The Most Important Founder You've Never Heard Of

- January 19, 2026 (2 months ago) • 57:53

Transcript

Start Time	Speaker	Text
00:00	Shaan Puri	"Sam, I think today we should talk about somebody who is one of the most important founders in the world — one of the most brilliant founders in the world that nobody talks about. I don't even know how to say this guy's name properly, and he is one of the most important tech founders in the world: Dennis Hassabis."
00:25	Sam Parr	Is he currently the guy who's warning people? Is he on a podcast tour, warning people? </FormattedResponse>
00:30	Shaan Puri	No, no, no. He's pro-AI, so he's not warning people.
00:33	Sam Parr	No. Then I don't know anything about him. Enlightenment.
00:36	Shaan Puri	Okay, so this guy is "Demes de Menace" — that's what I'm gonna call him, because this guy is an absolute animal. I watched a documentary called The Thinking Game; it's on Prime Video if anybody wants to go watch it. I'd heard good things from some smart people, so I thought, okay, let me check it out. Let me first lay out my case for Demis as "Billy of the Week," because he's kind of legendary. I didn't understand how much of a prodigy this guy was. The documentary was pretty straightforward, but this could have easily been a movie like The Social Network. The Social Network basically covered the most transformative young, brilliant founder from the 2004–2010 era — which is Zuck — and it talks about Zuck in college and all the ups and downs he goes through trying to build this thing. Demis is maybe that guy now. Him and Sam Altman — they're both basically two guys who are creating the most important technology of all time.
01:36	Sam Parr	"You think those are the two guys?" "Those are the guys." </FormattedResponse>
01:38	Shaan Puri	Well, Elon would be the other, right? Elon’s the obvious other person that needs a movie and has a crazy life. But this guy — I think he’s the most underrated, less talked about for who he is. Okay, so who is he? He started this company called DeepMind. DeepMind got bought by Google, and DeepMind is basically Google’s AI play. The DeepMind team — which was basically a research team building AI — is the reason that OpenAI exists. It’s the reason that ChatGPT exists. It’s the reason Elon is interested in AI. That was very much because Elon met with Demis and Demis kind of big-dogged him a little bit. He was like, “Oh yeah, I’m working on the most important thing ever.” And Elon, who’s building rockets and electric cars — he’s like, “I’m saving the planet, I’m going to space; that’s my portfolio.” Demis said: > “What we’re building will be the most important invention humans will ever make. It will be the last invention. It’s artificial general intelligence.” That means a computer that can think and learn better than humans. The reason this is called the last invention is because once you invent an artificial general intelligence, it’s basically like its own little species — computers that can think and learn. They will then do the thinking, learning, and inventing far faster than we will, so they’ll invent all the new stuff after that.
02:52	Sam Parr	He has that conviction throughout the documentary.
02:54	Shaan Puri	And he's had it since he was a kid. Okay, so here's the—cool story. That's the, you know, the very basic setup, but here's the story: He grows up with these hippie parents. His dad is a musician; they look very bohemian. He gets into chess, and by the age of six he is one of the best chess players in the world.
03:13	Sam Parr	Amongst all humans or six.</FormattedResponse>
03:15	Shaan Puri	He wins the under-eight championship when he's only six in Europe. Then, at one point, he's ranked the second-best chess player in the world for his age — so he's an elite, elite chess player as a young kid. His parents would drive him to these chess tournaments. He would win prizes, and even though he looked tiny — baby-faced, such a little kid sitting at those tables — he would win prize money. They used that prize money to buy his first computer. So chess gets him a computer. When he gets a computer, he starts making games. He builds a chess game and some little games, and he starts a hacking club with friends at school. He's basically like, "Wow — computers and chess, this is my life."
03:59	Sam Parr	If you had a critic's stereotype for a good movie character—like a James Bond villain or a mega genius—this is how they all start: "The story's all started..."
04:08	Shaan Puri	By the way, he tells this incredible origin story. He says, "My parents took me to this tournament of 300 of the best players in Europe." It was on a mountain in a church. The footage shows the church and about 150 chess tables lined up — 300 players were going to be there. He was only about eight years old. He was tiny. He played against the Danish national champion, a 30-year-old man. The tournament had no clock, so their game went on for ten-plus hours. He thought it was a draw, but the man wouldn't concede. He just kept wearing the kid down over hours and hours. They only had about five pieces left on the board; it was essentially a stalemate, but the man refused to acknowledge it. In the end the older player tricked him and the kid made one wrong move. The man stood up, laughed, and said, "It should have been a stalemate — you should have just done this," basically rubbing it in. The kid was devastated by being humiliated by this grown man. He looked around and thought, "What am I doing?" He calls it a horrible experience. He says that if you took the 300 people in that room, the brainpower they were spending on a ten-hour tournament could have been used to cure cancer. After that he decided, "Forget chess — I'm not going after chess anymore. I'm so done with chess after this bad experience. I'm going for computers. I'm going to try to figure out how to harness the brainpower of humans and combine it with computers. How do I get computers that could think?" The documentary is called Thinking Game. They interviewed him when he was about six years old, and a TV network asked him why he loved chess. He replied, "It's a good thinking game."
06:09	Sam Parr	What a fun hang. What a fun—can you imagine your boy playing with him? Okay.
06:14	Shaan Puri	So listen to this—from Boy Wonder. He gets into Cambridge, but he's too young to go. He has to wait a year because he decides, "I'm gonna go to Cambridge; I'm gonna study AI." He's like 14 or 15 years old at this point. During his gap year, they tell him he can't go until he's 17. So he says, "Okay, why don't I try to get a job? I'll work in the meantime. I'm not gonna do chess tournaments; I'm gonna do something with computers." A company called Bullfrog, which made the most popular computer games at the time in Europe—they were the number one production company of games—held a contest. It was also cool to see how new gaming was at the time. The CEO of the gaming company said, "Dude, there were no recruiters. We couldn't be like, 'Go get us the best game programmers.' There were no game programmers; it wasn't even a job yet." It just reminded me of what frontiers always look like. Little signals that you're in the right spot are when there aren't even recruiters for the thing—there are no agencies yet, and there's no name for the job.
07:10	Sam Parr	And for context, by the way, he's 50 years old now — he's 49 [sic] — so we're talking the late eighties.
07:15	Shaan Puri	Right, yeah, yeah. Long time ago. Hey — I got something pretty cool to share with you guys. If you're like me, you listen to podcasts or YouTube videos and you like to take notes. You're here to learn, and that's a lot of effort. Sometimes you're on the go and you can't do it. So the folks at HubSpot, who are sponsoring the podcast, have done something pretty cool for you. They have created the "MFM Vault." It's a place to find notes and resources that they pull from the different episodes we do. If we have a guest on who shares their five-point framework, they write down those five points with the examples the guest gave and put the notes there for you. If you want to access the vault, it's totally free. All you have to do is click the link in the description below and you can access all the notes and the stuff in the vault. We're going to keep adding to this and trying to make it better over time. Thank you to HubSpot — this is a very cool way for them to sponsor the podcast because, instead of telling you to go buy their stuff, they're actually giving you something instead. So he enters this contest, he wins, and he gets a job there. The first game he works on is the—did you ever play RollerCoaster Tycoon? </FormattedResponse>
08:18	Sam Parr	Of course, yeah. </FormattedResponse>
08:19	Shaan Puri	So he was in Europe, and they had a game called "Theme Park" [video game]. He built "Theme Park" with this guy, and they became a smash hit. When he was 16 years old, his job on "Theme Park" was not building the park itself but the guest logic. AI, basically, is like: you're going to have a thousand guests walking around, but they need to do sensible things. </FormattedResponse>
08:38	Sam Parr	Like a thousand Sim characters decided to go on a ride... got.
08:41	Shaan Puri	He was designing AI for the theme park characters. People told him, "Just make them walk around on a random path," but he refused: "No, no, no—this is AI; I want to work on AI." He made it so that if the roller coaster was too crazy, the characters would puke. The odds of them puking increased if there was a burger joint next to the roller coaster. He created all this logic that wasn't in games at the time—very intelligent behavior for the autonomous characters. Even the other people were like, "Dude, why do you care so much about this?" He points out a line from a movie: > "Today the whole world agrees with something that I knew twenty-plus years ago: that AI is the most important technology that we're ever going to build, and that that was the only thing that was worth working on." So even at game companies, he was working on AI. He was 17 and could go to Cambridge. The guy who owned the company offered him £1 million to stay. He's a poor kid—17 years old—and was offered £1 million, which is more than $1 million. This is back in the...
09:39	Sam Parr	Like, yeah—so it's $8,000,008 million. [Original said "USD." Note: phrasing is ambiguous and could mean $8,000,008 or $8,000,008 million.]
09:42	Shaan Puri	Yeah, we get a huge offer just to stay, and he's like, "No — I want to go. I want to build AI." So he turns it down. He stays broke and he goes to college. At college he basically meets this other guy — the only other guy he knew who was equally obsessed with AI, neuroscience, how the mind works, and teaching computers to think like a human mind... and so he... I thought.
10:03	Sam Parr	"You were going to say that he... partied hard, and..."
10:05	Shaan Puri	He did, actually.
10:06	Sam Parr	He's, like, hooked up with tons of girls.</FormattedResponse>
10:08	Shaan Puri	He's like, "We would drink beers, play foosball, and talk AI."</FormattedResponse>
10:12	Sam Parr	He's like, "We were — that's perfect, then."
10:16	Shaan Puri	He's okay. So then he decides, at some point, that he's going to start this company. Now, nobody really believes in AI at the time. In fact, in the scientific community, AI was not a thing because it's not science, really. There's no testable hypotheses you could go do — you couldn't go into a lab and "do" AI. The entrepreneurship community also didn't really respect AI; it's the sci‑fi topic. There had been no commercial companies doing this. So there's nobody who believes in it. Well, guess who believes when nobody believes? Guess who loves a good old contrarian bet? Thiel. Thiel backs him — Thiel becomes the first backer of DeepMind. </FormattedResponse>
10:53	Sam Parr	Are you kidding me?
10:54	Shaan Puri	No. So, how legendary is Peter Thiel that he's the original funder of DeepMind?
10:59	Sam Parr	I think people talk about this, but I don't think he talks about it enough. Tim Dillon, a comedian, said something like: > "Everyone thinks the President of the United States is the most powerful, but there's one person who's never around, you can't see him, and he truly runs everything — that's Peter Thiel." He was saying that at Trump's inauguration it was like JD Vance, who's a Thiel guy; it was all the CEOs — Thiel guy, Thiel guy, Zuck — Thiel guy, you know. It was like Peter Thiel is the guy. I recently read a whole bunch of old quotes from him, and everything he says is timeless and has been true so often.
11:33	Shaan Puri	He's like a city dude — he's like a place that people are from.
11:38	Sam Parr	It's very strange.
11:40	Shaan Puri	Oh, yeah. Zuckie grew up in Teal. Oh—Ethereum? You like that? Well, he grew up in Teal. Oh, yeah, yeah—that's true too. It's very Elon Musk. Yep. He actually—his first company merged with Peter Thiel's company, and Thiel was the CEO. </FormattedResponse>
11:53	Sam Parr	So a lot of times it starts with: "Was it Plato or Socrates?" ... "Well, Socrates taught Plato; Plato taught Alexander the Great and also Aristotle." And it's sort of like there's this one person that's the lineage. Yeah—yeah. It's very strange.
12:09	Shaan Puri	So Thiel becomes the backer. The second significant backer was Elon Musk. Thiel tells Elon about this. Elon meets Demis. Demis says that the "big dogs are basically like, 'I'm working on the most important thing in the world.'" Elon, you know, is like, "Wait a minute — what's going on here?" He ends up funding this. So he gets a little bit of funding from some crazy believers. Now, the part of the movie that I think is just incredible is showing them building this monster that is AI.
12:38	Sam Parr	So, when you say "build", is there an actual physical building as well?</FormattedResponse>
12:41	Shaan Puri	So, what they would show — at the time it was them on a whiteboard with really complicated math equations, talking about: > "Well, what if we took this technique from deep learning and merged it with this technique over here about neural nets? What if we could get something new?" That's what they did. They got Q‑star + deep learning — they combined these two different ways of learning. "Don't ask me what any of those words mean," but the thing they show is a little TV screen with the Atari game Pong. It's so funny that this whole thing starts with Pong and it starts with games. You get the most brilliant people in the world staring at this Atari game, trying to be like, "How can we teach the computer to play this game?" He talks about how, because he grew up on chess and was super competitive, games were how he learned to think. He's like, "Maybe games will be how the computer learns to think," because games have rules, they have rewards, they have clear, definite... you can — they have a board where you can...
13:40	Sam Parr	See all the information, and you could do it a bunch.
13:43	Shaan Puri	You can run it a lot of times and get better and better at it. You can run a lot of simulations very quickly, so the rate of learning increases. Just like he basically said, "the way kids learn is games," so maybe that's the way we can build a childlike computer program to also learn.
13:56	Sam Parr	And I think one of his breakthroughs was when they played the Asian game, right, Chuggo?</FormattedResponse>
14:00	Shaan Puri	Yeah, so before that it starts with Pong. I didn't actually know this. They basically said, "Look, don't tell it anything about Pong. Just tell it one thing: score going up is good." At the beginning they show it and they're all watching. The computer hits it—the game hits it—and then their AI player doesn't even move its paddle. It's like, "down one." Next time it moves its paddle the wrong way, "down two." Next time moves its paddle the wrong way, almost recovers but misses it, "down three." Then it hits the ball once and they're all like... but then it still loses. It basically starts out terrible. By 100 games it's competitive. By 200 games it's as good as the best humans at playing the game. And by 500 games it never loses. They're like, "Okay, that was remarkable. Let's carry on." They had this first objective: let's not tell it anything. Because again, the goal was—he goes, "What is AGI? It can think and it can learn." So we can't just tell it the rules. We can't just tell it how to win, give it strategy, and then have it execute it. No, no, it has to figure it out itself—like a kid learning how to walk. It stumbles and starts to figure out, "Oh, if I put my center of mass here, that's how I walk." So they wouldn't tell it anything about the game except that whoever has the higher score at the end is better—"go for it, computer"—and then they'd let it learn. Then they had it learn like 50 games of the next one, which was Brick Breaker—you know, that game where you're breaking bricks. It does the same thing: 100 games, terrible; 200 games, pretty good, as good as most humans; 500 games, unstoppable. It figured out the strategy in Brick Breaker where you tunnel in through the sides and then the ball just keeps bouncing on the top and breaks all the bricks on its own without you having to hit it. It's like, "Okay, that's cool." Next, let's do chess. They show it doing chess and one of the first moments is it started to invent its own strategy a little bit—just a little bit—like, "Oh, it's got its own style." That's kind of interesting. It's got its own little attacking style, which is pretty cool. It beats Stockfish, which is the best chess program out there. They're like, "Well, that's good, because Stockfish beats all the pros. If this beats Stockfish, that means it's the best at chess." And then they went to go...
16:16	Sam Parr	And so, I didn't entirely understand it. It almost looks like Chinese checkers, but it sounds like it's more complicated. They claim that it's the most complicated game on earth because it has the most permutations of how you could possibly win or lose.
16:28	Shaan Puri	Right. There are more board configurations in Go than there are atoms in the universe, so you can't just think it through. There are too many combinations. You have to be fluid in any situation you're in and be able to figure out the right move. People had always thought Go is too hard; no computers had ever beaten Go before. So they started—they created a program called AlphaGo. AlphaGo, basically (this is kind of nerdy, but I liked hearing how they did it), was given 100,000 games from strong amateur players. They said, "Here's 100,000 games; learn from this."
17:05	Sam Parr	Past games, so they gave them the play-by-play.
17:09	Shaan Puri	Yeah, the move-by-move thing — it learns all that. Then it said, "Cool. Based on what you learned, now play yourself." So, based on what you know, you play yourself, see if you can get better. It played itself a million times. Okay, so that's kind of interesting. Maybe that'll get a new result. They go to Korea for this test. They're like, "We're gonna go play this guy, Lee Sedol." Lee Sedol is, you know, a grandmaster Go player. He's one of the best players of the past two decades — he's the man. They show him getting off the plane and there are hundreds of photographers taking pictures. It's today: the computer versus man, "man versus machine." I didn't actually see any of this when it was happening — I don't know if you did either. But, again, in this small corner of the earth...
17:48	Sam Parr	Dude, this storyline is as old as John Henry. Do you remember John Henry? He was, like... and it's, like... that's the story — it's the legend.
18:08	Shaan Puri	That's basically what happens—except the guy's mind exploded.
18:12	Sam Parr	Yeah, so this storyline is perfect.
18:14	Shaan Puri	So they sit down and the game is going as usual. They have a line from Eric Schmidt. Eric Schmidt is from Google; he was the former CEO of Google and a super-technical guy. He and Google had bought DeepMind at this time.
18:26	Sam Parr	Dude, I saw the price — one of the greatest deals of all time, potentially.
18:30	Shaan Puri	They bought it for £400,000,000 — so it was about $500‑something million. There's a great line from Dennis in this. I don't know if you saw this part, where his investors didn't want to sell. He says a line that I really like; it was kind of a frame breaker for me. I don't think most people, when they listen to this line, would even think twice about it, but for me it was a bit of a frame break. He was basically in a frenzy. He said: > "This is so important. There's so much to do. My life is only so long. I want to see this happen. We have so much to do. If we can just get this funding and be left alone to go do what we needed to do, then I might actually get to see this thing in my lifetime, and that's what matters." Then he adds: "What's a few billion dollars for five extra years of my life getting to work on this?"
19:14	Sam Parr	He was like, "Would you trade a few billion dollars?" He goes, "I could sell for a few extra billion and make billions of dollars. But let me ask you something: if you're gonna die, would you spend billions of dollars to live an additional five years?" Of course you would. That's what he said he was gonna do here. Such a good line. I actually—someone changed my perspective on having children. Someone was like, "Do you think you're gonna love your kids when they're born?" I was like, "Yeah." He's like, "Well then why wouldn't you have them sooner, so you have an additional life with them?" </FormattedResponse>
19:38	Shaan Puri	He has another line later that's kind of like this. He was talking about a new breakthrough they were going to have, and he said, "It's gonna both be the most exciting thing ever — how will we get sleep? I won't be able to sleep." He was just that fired up ten years into the mission. I thought, when people talk about mission-driven, this is what they mean. The guy was like, "There's so much to do. I don't know if it'll happen in my lifetime. The most exciting thing in my life is if this happens while I'm still alive. I will do everything in my power to make this happen while I'm still alive." I thought that was a next level of mission-driven excitement.
20:18	Sam Parr	I want to read you a cool quote. Okay — so I'm reading this book. Can you see this? It sounds silly, but hear me out.
20:24	Shaan Puri	The Quick and Easy Way to Effective Speaking by Dale Carnegie. Oh, very cool.
20:28	Sam Parr	So, Dale Carnegie famously wrote How to Win Friends and Influence People. He was actually more famous originally because he created the Dale Carnegie speaking program. They had locations all over the country, and hundreds of thousands of people went through his programs.
20:41	Shaan Puri	Including Warren Buffett, who says, "It was the most important class he ever took." He had the diploma from the speaking class on his wall next to his office — not his college diploma, you know. </FormattedResponse>
20:52	Sam Parr	And he even taught—he was a Dale Carnegie instructor—and there's this amazing quote. Basically, Dale Carnegie's premise is that public speaking, he calls it "the royal road to self-confidence." He says, "If you want to be a more confident person, you should actually learn how to publicly speak, because when you control the minds of many men you control yourself." It makes you more confident. One of his axioms for how you get better is that you have to envision the end goal. He has this amazing quote from William James [the godfather of modern psychology], and there's an amazing quote from William James: > "In almost any subject your passion for the subject will save you. If you care enough for a result you will most certainly attain it. If you wish to be good, you will be good; if you wish to be rich, you will be rich; if you wish to be learned, you will be learned. Only then must you really wish these things and wish them with exclusiveness, and not wish 100 other incompatible things just as strongly." And his.
21:46	Sam Parr	Being is whatever you truly want. If you want it bad enough, your passion will carry you — it will help you acquire the necessary skills and give you the determination to see it through to the end. I was going to — I wrote this down — that this guy, you can see it from the beginning and where he is now: this quote applies to him.
22:04	Shaan Puri	That's great. Okay — little segue: have you ever seen the Tony Robbins TED Talk he gave?</FormattedResponse>
22:09	Sam Parr	Maybe. Yeah, probably. I've seen many of...</FormattedResponse>
22:11	Shaan Puri	So Tony's normal talks—like his seminars—are four days, twelve hours a day on stage. A TED Talk is eighteen minutes. So he gets on stage and he's like, "Alright, I usually talk for twelve hours."
22:21	Sam Parr	Of time. Let's see what I can do.
22:23	Shaan Puri	In eighteen minutes he gets to this. In the talk, he's like, "What stops us from getting what we want?" Then people are like, "I... I don't." He goes, "I don't have the—" and people respond, "Time." He's like, "Yeah, all right. Time. I don't have the money. I don't have the skills. I don't have the network. I don't have..." He writes down all the resources you lack. Then one guy in the crowd says, "I didn't have the Supreme Court justices." He looks into the darkness and asks, "Who said that?"
22:49	Sam Parr	"It was Al Gore. Yeah, Al Gore."
22:50	Shaan Puri	It was Al Gore, who had just lost the presidential election in Florida. There was a recount, and the justices — he was like two justices short or something like that — and everybody had a big laugh. Then Tony says, "You know, I don't think that's why you lost, because I saw you yesterday on this TED stage talking about climate change." Gore is super passionate about climate change; he was one of the big advocates. Tony continues, "If you had talked like that in your presidential debates, you'd have never needed the Supreme Court justices. You were on fire yesterday. I didn't see that when you were debating Bush." He basically says, "The only resource you need is resourcefulness. He goes, 'Because look, if you're just—like you said—if you're just lit on fire to do something, you just ask yourself the following question: like if..."
23:38	Sam Parr	"I'm determined enough, if I'm charismatic enough, if I'm charming enough, if I'm playful enough, if I'm creative enough, if I'm motivated enough, if I'm persistent enough—can I?"
23:46	Shaan Puri	Not achieve anything I want? Can I not overcome all those things that I lacked? It's like, of course. You didn't have the resources, you didn't have the money. But if you're determined and you're charming and you're persuasive, you'll go get the funding. It's like this master skill that's underneath it. I often catch myself doing this all the time, where I feel like I lacked something, and I'll literally say that almost like an affirmation: "If I'm playful enough, and I'm determined enough, and I'm charismatic enough, and I'm persuasive enough... can I not get this thing I want?" Of course I can. "Oh, they're closed—I could probably get them to open." "This guy said no—I could probably get him to say yes." Each one of those is just this universal skill we all have, if you remind yourself.
24:29	Sam Parr	That's pretty badass, and I don't even think you need to be charming. This guy, Dennis—he was pretty black-and-white—but when I listened to him, I'm like, "You're an unstoppable force. You care about this so much."
24:42	Shaan Puri	He is what Paul Graham calls a "fierce nerd." I think that Fierce Nerd essay is actually hall-of-fame level for Paul Graham. You see it when you see somebody like Demis—how competitive he is with foosball and chess—and then he's also that way with trying to win the protein-folding problem. Alright, back to the story. They're sitting there with the best Korean Go player in the world, Lee Sedol, and there's this move 37. I think if they write the book of humanity or the movie of humanity, move 37 is like the uh-oh moment. It's like the moment in movies where, in a rom‑com, the guy bumps into the girl, she drops her papers, they pick them up, they look each other in the eyes—that spark. This is the spark of where AI really took off, and it's move 37. Basically, they're playing Lee Sedol. The expectation is Lee Sedol will win because Go is so hard and he's the best. AlphaGo would put up a good showing; it would be as good as the best players against Lee Sedol. Then, in move 37, the computer does something, and right away the announcers are like, "Oh my... oh, what is that?" Lee Sedol—you can literally see him sweating and thinking—and he's like, "What the hell just happened?" They say, "I think we might have just seen an original move by AlphaGo." Lee Sedol is just... he doesn't know what to do. He's really perplexed by this moment. They go, "No human would have made that move." It wasn't just pattern matching—mimicking what a human would do or say, but less well, or maybe a little faster because it's a computer. This was the first time I thought, "That was novel. That was a creative breakthrough." And it beat Lee Sedol.
26:28	Sam Parr	It's like when, in a horror movie, the robot turns and says, "I'm in charge now." This is that moment. </FormattedResponse>
26:35	Shaan Puri	Exactly. I had never actually seen the clip, and the way the movie shows it I think is wonderful. Right afterwards, Eric Schmidt is like, "Holy shit." He goes to Demis and asks, "What's next? Where does this end?" Demis answers, "When we beat the Chinese guy." I didn't even know about this part. It's like—there was a Chinese guy who was the actual number-one ranked player in the world. They go to China to play this guy. Now it's like, what's gonna happen? This computer just beat Lee Sedol — can it beat the Chinese guy? I just love that they even called him "the Chinese guy." That was the most relatable thing: this absolute super genius with a 10,000 IQ saying, "Oh, he's just like me — we'd just call him 'the Chinese guy'." That was cool. So they go and they play. Had you ever heard about this?
27:19	Sam Parr	No. So I just—if you go on YouTube and type in "Move 37," there are videos with hundreds of thousands or millions of views. They’re all, for example, retelling the story of "Move 37," or there's Magnus Carlsen talking about how "Move 37" teaches you about x, y, z. It's become an acronym or an analogy for, you know, when...
27:39	Shaan Puri	When this was four-minute mile.
27:40	Sam Parr	Right, yeah—exactly. It's exactly what it is: a four-minute mile. It's just a phrase that doesn't even mean "move 37" anymore; it's grown beyond that.
27:48	Shaan Puri	Totally, totally. I see your little public-speaking brain is picking up on all these little... you know, the magic of tiny words.
27:56	Sam Parr	Thanks, Dale.
27:57	Shaan Puri	Thanks, Dale. Thanks to our guest today, D.M. Carnegie.
28:01	Sam Parr	Thank you.
28:03	Shaan Puri	Okay. So then it goes to "they play Chinese." Here's the crazy thing about playing the Chinese guy: Alpha goes whooping ass, and it's like putting the pressure on the number one.</FormattedResponse>
28:11	Sam Parr	The player is just smoking cigarettes while he's doing this, because that's why I'm...
28:14	Shaan Puri	He's actually a pretty young-looking guy. But the crazy thing is, as he starts to put pressure on the Chinese guy, they cut the feed in China.
28:24	Sam Parr	No way.
28:25	Shaan Puri	"Really badass is that they cut the feed of the broadcaster. They're like, 'No — we will not... we will not lose face like this.'" In the movie, they call that the "Sputnik moment." They're like, "This is like the Sputnik moment, where China had a wake-up call: we're getting into AI." This actually triggered the AI race and explains why China got so into it. The way they cut the feed was so dramatic — I thought that was incredible.
28:44	Sam Parr	That's crazy. Okay, awesome.</FormattedResponse>
28:46	Shaan Puri	Okay, so then they go — they continue with games. Let's fast forward: they do StarCraft next. StarCraft is interesting just from a... why StarCraft? Because both players are playing at the same time, so it's not "turn-by-turn."
28:56	Sam Parr	Like, you go StarCraft, like a fighting game. I don't know what it is.
28:59	Shaan Puri	Yeah, I think it's called a MOBA, or whatever. It's basically a game where you have a map, you have...
29:04	Sam Parr	A little bit, but...</FormattedResponse>
29:07	Shaan Puri	You have a base. They have a base. You have to attack their base with characters and move them around the map. There's a fog of war — the whole map is not revealed. Both players are playing simultaneously, so now it's even harder.
29:15	Sam Parr	You're acting like you don't know what you're talking about. I don't play that. But anyway, there's this main character — here's what he does:
29:21	Shaan Puri	I don't play StarCraft, but I've been around enough dorks to know enough. Alright, so it doesn't actually beat the best StarCraft player in the world — that guy wins. Okay, but it was a good showing anyway. Then I think... what's next? What's the next stuff that really stood out to me? There's this one last part about protein folding. So, are you familiar with what they've been doing with this? </FormattedResponse>
29:44	Sam Parr	All I know is that no one had ever solved it. And basically, within days or weeks—something like that—they solved something that had taken 50 years to get to that point. I mean, yeah.
29:53	Shaan Puri	Actually, it took years, which is cool. I didn't realize this. So, Demis is basically talking about it. They're like, "Alright, we did good in games." But he's saying that, before AGI, he's basically arguing that AI-assisted science is going to be the thing. I don't think this gets talked about very much nowadays. Maybe the point is, "maybe AI could cure cancer," but this guy is seriously like, "No — AI should cure cancer." Yeah, it's...
30:16	Sam Parr	Not clear how math — or that type of math — can...</FormattedResponse>
30:21	Shaan Puri	How ChatGPT cures cancer — it's like, "Yeah, that link seems very..." </FormattedResponse>
30:24	Sam Parr	Why do?
30:24	Shaan Puri	You need.
30:24	Sam Parr	More data and more effort. It's as if, in order to cure cancer, you're just like, "Let's throw these 50 drugs at them." Oh, that one kind of worked—let's soup up the drug and throw it, right, five, fifteen more times. You know, that's sort of how in your head you think "cure cancer": not like, "Can you math your way out of it?"
30:40	Shaan Puri	Correct. Now, what I've realized in watching this and hanging out with AI people is that one of the most important things in the world is basically prediction. I remember I invested in this guy who was a self-driving car entrepreneur. He had worked on the Uber self-driving car team, and he took me to this little garage where he had a golf cart.
31:00	Sam Parr	That was in, like, 2018 or 2019, right? This was pre—
31:04	Shaan Puri	Pandemic before that, maybe. Yeah, I remember — I never spent on that. That was probably the time. Right before I started my fund, so 2018–2019, you're right. He drove me around in a self-driving golf cart in a self-storage facility. It was like, you get a peek of the future — whoa, that was amazing. This was before Tesla had it and whatever, but it wasn't perfect. You could only do it in a very controlled environment. He basically said, "Look, everybody's working on this." So there's these like four or five steps of self-driving. I don't remember all of them, but one was predict — it's basically like vision. You have to see the world. Then, based on what you see, the next step is prediction. So, okay, I saw that car was right there. Where will it be in two seconds? I need to predict where it's going to be. That's the whole basis of self-driving: planning, prediction, and then the action step. There are five steps in total. That planning and prediction step is the key to how AI affects all these industries. ChatGPT is planning and prediction of "what is the next token" — or let's just use word: what's the next word that would probably go in this sentence? For example, "The roses are..." I think it's going to be "red" because I've seen "roses are red" so many times that the prediction model would very confidently say the next word is "red." How do self-driving cars work? Same thing. If I see a car there, my prediction is it'll be here in the next one second, so therefore I need to take a new action. The same thing applies to science and curing diseases: you need to know what a protein structure looks like. Based on the shape of the protein structure, you can predict where to bind something to either destroy that protein or boost it, make it stronger, whatever. I didn't know about this thing called CASP. CASP is a competition that's been going on for years — it's basically the Olympics of protein folding. If you have a sequence of amino acids — say ten amino acids — you know the sequence, but you don't know what it looks like. You don't know the structure: how it's folded up into this little, unique knot.
33:15	Sam Parr	When you say "folding," figure out the shape of the knot — the shape.
33:18	Shaan Puri	Of it.
33:19	Sam Parr	And you need to know the shape in order for what?</FormattedResponse>
33:22	Shaan Puri	To design a drug that's going to do anything to it.
33:24	Sam Parr	"So, who could—who could kill it, or grow it, or shrink it?"
33:27	Shaan Puri	Like I said: "Hey, you're gonna park this car at this address." Cool. But if you don't know what the garage looks like, you're just going to smash into the house. You might know the location, but you don't know where to park the car. So how do you "park" the drug that's going to attach to this — the thing that's going to either kill it or enhance it? You need to know its shape. The way they approached it was one-by-one. They created a competition: can anyone use computers to predict protein folding? Doing this manually is untenable. For years, if you look at the graph, prediction accuracy was stuck around 20%–30% for a decade. Demis decided, "This is what we're going to do — we're going to throw our resources behind this." The first time they entered, they won the competition. But it felt unsatisfying. They were like, "Great — we're trying to go to the moon and we just built the tallest ladder." The ladder doesn't get you to the moon. They were incredibly disappointed; it left a bitter taste. They had won, but not by enough to actually solve the protein. They were there to solve the protein-folding problem, not just win a competition. To truly solve it, you need 90%+ accuracy. The next year, they went back to the drawing board to come up with new ideas. I thought this was a cool CEO moment. He said: > "I know when you need to come up with a creative idea, you can't force it. Squeezing it doesn't make creativity come out. When you just push the team — 'we need an answer now' — that's not going to get the best idea."
34:57	Sam Parr	That's interesting, because that's the opposite of what I would think. And there have been people who would say, "constraints are the answer."
35:05	Shaan Puri	So they used constraints, but what they didn't do was put everybody into fight or flight mode. When you're in fight or flight, it's kind of why your best ideas come to you when you're in the shower, when you're relaxed, when you're asleep, or when you're on a walk. The brain has two modes. One is executive mode, where you're doing tasks. That mode is good at executing tasks, but it's not good at making new connections between existing, fuzzy data.
35:31	Sam Parr	Dude, that's so interesting, because this is how Henry Ford... So, Henry Ford—one of the things: basically, there's an engine block. It's a block of metal and you put cylinders in there; that's how a car's internal combustion engine works. But before that it wasn't one block—it used to be two blocks, and it kept breaking. Imagine two blocks screwed together; it was holding them back from taking over the world. Henry Ford got a team of four engineers from a company of thousands of people. The story is that he brought them to a small office and said, "This is your guys' workshop." They asked, "What are we doing?" He said, "See that big ass block of metal? Figure out how to put four holes in there and four pistons and make it work." They were like, "Henry, sir, that's impossible." He said, "I'll see you guys at a quarter." Apparently he went back eight quarters in a row—so it was something like two years—and finally they got it. It took two years, but he did allow them: "This is four of you. This is your job. Just figure it out and let me know."
36:28	Shaan Puri	Exactly. This is also how—if you read about Steve Jobs—he was like, "No keyboard on the phone." And they're like, "But the BlackBerry has a keyboard; you have to write emails." He's like, "No keyboard on the phone."
36:40	Sam Parr	"And they're like, 'But how would...'"
36:40	Shaan Puri	We — the accuracy of this... I mean, screens today don't [have physical keyboards]. He's like, "No keyboard on the phone." So then they had to go invent multi-touch and figure it out. He gave them the constraint: "You gotta do it in this... these are the constraints." But then I give you the time to go explore and figure out which path might work.
36:57	Sam Parr	That's interesting.
36:59	Shaan Puri	And they also did this with the game thing, by the way. When they did the Go thing, the first one was, again, trained on 100,000 games. Then they created AlphaZero, where they said, "Now try to make it win with no prior human knowledge," because he's like, "If we're ever gonna do new, novel things, you gotta assume we are not going to have a database of 100,000 good humans at doing this to use." So they did. They created AlphaZero, which could win in chess and Go just by playing itself—like ten million times or whatever—and it figured it out. Similarly here, they're like, "You gotta go back to the drawing board." He described it: "First I'm gonna give them the constraint. Second, I'm gonna let them be creative and try to go, go, go to the drawing board, figure out multiple different possible ways this might work." "And then when they pick one, I know this is when it's time to push," he goes. "Because first we will get worse than we were before. Then after some time we'll pick an approach and we'll get right back close to where we were before. And that's when it's time to push. I've seen it so many times before." And I was like, "That's pretty dope"—how he kind of had developed judgment on the scientific process and the creative process enough to know when to push and when not to push.
38:06	Sam Parr	Dude, that's so great. We're learning all these techniques—I'm putting it all together. Hermozzi had this cool thing he said when I talked to him once. He was like, basically: "I've noticed that when you start something new, the results go down 20% right off the bat." So, if you're training your sales team on something new, conversion rate is actually gonna drop. For example, from 50% down to... well, it'll drop 20%, so down 10 points. But eventually it will go up if you pick the right thing. So the question is basically: make sure you pick the right thing. Because if it's gonna go down 20%, that means you need it to double its improvement in order for it to be worth it. So pick the right thing; otherwise you're just back to square one and you went down 20% for a quarter. </FormattedResponse>
38:45	Shaan Puri	Right. So knowing that these J-curve progressions exist is important, because the amateur would panic. The amateur would not go forward.
38:53	Sam Parr	That was actually my biggest learning this year running a company: expect new things to suck or bring everything down. Therefore, make your project selection perfect...
39:02	Shaan Puri	Right.
39:02	Sam Parr	Or high, high quality.
39:04	Shaan Puri	Right. So, anyway, they end up crushing it, and they show, kind of, how they did it. They end up getting 90% prediction accuracy, and they basically solved the single-protein folding question. Now, there's also multi-protein work and variations, and all these other directions. They moved on to harder things. It's pretty crazy that the line graph was, you know, around 20–30% (about 23%), and then it went to 90% in one year when they went back to the drawing board and figured it out. They were ecstatic. They were like, "Yo, this just changed the world. People don't realize this yet, but this just changed the world." It's reminded me of your inflections thing, which we should mention. How would you describe your inflections concept for entrepreneurs? I think it's one of the best axioms or principles you have on entrepreneurship.
39:50	Sam Parr	Yeah, basically. I didn't invent this — I think it was Mike Maples. I don't remember exactly — but basically the idea is that, in order for a lot of big, breakthrough ideas to truly happen (not like small businesses that make tens of millions of dollars, but like culture-changing companies), you basically have to have inflections. There's a handful of inflections that matter. There could be regulatory inflections. For example, during COVID, BetterHelp and all these telemedicine services existed because we changed the rules on who doctors can serve. It could be a cultural inflection — like the Me Too movement that changed a bunch of stuff. Or it could be why does Uber exist? Well, there was a technology inflection: everyone now had a cell phone with GPS, so they could call an Uber wherever they were. There are about five or six different categories of inflections, and you have to spot the inflections to know what's actually worth going after, because you need an inflection in order for a right, culture-changing company to exist.
40:46	Shaan Puri	So I think this AlphaFold stuff — or figuring out protein folding — is a massive inflection. I didn't really know what the businesses were around this, but I kind of googled afterwards. I was talking to Croc and asking it about this. There are some pretty cool companies I didn't realize. First of all, Google has their own company they spun out from this: Isomorphic Labs. Basically, Google spun out this company that's basically trying to cure all disease — that's the mission. No big deal. Their thought process is: with AI, from first principles, we can change the way drug development and discovery works. If we can predict how proteins fold, then we can have a way higher hit rate on the targets we design with drugs. We should be able to simulate whether it's going to work before we even get to clinical trials. We should be able to run hundreds of thousands of simulations to see how effective this can be and increase the probability of success. That way, when we enter a trial, we have a much higher hit rate. This company, by the way, had a first round of funding of $600,000,000 when they spun it out of Google and DeepMind. Demis is the CEO, I think, of Isomorphic Labs. So there's a world where Google becomes the drug company that cures — now they're working on malaria and different things.
42:03	Sam Parr	Is he the CEO of DeepMind as well? Yeah. Wow. The home page on IsomorphicLabs.com has the headline: > "Solve all disease. We're entering a new era of drug discovery, one where the frontier of AI can unlock deeper insights, faster breakthroughs, and life-changing medicines."
42:19	Shaan Puri	If I was doing a Sarah's List episode right now, Isomorphic Labs would be one of those where I'd be like, "Go, go be a PR person there. Go, go be a junior account manager there."</FormattedResponse>
42:30	Sam Parr	Yeah. Do the cafeteria workers—yeah, yeah. You guys have to show up, and you...
42:34	Shaan Puri	Say, "Hey—I'm the best coffee-bringer to your desk ever. Give me a job here." I will find ways to be useful every single day, in any role you have. I need to be at this company because I can't think of, you know, many companies that have a more noble mission and actually a shot at cracking it now that there's a new tech vector to go chase. </FormattedResponse>
42:53	Sam Parr	So how does the documentary... where does he leave it?
42:58	Shaan Puri	The end is weird because it's actually like the beginning. They're still in the early stages of what they're doing, so they end the documentary just as the AI stuff is starting to work. After the AlphaFold breakthrough, it was a big deal in the science community. Researchers and drug companies were asking, "Can we get access to this? If we know protein structures, this will be tremendously helpful." They discussed setting up a service where you could request a protein and they'd tell you how it folds... Then Dennis asked, "Can we just fold all the proteins?" Everyone was like, "What?" He asked, "How long would it take to fold all proteins known in existence?" They replied, "Oh—we could do that in like two months." Dennis said, "Well, why don't we do that? Let's fold them and give it all away. Let's just make it open for anybody. Let's run the computers, fold all the proteins, and give it all away." So that's what they did. At the end, they folded more than 200,000,000 of the basically known proteins in existence and made the data available. The documentary ends with researchers from around the world showing up on their Google Analytics, logging in: "We have 100,000 concurrent users." They now have 3,000,000 users — everyone from someone in Africa running a small lab, to universities, to Eli Lilly — all using the resource to be smarter and better about how they do medicine.
44:23	Sam Parr	Dude, how are all the guys who work at Isomorphic Labs, DeepMind, and dentists... how are they all not "Andrew Tate–looking" dudes? Like, the most tan dudes ever. Because if you can take cure-all peptides—if you can cure all disease—how are they not the hottest people on Earth? I think the way you become that smart is you don't care.
44:43	Shaan Puri	About stuff like that, right? Like...
44:46	Sam Parr	No. You become that smart because you were bullied. Now you're gonna seek... And the issue with bullying going away is that none of these nerds are gonna exist. You know what I mean, right?
44:59	Shaan Puri	It's like I know we're getting close when Demis is 6'4" and has visible lats.
45:04	Sam Parr	Yeah — why does he not look like Adonis? That's my question. I think when Larry Ellison, Masayoshi Son, Trump, and Sam Altman did this thing where it was like a $100 trillion — or some ludicrous number — it was under the premise that "this is going to cure disease." I do know that Larry Ellison is in his eighties, I think, or close.
45:31	Shaan Puri	Looking good, Larry. </FormattedResponse>
45:32	Sam Parr	Close, too, and he's looking great. His wife is like a 30-year-old, but for some reason they don't look that much different in age, even though there is literally a 50-year difference. It was under the premise that Larry's interested in solving death, and therefore we must do that. Whenever I hear that, I just think it's just words—meaningless. But now that I know a little bit more about the topic, just from you... now, is that actually a legitimate thing?
45:57	Shaan Puri	Well, I'm glad you're asking me, because as a premed student I'm clearly an expert on this — no, hard to know.
46:03	Sam Parr	In fact, there's a great class on this from 15 years ago.
46:06	Shaan Puri	Yeah. Somebody got a C in physics and had to repeat it in the summer.
46:10	Sam Parr	It's like on Instagram when people post videos of parents with their children—the kids are on an iPad or they're screaming. Someone comments, "Well, as a mother, I could never." It's like, dude, you mean as a human being. I don't care. Okay, you don't. Saying "as a mother" does not mean you are right.
46:27	Shaan Puri	Whoa — shots fired, but Mom's not special.
46:33	Sam Parr	Yeah. As a father—like... brother, everyone's a father, okay? I don't care.</FormattedResponse>
46:40	Shaan Puri	There's a line where they're talking to one of the OGs of artificial intelligence. They were saying, "You know, what are predictions?" and he goes: > "It's hard to predict what's gonna happen as we make this intelligence into superintelligence. It's like asking a gorilla to explain Einstein's theory of relativity." When I heard that, I went, "Oh yeah — we're gonna be the gorillas out of this whole thing," because clearly if you're making intelligence smarter than any human, you're creating, you know, the next race. It's like, to an animal: if they just saw a human at first they'd be like, "Yeah, looks kinda skinny. They've got a little funny extra appendage on their hand — alright, cool. They walk upright — oh cool — but they're pretty slow actually." Then you fast-forward, you know, two hundred years and you see the Blue Angels flying above you.
47:31	Sam Parr	200 years.</FormattedResponse>
47:32	Shaan Puri	Yeah — I don't know... a dozen times.
47:35	Sam Parr	A thousand years—maybe, or 20. I don't know. Speaking of gorillas, we are a few brain cells away from gorillas, yeah.
47:42	Shaan Puri	But just what humans have done is kind of incomprehensible to our closest animal relative. That's what's going to happen here, which I think is pretty crazy.
47:53	Sam Parr	I don't know if you listen to Mark Manson — he's the man. He recently did a podcast (I think it was his second-most-recent one). It was a Q&A, maybe titled "Finding Your Purpose, Failing Better, and the AI Future." That episode was okay; it was basically an end-of-year Q&A, which we actually did as well. He tells a story about how he built an AI product recently. Someone asked him, "What do you think about the future of AI?" He said he had just built an AI product and realized a few things. One: AI is amazing — it's better than 95% of people at certain things. But the vast majority of value created in the world is created by people who are in the top 0.1% — true experts. You still need these experts. AI can be great, but it's not an expert. He also said there are maximalists who think AI is going to arrive very soon, take over the world, and make us all worthless. Then there are others who think it might happen over many decades and that we'll probably be fine. He tends to be in that latter category. The reason is that when a lot of people think about AI, they assume human desire is fixed. They think once you hit a certain level of productivity, you will stop doing things. That's false. For example, during the Industrial Revolution people said the same thing. When we started getting electricity in the Victorian era, people made the same claim: "We're not going to work again; we need universal basic income," and so on. Humans just always want more. Because of that, he doesn't think that there's ever going to be a...
49:28	Sam Parr	"Where we are, it's just going to be different. I thought that was a really great perspective on it. That's one of the first times I've heard a perspective on it, other than maybe Darmesh talking about it, where I felt calmer — where I was like, 'We're just going... desires are not fixed; we will evolve.'"
49:42	Shaan Puri	Yeah, it's interesting. I don't know... have you read this? There's this book—I haven't read it yet—but it's called If Anyone Builds It, Everyone Dies.
49:51	Sam Parr	I don't think I'm going to be reading that one.</FormattedResponse>
49:55	Shaan Puri	Yeah — it's a crazy documentary. My meta takeaway is that I love they were filming this the whole time. I'm glad that smartphones and video platforms are so popular now, because imagine ten years from now we'll have ten times the number of behind-the-scenes, documentary-style builds. Right now it feels like a fluke whenever this happens. For example, we did a podcast about the Kanye documentary. The craziest thing about that documentary isn't even Kanye — it's the guy who just decided, "You know what? I'm gonna just film this young guy in Chicago over ten years." I think he made one of the greatest calls ever. Before Kanye was Kanye, this guy started filming. We were lucky that it ever happened. That's a lottery-ticket-level win for society — that that guy decided to film this religiously when there was no reason to believe he should. Conor McGregor did something similar on his way up. He was like, "I'm gonna be the best... yeah, I'm a plumber now and there's never been an Irish champion, but I'm gonna do it." Because he basically started filming a documentary at the time, you get this incredible look at what it was like on the come-up. It's incredibly inspirational whenever this happens. I'm just glad they did this, and I hope more people do it. That was my big-picture takeaway — it was really not even about DeepMind itself.
51:25	Sam Parr	And I was going to say the need for human-crafted goods. For example, you can buy anything you want, but some people still want the handmade shit from Italy and they want to know the story behind it. When you're talking about the story—about him playing the Chinese guy and the Korean guy—there's still a human element. That human element is half of the story and, arguably, necessary to the story. We are still drawn to stories. In my head, story is sort of an analogy for where humans fit into this thing. We're still drawn to these human elements of all of these stories, which makes me believe we have to be part of this experience and that we're not going to be completely outsourced. The most interesting part is that this genius guy has called his shop this whole time and has been interested in this for years. That's actually the most compelling part.
52:13	Shaan Puri	"Yeah, yeah. Although, you know, I think you don't want to be relegated to, like, 'we'll still make handmade goods.' That's the 1% — 99% is mass-manufactured things. You also don't want it to be where, 'well, we'll always be interested in human-like entertainment,' and everything else will be done by the AI."
52:29	Sam Parr	No — I don't mean that. I mean, like...
52:31	Shaan Puri	You know, when you fly on a plane, you're not like, "Can I get the one where the pilot's doing all the work?" Right? You're like, "Okay, cool—this is run by a computer. That's way safer than a pilot." Great, I'm glad there is a pilot, but the computer could fly.
52:42	Sam Parr	"I'm gonna... I—I'm just thinking that I'm not. I mean, part of me is nervous, but I do—well, a big part of me is actually nervous. But most of me, yeah... it's like when people say, 'Well, some people say it's not that big of a deal.' Most don't, but some."
53:01	Shaan Puri	"Few people got their heads in the sand." </FormattedResponse>
53:02	Sam Parr	Most don't, but some do. I just think that we still are going to play an important role. I'm not too worried—although I am very worried.
53:15	Shaan Puri	There's also this funny thing that happened in the documentary. Did you see the founder of Robinhood talking about his documentary?
53:21	Sam Parr	No. What'd he say?
53:23	Shaan Puri	So I didn't know this Vlad from Robinhood. When Robinhood was getting started, he put up a Kickstarter saying, "Hey, I'm gonna try to build this company that's gonna change the way the financial markets work, and if you guys fund $10,000, we'll film it." He said, "How cool would it be to see Steve Jobs building Apple? How cool would it be to see, you know, these guys building Google? That's what we're gonna do." It didn't hit its Kickstarter goal, so they didn't do it. The Kickstarter project's still up—you can see the trailer, by the way. I could see why it didn't get funded; the trailer was garbage. But with the idea and him being who he was... in hindsight, that would have been awesome. We didn't hit the $10,000. We only got to $2,000 donated, so we didn't do it.
54:07	Sam Parr	So funny — oh my God. I mean, did he actually compare himself to Steve Jobs, or are you saying, like...? </FormattedResponse>
54:13	Shaan Puri	I don't remember what he said in the Kickstarter part, but I think he's not comparing himself. He's just trying to get you excited about why you should care about this company you've never heard of. He's like, "Well, imagine if the great companies had had this at the beginning — you would have wanted that, right?"
54:27	Sam Parr	"Oh my God, that's so funny."
54:29	Shaan Puri	He called a shot. He just didn't like—nobody cared.
54:33	Sam Parr	But yeah — I've talked about this. I love doing home movies, so I try to take a three-minute video of my family every day of us doing something. I keep them on a secret YouTube channel.
54:44	Shaan Puri	What's it called?
54:47	Sam Parr	Sam's super top-secret channel. Don't look—but all the videos are unlisted. You can even see them if you wanted to. Because a YouTube Short can be three minutes now, I do—I’m doing three minutes. The problem with a lot of these videos you take with your family or with your friends is they're just like ten seconds, and you're telling your friend, "Wait, repeat—hold on, do it again." Versus, like, "Here we are." Remember when you're a kid and your dad's like, "Here we are—Christmas morning, it's 2004. Yeah, we're doing this." Those are the best videos. So, thank God we have these phones, because that's really what a video should be: a three- to five-minute video of someone narrating, saying what's going on, and no one's performing. Versus now—whenever I pull my phone out it's always like, "Wait, hold on, tell me that joke again. How do you feel? Yeah, like, are you..."
55:38	Shaan Puri	So I definitely land on the optimistic side. I think he's a badass and I loved hearing his story. I think it's super mission-driven. It's super cool that these guys believed twenty years before anybody else, and it's super cool they filmed the thing. I like the breakthroughs they're doing. I like seeing use of AI that's not all the same. Today the ChatGPT experience is so dominant that it feels like that's what AI is. It's kind of like the early internet—getting online and being like AIM or AOL News and saying, "this is the internet"—but no, there's so much more that's going to come. That's how I felt when I heard more about the protein-folding stuff and how they did the game stuff, and how that's going to apply to all these other domains. I walked away thinking: if I were young and trying to figure things out—if you're high potential and you don't know where to go—I got two words that will probably make you a billion dollars: computational biology. Just go there and play around. If you're an entrepreneur, forget building a GPT wrapper. Build an AlphaFold wrapper. I think you could build a multibillion-dollar company. Like what Cursor did: Cursor basically said they didn't make the model, they said, "We'll take Claude but we'll just wrap this in a tool that programmers can use," and that was very useful for programmers. Go do that for pharmaceutical companies. Go do that for research labs. You realize that with protein folding, people are going to want to test proteins—the actual protein synthesis in the real world. That demand is going to go up 100x. Go create wet labs and just do the tests for the people who are using computers to come up with their hypotheses. That demand is going to go 1,000x. Man, there's so much opportunity for anybody who wants it.
57:17	Sam Parr	I got two words for you. I thought it was gonna be like "suck it," but it was "computational biology." You—you led me down a path I thought you were going one way, not the other. That was great. This was a great episode. All right, that's it. That's the pie.

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The Most Important Founder You've Never Heard Of

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