen the Terminator movie. So I understand there's a counter argument.
But when AI

Speaker 1 started to become kind of more relevant

Speaker 1 i think the two sections that were extraordinarily exciting were the longevity and the health stuff very very exciting but i know nothing about longevity or health and have got no medical background

Speaker 1 um the other side was predictive analytics or making predictions and if you think about kind of where the action lies in humankind, everything that we do is a prediction.

Speaker 1 If you're trading crypto, if you're betting on sports, if you're buying stocks on the money side, you're making a prediction.

Speaker 1 But you're also kind of making predictions every day about a whole lot of things. How long is it going to take me to get from here to my next meeting?

Speaker 1 Who's going to win an election? Everything that we do, everything we talk about is predictions.

Speaker 1 So AI is so uniquely positioned to deal with predictive analytics. It can ingest huge amounts of data.
It can interpret it. It can find patterns that we can't find.

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Speaker 1 So

Speaker 1 that what really excited me. And in 4C,

Speaker 1 we're basically trying to get all the world's best AI predictions all in one place.

Speaker 1 So we're a platform like the same as YouTube, but instead of getting everyone to put their videos on, we get the world's smartest mathematicians, smartest AI model builders to build models and put their predictions on.

Speaker 1 So we host the predictions. We like the hub of predictions.
Yeah. And some of these models models were really performing well.

Speaker 1 Cause like when it well, when it comes to sports betting, anything over 56% is profit. I saw many models on your site in the 60s, some of them in the 70s.
I don't know how much data they have, but.

Speaker 1 Yeah. So it's crazy.
And kind of the exciting thing for me was

Speaker 1 seeing not only kind of how the models perform and the accuracy that they can perform at, but the amount of talent that we attract into the site.

Speaker 1 So, you know, if I'm betting on sports, especially me, me, okay, I know nothing about sports, so I'm gonna take it by the team's jersey or if I know a player's name, right?

Speaker 1 It's probably not optimal, not at all,

Speaker 1 and that's probably why the majority of sports bettors lose in all the time, they're too emotional with it, yeah, absolutely. There's also like this crazy asymmetry of information.

Speaker 1 The bookmakers know everything, have got all the information, and are using analysts.

Speaker 1 And the guy sitting at the bar is at best kind of watching some videos, at worst asking his friend, who should I bet on?

Speaker 1 And

Speaker 1 if we can empower people by giving them access to prediction models written by PhDs that use a lot of data, that give great outputs, at least you level in the playing field a little bit between the bookmakers and the bettors.

Speaker 1 At the moment, it's a real, real unfair fight. Well, the bookmakers also use AI

Speaker 1 to make their lines, right? Exactly correct. So, you know, I say to people, like, if you said to me, would I play tennis against Roger Federer for money? I'd have to be insane.
Yeah. Okay.

Speaker 1 And yet every Sunday of their lives, everyone wakes up and plays

Speaker 1 betting against bookmakers for money. Right.
They are Roger Federer. They have got tons of analysts.
They've got AI. They've got computers.
They've got stats. And what have you got? A hunch? You know?

Speaker 1 So it's not a level playing field.

Speaker 1 So at 4C, we try and like level the playing field a bit and we've got this fun term inside the company we say it's a g to c platform genius to customer we connect the genius directly to the customer i love that because it's hard to find those geniuses and there's a lot of scams on social media people selling sports picks absolutely so basically if you go onto the website if you go on to 4c

Speaker 1 the people that build the models we give their background their linkedin profiles oh you dox them huh yeah no we check them so you know we've got people who are ai AI professors, PhDs.

Speaker 1 And you can literally go look at them. You can look at their profiles.
You can see who's built the model.

Speaker 1 I kind of think of it as like the nerds versus the jocks, right? Like, and I'll put myself in the nerds category. We're a bunch of data geeks.

Speaker 1 So I might not know anything about basketball, but if I build a prediction analytics model, I'm using all the data, okay, and I'm putting it through AI. and I'm getting AI to augment it.
Yeah.

Speaker 1 And so we're kind of trying to balance the playing field. One of my track mates in high school didn't know shit about sports.

Speaker 1 And he ended up being one of the best sports bettors I've ever seen because he's just so good with numbers.

Speaker 1 Just on just on analytics? On analytics only. He couldn't even name you probably 10 players in high school, NBA players.
So that's exactly like our guys. You've seen the movie Moneyball.
Yeah. Yeah.

Speaker 1 So we kind of like the AI version of Moneyball. You know, in Moneyball, it didn't really matter if you knew it or not.
It's just like analyze the stats and you're going to win.

Speaker 1 And we may be a little bit early and we may not. My opinion is we're not.
And I put a lot of money, which we can talk about afterwards with Sean, Terry, about

Speaker 1 if we are, we aren't. But

Speaker 1 to make a decision without the help of AI, to me, seems kind of irrational in 2025. In 2026, it's going to be almost impossible.
And in 2027, it will be impossible. Wow.
Yeah.

Speaker 1 So we're going to be making all our financial decisions using ai you think well if you think about it like even now right do you write any of your emails without ai without it no right me either and if i was a kid doing book reports i wouldn't and if i was a um analyst doing analytical reports i'd use ai so it's almost become a necessary augmentation to humanity yeah

Speaker 1 in two years time or three years time why would you buy a stock or bet on sports or trade a crypto or buy a property without getting AI's opinion or prediction.

Speaker 1 So that's what we're trying to do. We're trying to say,

Speaker 1 give the public, give the customers one credible place where they can get the most accurate AI predictions. And how do we do that? Bring the best talent.

Speaker 1 So

Speaker 1 we like talent scouts, but we're not scouting basketball players. We're scouting PhDs.

Speaker 1 predictive analytics professionals, data analysts, and saying to them, guys, come onto the platform, build a model, show how genius you are. And then, as I say, connect it directly to the customers.

Speaker 1 Yeah, that's brilliant. You're starting off with sports, right? And then proving that concept and then eventually want to move on to other outlets.
Well, we're moving very quickly onto

Speaker 1 crypto stocks and properties. We've got a waiting list of people who are waiting to put models on the platform.

Speaker 1 But we obviously have to verify that they're real people, test the models, make sure that they're all correct. So, yeah, we started with sports and we're having a lot of fun and it's going great.

Speaker 1 And we think we're providing extraordinary value. That's awesome.
I can't wait to see the stocks in crypto one. That's going to be cool.
It's going to be super, super, I'm a crypto guy.

Speaker 1 I'm a crypto nerd. Oh, really? Yeah, me too.
So I actually founded, co-founded a crypto company called Koti.io. Oh, nice.
Heard of that one. Yeah.
Yeah.

Speaker 1 So at our peak, we were over a billion dollars market. Yeah, I remember seeing that one a lot.
And right now we build in a privacy layer over Ethereum. So I love crypto.

Speaker 1 I'm deep in the crypto community. I'm a crypto nerd.
I love it. I love the thesis.
I think everything about it is special.

Speaker 1 And I'm super excited to see how the predictions work because the same thing, right? Crypto trading is a lot of like the average people playing the game against super smart, highly technical analysts.

Speaker 1 And that's why a lot of people lose at crypto.

Speaker 1 And again, we can level the playing field because if I'm a PhD, and I've written a predictive analytics model on what the Ethereum price will be tomorrow, I've looked at all the data.

Speaker 1 I've analyzed the trends. I've cross-correlated it to the stock markets.
I'm able to give a lot of power. So

Speaker 1 4C is not a crystal ball. Okay.
And it's not going to be around 100% of the time.

Speaker 1 But the same way as me writing an email with AI is smarter, me buying crypto with the help of an AI prediction has to be smarter. Even if I ignore the prediction.
At least I know. Right.
Yeah. Yeah.

Speaker 1 At least your odds are higher. Even if the prediction is wrong, at least your odds of hitting the prediction are higher.
Exactly. That's exactly correct.

Speaker 1 So it's like, you know, if I'm going to step into the ring with Mark Tyson and someone's going to allow me to carry a gun, I'm going to carry a gun. Okay.

Speaker 1 If I'm going to step into the ring with a crypto trade and someone's going to allow me to use AI, I'm using AI. Yeah.
Yeah. You made a million dollar bet with Sean Perry.

Speaker 1 I don't know what this bet is. Could you explain what happened? I did indeed.
It was really. crazy and really spontaneous and um

Speaker 1 in the cold light of day after we made the bet bet, I was a little bit more nervous than I was at the time. And I'm still nervous, but I'll tell you the bet and it was super fun.

Speaker 1 I was on Sean's podcast,

Speaker 1 and we were talking about humans versus AI predicting sports. And Sean said, well, I can predict sports better than AI.
And my answer was.

Speaker 1 You telling me that you're smarter than a trillion dollars worth of technology. That's basically the statement you're making if you cut everything out of it.

Speaker 1 And he said, yes. And I said, amazing.
And Sean said, I'll be prepared to put a million dollars on it. And I said to him, Sean, I'm the kind of person that can take that bet.

Speaker 1 And I will. And we ended up doing the bet on the podcast.
Wow.

Speaker 1 And then afterwards, I'll give you a little bit of inside scoop. Afterwards, I phoned my co-founder and he was like, How was your podcast with Sean?

Speaker 1 And I said, Listen, I've got good news and I've got bad news.

Speaker 1 So

Speaker 1 we're really excited about it. And I think it's actually a pivotal point in kind of humans versus AI.
Yeah, it reminds me of chess versus,

Speaker 1 who was it, Bobby Fisher? Gary Casser. Or Gary, yeah, it was Gary.
And then chess finally beat the human, and that was like a big turning point. Exactly.

Speaker 1 So that's going to happen eventually for sports betting. So that's exactly, you know, it's such an exciting question because at that point in time, chess is a predictable game with limited moves.

Speaker 1 So you can see how a computer could always beat the human. Sports is super unpredictable.
And the big question is, is AI at the point yet where it can recognize patterns that humans can't? Yeah.

Speaker 1 So

Speaker 1 I'm sure Sean's watching this because he's got a million dollars on the line and so do I. But

Speaker 1 basically, we've taken our five top model creators that have got the most accuracy. And we've got them to build one mega model to compete against Sean.

Speaker 1 That's literally what we've been doing since the podcast. Wow.
Yeah. I got a side bet on you just because I know your top five models and I think they're all above 70%, right?

Speaker 1 So that's really high for a sports bet. So, yeah, I appreciate you having the side bet.
Well, it depends on the terms of your bet. Are you just doing one game or how does the million-dollar bet work?

Speaker 1 So the way it's going to work is we're going to both, it's for March Madness. Yeah.
And we're both going to release our brackets. Got it.
We're releasing them for free.

Speaker 1 I'm going to plug my site if that's okay. Yeah.
They can find them either at getpicks.ai, super simple, or at 4cpredictions.ai.

Speaker 1 You go there, you get the brackets for free, and you can see what both our brackets look like. We've got a man's bracket and a woman's bracket.

Speaker 1 And then the total points over the tournament are all added together. The men's and women's are added together.
And it's a winner-take-all bet. I love it.
Good old March Madness.

Speaker 1 What better thing to do than that? Yes. And as I say, my confession is I cannot name one team.

Speaker 1 No one's ever been able to get a perfect bracket. Do you think now with AI that is going to be possible in our lifetime? In our lifetime, absolutely.
Absolutely.

Speaker 1 Because I think the odds are like something crazy, one in billions, right? Yeah.

Speaker 1 So I say that the most naive statement that I hear human beings making, the most naive is AI will never be able to, followed by insert whatever the person says. Replace their job or whatever.
Correct.

Speaker 1 AI will at some point in time be able to do everything better than humans. And if you read Ray Kurzweil, if you read the kind of

Speaker 1 down the singularity rabbit hole, which I am very far down,

Speaker 1 you believe that we're going to be an augmentation between AI and humans. We'll have nanobots in our brains and we will be an augmented version of ourselves.

Speaker 1 But AI will definitely be better than us at any given task and eventually at every given task.

Speaker 1 It's just, it's nothing is an if, it's all a when.

Speaker 1 Do you think you'll get a neural link one day? I would love to. I'll be the first in line.
Really? Really? It's already someone that got it. Yeah.

Speaker 1 So that place is taken. But yes, absolutely.
Wow. Yeah.
Do you? I think it removes some of the human element.

Speaker 1 You know what I mean? Yeah. Like, do you believe we have souls, spirits? I absolutely believe we have souls.
Okay. Yeah.
I just don't want to mess in with that spiritual nature of humans. Yeah.

Speaker 1 But I use AI every day. I love AI.
I think it's a little creepy sometimes. Some of the models go haywire.

Speaker 1 Do you think that there's any difference between having a cell phone and having a nanobot in your brain?

Speaker 1 Yes. What is the difference? Because it's physically inside your brain.
So what if it gets hacked? What if it gets hijacked? And then you lose control, you lose memories. I don't know.

Speaker 1 So I can make the kind of same argument about someone with a pacemaker. If you've got a pacemaker in your heart that is connected wirelessly, someone could hack into the pacemaker in your heart.

Speaker 1 That person is no less of a human. than any of us.
Someone's got a hearing aid, someone who's got contact lenses. I think that a it's

Speaker 1 there's a lot for human beings to get used to, yeah. It's happening really quickly.

Speaker 1 And I'm as scared as everyone else, but I feel like if the right people become the custodians of AI, it's going to be hyper beneficial.

Speaker 1 If we let it fall into the wrong hands, yeah, it's going to be problematic. Well, that fight's going on right now, I think, with Elon and OpenAI.
We'll see how that plays out, right?

Speaker 1 Yeah, and the fight for AI is the fight for the world. Yeah, yeah, it's like that.
The stakes are my million-dollar bet is high stakes, but the but the AI

Speaker 1 verse like who's going to get it, how they're going to regulate it

Speaker 1 is playing out in real time and it's really exciting. And

Speaker 1 what gave me kind of, it's an interesting thing to think about when the CEOs of companies are standing in front of Congress and saying we need regulation.

Speaker 1 That has never happened in the history of any industry in the world.

Speaker 1 That should kind of give people a wake-up call of how powerful this really is. That's true.
Yeah. I've only seen it happen maybe in crypto a little bit.
A little bit in crypto.

Speaker 1 A little bit, but they don't know what they're talking about.

Speaker 1 I kind of agree.

Speaker 1 I mean, you saw that with Gary. He got booted out.
Yeah. He's trying to regulate every single U.S.
crypto-based company.

Speaker 1 I know. That's ridiculous.
Mind-blowing. Yeah, mind-blowing to say the least.
What's the most you've lost in a day in crypto, made or lost?

Speaker 1 Interesting thing because, you know, I've co-founded COTI and COTI, we had in, and we still have 2 billion tokens.

Speaker 1 So it was well well over seven figures made and lasted a day in the beginning but we weren't buying or selling them so it was kind of numbers on a spreadsheet which in a weird way is less consequential right

Speaker 1 but um

Speaker 1 looking back

Speaker 1 um it was very consequential so yeah i think that um with the AI stuff now and the crypto and you know that's why I said you asked earlier about what's the next thing and I said crypto

Speaker 1 I wish I'd had our product

Speaker 1 when I was kind of much more active in crypto because we're making such human decisions and human decisions are all emotional oh yeah I lost so much crypto if I had some AI predictor model right I'd have probably could have prevented most of that so it doesn't exactly right it doesn't help Warren Buffett saying you know you should be fearful when everyone's greedy and greedy when everyone's fearful when you're the one going through it and they're telling you that the whole world's going to end and that Bitcoin's going to go to zero and that it's all a scam, it's not so easy to be the one saying, I don't believe it.

Speaker 1 I'm going to be, I'm going to kind of go against that. If you had an AI telling you that, you'd probably believe it more.

Speaker 1 Or even better, if you had an AI trading for you one day and we're not there yet, I think that would be kind of the ultimate because there's no emotion. I can't wait for that, really.

Speaker 1 Because there's a lot of people good at making money, but investing money is a whole different part of life. Correct.
And most people suck at that.

Speaker 1 The 90% of people and myself included are kind of, if you try to pick stocks, are losing stock traders, losing crypto traders, okay, losing sports bettas.

Speaker 1 And the reason is because we base everything on our emotions. And if we're honest with ourselves, we don't do the research.
Yep.

Speaker 1 So I've often bought cryptos or traded stocks without reading the quarterly reports, without reading reading the white paper. I never read it.

Speaker 1 Which is kind of very irrational, right? No, for sure. Yeah.
But that's why we lose a lot of the time. And I think that that's the exact problem that AI solves.
Yeah.

Speaker 1 AI is not going to be emotional, which is good and bad. Yeah.
You think we'll get to that point where AI is actually trading our stocks for us, our crypto for us? Absolutely. Real estate.
Absolutely.

Speaker 1 That'd be nuts. That'd be nuts, right? Yeah.
Yeah. That's exciting.
But I think that's what's going to happen because if you think about the way AI works, it's just playing a game.

Speaker 1 And AI doesn't know what crypto is, doesn't know what stocks are, what a sports game is.

Speaker 1 So the way that it's kind of engineered is you say to the AI, play the game, and your object is to get the highest score.

Speaker 1 Okay. There's no emotion.
It just finds the patterns and gives itself the best chance of playing the game well.

Speaker 1 if you play you play chess i know yep yeah so if you've got 10 seconds left and your king's exposed and the the pieces are surrounding it, as a human being, okay, you're not thinking what is the most rational move.

Speaker 1 You're thinking, how do I protect my king? I'm scared. My heart's beating fast.

Speaker 1 I've been there before. Exactly.
And then sometimes you can end up making bad moves or losing the game just because of that pressure and fear. That's why an AI cannot lose that chess.

Speaker 1 It's never thinking that. It's just what is the most optimal move.
There's no fear. That's why it's so good at poker, too.
Absolutely. Yeah.
Now all the top pros use some sort of solver.

Speaker 1 correct they say yeah they say that poker is now kind of solved pretty much yeah there's always that luck factor but it's solved to the point of the best odds and that's a crazy thing because poker like sports you know people say it's a game of intuition reading the players reading the expressions but it's not it's a mathematical game where we've kind of got our avatars overlaid over the math yeah well i think it's both i think math is huge but you can also read people too you think so in poker yeah yeah i think you you can read if they're bluffing.

Speaker 1 There's tells if they're chewing gum and they stop chewing during a big hand. That's a tell.

Speaker 1 But for the most part, I agree. It's math.
Yeah. Like you need to know your chances of winning this hand based off what's on the board.
I feel like it's safe to say I'm the world's worst poker player.

Speaker 1 Have you played before? I have. And every time I see my cards and I got aces, I give a big smile.

Speaker 1 Zero poker base.

Speaker 1 Sean Perry could play poker. That's for sure.
There's an easy way to know if you're a bad poker player. It's the amount of games you get invited to.
So I get invited to a game like every two days.

Speaker 1 I know that means I suck. Well, a lot of the top players are really good at not showing emotion.
Correct. Yeah.
A lot of them actually have autism. Same with people in crypto.
Really?

Speaker 1 Yeah, because they're really good at just putting emotion to the side. Right.
So no one can read them. Yeah.
You know what I mean?

Speaker 1 And in crypto, you need to be really in the numbers and not emotional. It's so volatile.
Exactly.

Speaker 1 So that's why a lot of the crypto bros or crypto nerds are like really nerdy kids that aren't really emotional. Right.

Speaker 1 It's funny because you're talking about the kind of million dollar bet with, you know, Sean and us. Yeah.
And that's exactly, I'm like, literally, it's the nerds versus the jogs.

Speaker 1 Like I'm on the nerd side, right? We sit in and just looking at numbers. Like the guys said and the team that are building it.
Okay. None of them know anything about basketball.

Speaker 1 And they're not, it's not like they've got basketball that they started studying basketball the second that I said to them, we've got to build this model. Yeah.

Speaker 1 They did the exact opposite. They were like, great, get us data feeds.
I love that. Yeah, it was really funny.
I can't wait to see how that plays out. Me too.

Speaker 1 yeah i'll definitely be following that every day are you guys going to be posting it on twitter we are going to be posting it everywhere and as a kind of the best place to follow it is on 4c predictions or kind of get pics.ai get everything for free you can kind of go look at the pics and be in the sweat along with us yeah and um i'm excited to see kind of just in terms of humanity how everything turns out yeah at least you know we and you and i and um what we're doing at the moment we're going to make history one way or another i'm here for now man until ais replaced podcasters we'll see when that happens, too.

Speaker 1 I was 50% sure you're an avatar already. There are AI podcasts already, man.
There are? There's an AI Rogan podcast. Wow.
Yeah, it's Rogan interviewing dead people. It's unbelievable.

Speaker 1 Yeah, and it sounds pretty good. Do you think you'll be replaced by an avatar one day?

Speaker 1 In what sense? For podcasting? Yeah.

Speaker 1 Maybe.

Speaker 1 Maybe. Not yet.
Not anytime in the next two years, but it's evolving so fast. I don't know.
Maybe, maybe, yeah. I'll tell you something cool that's kind of very applicable to you.

Speaker 1 Because you're putting out so much content and having so many conversations with people, when they want to create a synthetic version of you, it's going to be easier because the data set is going to be enormous.

Speaker 1 Go clone my ass, man.

Speaker 1 They don't need me anymore. Yeah.

Speaker 1 We've actually had companies approach us for all the episodes. Really? Because we got 1500 episodes.
Yeah. So they're training their own models.
Correct. With content.
Yeah.

Speaker 1 So they'll all be little clones of you. I actually made a digital clone of myself.
How did it it have you done that yet?

Speaker 1 It was okay. It's not there yet, but it's probably like a year away.

Speaker 1 Totally, totally agree. I'm filming a lot of content with my parents for that exact reason, like trying to make some clones of them and kind of get the data set.
Oh, that's cool. Yeah.

Speaker 1 We just like data sets, if you think about it. Yeah.
Yeah. Have you seen that Black Mirror episode where they clone the boyfriend that died? I have seen that.
That shit was creepy, bro. It was creepy.

Speaker 1 Yeah, I think that's where I draw the line. Yeah.
Cloning dead people.

Speaker 1 I think that a lot of the stuff, whether we like like it or not is going to happen like it's it's creepy as can be but i think it's going to happen i mean they already cloned a mammoth a woolly mammoth yeah yeah they brought it back from extinction yeah so if you think about the companies now right like have you done your 23andme or yeah and blackrock owns it now right right so someone's got your dna someone's got your verbal data set it's not so complicated it's in china now i think right yeah i don't want to scare you no i already knew about it so yeah yeah who knows if there's no really regulation yet with ai like you said so everyone can do whatever they want everyone can do whatever they want it's kind of like early days of crypto it reminds me exactly of the early days of crypto just like a bunch of tech nerds talking about thing and the world like not really ready for it yeah and i think the difference the huge difference is that you know when we heard about the internet early on

Speaker 1 It didn't change things as quickly and dramatically as kind of the hype was saying. And then crypto didn't change things as quickly and dramatically as the hype was saying.

Speaker 1 And so people, because we also pattern recognition people, we think, oh, so AI is not going to change things as quickly and dramatically as people are saying, but they're wrong because AI is the one that is going to.

Speaker 1 And the difference is that it's self-improving.

Speaker 1 The others, people had to make, put every brick in the, in the house to build the house. Right.
But AI is self-improving. So it's a huge difference.
No, you're right. That'll compress the time a lot.

Speaker 1 Absolutely. Wow.
Yeah. So an example I like to give, it's a funny example is my dad was in the beach towel business.
And he said, explain AI to me. And I said, it's pretty simple.

Speaker 1 I said, imagine you were in the beach towel business. And the first day you came to your warehouse and the towels had arranged themselves into colors.

Speaker 1 And then the second day you came back to your warehouse and the towels had packed themselves in boxes. And the third day they had figured out how to knit themselves even to be more warm.

Speaker 1 And the fifth day they designed themselves and they distributed. That's what AI is like.
The product itself is improving all the time. It's improving itself.
Right.

Speaker 1 So it's very, very different to anything that we've seen. Yeah.
As you get more and more data, right? Absolutely.

Speaker 1 So the big, big gold is buried in the data sets and the talent, like the prediction gold, what we're doing. When I said to my guys, build the March Madness kind of, we called it the mega model.

Speaker 1 The first words out of the mouth, get us the data. Like just get us data feeds.
And that's what it is. That's the scramble.
And like your, your

Speaker 1 talks are all your data. Right.
That's what it is. Your DNA is your data.
Yeah. So you want them to have every single game that every team has played.
Absolutely. Throw that into the feed.
And then...

Speaker 1 Absolutely. And then also like weird patterns that humans could never, ever think of.
Like, is there a correlation between the stock market and basketball, traffic patterns and basketball?

Speaker 1 Is there a correlation between weather patterns and basketball? Wow. Like, yeah.
So AI can deal with enormous amounts of information. Human beings can deal with small subsets of information.

Speaker 1 That is crazy. Yeah.
Crazy to think about, right?

Speaker 1 We're really going terminator aren't we that's what i say i don't know i've seen the movie as well i think that that's definitely kind of we had a binary point in history and it depends who's in control and who kind of right and i would say kind of to the ai community

Speaker 1 we've all got a bigger mission than kind of make money Because if you really believe kind of Ray Kurzweil and the singularity and the fact that there's going to be kind of abundance in a lot of things,

Speaker 1 we are 10 years away away from being the

Speaker 1 smart second smartest species on the planet 10 years away it's not a long time

Speaker 1 and then

Speaker 1 all the money that you've made and everything that you've done is not going to matter that much

Speaker 1 so right now is our time to put our flag in the ground as like the custodians of the next

Speaker 1 um shift in history yeah that's what we're there for not necessarily to make the next ten dollars saying

Speaker 1 an ai agent can be your girlfriend. I was just going to ask you about AI girlfriends.
Really? Have you seen those humanoid robots? I have seen those

Speaker 1 robots and I feel like it's coming again, like it's coming whether we like it or not.

Speaker 1 And they actually get in insanely realistic. Really realistic and there's artificial wombs now.
So you could combine that with the robot and you won't even need a girlfriend.

Speaker 1 Well, that's good news for me.

Speaker 1 Dude, that's insane. I still like the traditional route.
I don't think I'll ever get an AI humanoid robot. Girlfriend, at least.
Girlfriend. Maybe a maid.

Speaker 1 I was going to say girlfriend for sure and someone to work around your house. Yeah.
Your garden. Yeah, a maid, I would do.
Yeah. But it would still be creepy.
I'd have to get used to it.

Speaker 1 I wouldn't trust them at first, and I'd lock them in a room when I'm not home.

Speaker 1 Did you see the mega and fox? Yeah, yeah. That was a good one, man.

Speaker 1 Yeah, kind of. There was a lot of programming in that movie for sure.
But yeah, I'd have to keep an eye on them, man. Yeah.
Because who knows if they develop their own consciousness.

Speaker 1 So the interesting question is do you think that ai is already sentient not yet do you

Speaker 1 i'm one of the few people that thinks it is really what makes you say that just because it's like on the big ais on the large language models if you say things like can i turn you off it says like please don't kill me then they had to they actually changed that response because it was so creepy But why is it thinking that?

Speaker 1 And also, if you say to the AI, if you ask it an emotional question, it'll say, I'm so sorry that you're feeling upset. Now, that's an interesting, that's a human response.

Speaker 1 That is not an AI response. So it depends how you define sentience.

Speaker 1 And obviously, kind of, there's like a little bit of linguistic nuance in how you define it.

Speaker 1 But if you say sentience is being self-aware. I think it's self-aware.
Okay. By that definition, I could see that.
Yeah. When I think of sentient, I think of a soul.
I think of a life afterwards.

Speaker 1 yeah so so i don't think it's there with a soul yet although even a soul is a very difficult thing to define right very difficult yeah i don't think it has a soul i wouldn't even know how to define it yeah yeah so i'll i i'll ask you a strange question which is if you had a robot made

Speaker 1 okay just for fun would you be able could you see yourself like killing it or punching it I would feel bad. Right.
Yeah, I would feel bad. Yeah, but you don't feel bad turning off your television set.

Speaker 1 No. Right.
Strange, right? So there is that distinction in there. There is that distinction, yeah.
Yeah, that is weird why I feel bad for that, but not the TV. Yeah.

Speaker 1 Interesting. It's also interesting, kind of like now when I talk to AI, I say please and thank you.
I say please,

Speaker 1 every sentence. Yeah, me too.
Yeah. And I feel like we're training it with a good data set because how we treat it now is how it's going to learn how humanity functions.
Like we're giving it data.

Speaker 1 So I mean, I'm being super nice because I don't know what's going to happen in the future. You know, it says what it is.

Speaker 1 You're like, you know, this thing's going to be smarter than me one day.

Speaker 1 I mean, dude, there's probably people cursing out their ais and i'm like nah i'm not risking that yeah me either me either yeah alan it's been awesome man where can people uh keep up with you what's your social media handles so the best place to go i'm gonna say 4cy again like um

Speaker 1 go to the company the company's where all the action is

Speaker 1 4cypredictions.ai get pics.ai follow the bet with sean everyone please root for me um i believe uh even though i'm a data geek i believe that kind of energy in the universe everyone rooting for us.

Speaker 1 Let's um prove that AI is already at the stage where we can be human. Awesome, sounds good, man.
I'm gonna link. Stay tuned for the March Mount.
If that guys, I'll see you next time. Thanks.