Story Of The Most Important Founder You've Never Heard Of

22:30If you want to read the whole book instead of just reading part of it, visit HubSpot.com. Okay, little segue. Have you ever seen the Tony Robbins TED Talk he gave? Yeah, probably. I've seen many of his talks. So Tony's normal talk, like his seminar, is like a four-day, 12 hours a day on stage thing. So TED Talk is 18 minutes. So he gets on stage. He's like, all right, I usually talk for 12 hours at a time. Let's see what I can do in 18 minutes. And he gets to this point in the talk and he's like, what stops us from getting what we want? And then people are like, I don't, he goes, I don't have the, and people are like, time.

23:02He'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, and he writes all these resources that you lack down. And then one guy in the crowd goes, I didn't have the Supreme Court justices. And he looks through the darkness. He's like, who said that? And it was Al Gore. Yeah, Al Gore. It was Al Gore who had just lost the presidential election. I remember in Florida, there was a recount and the justice, he was like two justices is short or something like that. And everybody has a big laugh. And then Tony says, he goes, you know, I don't think that's why you lost because I saw you yesterday on this Ted stage talking about climate change.

23:40You know, Gore's like super passionate about climate change. He was like one of the big advocates for climate change. And he goes, if you had done, if you had talked like that in your presidential debates, you would have never needed the Supreme Court justices. You were on fire yesterday. I didn't see that when you were debating Bush. And he basically says, he goes, 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 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 am like motivated enough, I'm persistent enough, can I not achieve anything I want?

24:17Can I not overcome all those things that I lacked? It's like, of course, like you didn't have the resources, you didn't have the money. Well, 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. And so I find my, I often, I actually catch myself doing this all the time where I feel like I lack something and I'll literally go say that almost like an affirmation. Like, well, if I'm playful enough and I'm determined enough and I'm charismatic enough and I'm persuasive enough and I'm determined enough, like, can I not, can I not get this thing I want?

24:45Of course I can. Like, oh, they're closed. I could probably get them to open. Oh, this guy said no. I could probably get him to say yes. Right? And then like each one of those things, that's like, just like this universal skill we all have if you remind yourself. That's pretty badass. And I don't even think you need to be charming. This guy Demis, 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. He is what Paul Graham calls a fierce nerd. I think that fierce nerd essay is actually Hall of Fame level for Paul Graham. And you see it, when you see somebody like Demis and how competitive he is with foosball and chess.

25:22And then he's also that way with trying to win the protein folding problem. All right, back to the story. So they're sitting there with the best Korean Go player in the world, Lee Sedol. And there's this move, Move 37. And 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, you know, in a rom-com, it's when the guy bumps into the girl and she drops her papers on the ground then they pick him up and they look each other in the eyes. It's like the spark. This is the spark of like where AI really took off. And it's Move 37.

26:01So basically they're playing Lisa Dole. The expectation is Lisa Dole will win because Go is so hard and he's the best. But we'll put up a good showing. We'll be as good as the best players against Lisa Dole. And in Move 37 the computer does something and right away the announcers are like oh my. Oh what is that? And Lisa Dole you can literally, they show him like sweating and thinking. And he's like, what the hell just happened? They go, and they go, I think we might've just seen an original move by AlphaGo. And LisaDol is like, just, he doesn't know what to do. He's like really perplexed by this move.

26:36They go, no human would have made that move. And it was the first time that it wasn't just pattern matching. Let's mimic what a human would do or say, but less good than a human would say or do it. Or maybe it's a little bit faster because it's a computer, but it's still doing what a human would do. It was the first time it was like, that was novel. That was a creative breakthrough. And it beats Lisa Dole. It's like when in a horror movie, like the robot turns to you and says, I'm in charge now. Like this is that moment. Exactly. And so I had never actually seen the clip. And the way the movie shows it, I think is wonderful.

27:11So then right afterwards, Eric Schmidt's like, holy shit. And he goes to Demis and he goes, what's next? Where does this end? and he goes, when we beat the Chinese guy. I didn't even know about this part. It's like, then there was a Chinese guy who was the actual number one ranked player in the world. They go to China to play this guy. And now it's like, what's going to happen? This computer just beat Lisa at all. Can it beat the Chinese guy? And I just love that they even called him the Chinese guy. It was like the most relatable thing that this absolute super genius with like a 10 ,000 IQ said.

27:41I was like, oh, he's just like me. He would just call him the Chinese guy. Like that was cool. And so they go and they play. Had you ever heard about this? No. So I just, if you go on YouTube and type in Move 37, there's videos with hundreds of thousands and millions of views. And it's all like, for example, retelling the story of Move 37. Or there's Magnus Carlsen talking about like how Move 37 teaches you about X, Y, Z. Like it's become like an acronym or like an analogy for like, you know, when this will find a mile, right? Yeah, exactly. It's like, exactly what it is, a four minute mile. Like it's just a phrase that doesn't even mean Move 37 anymore.

28:16it's grown beyond that. Totally, totally. I see your little public speaking brain is picking up on all these little, you know, magic, the magic of tiny words, huh? Thanks, Dale. Thanks, Dale. Thanks to our guest today, Dale Carnegie. Thank you. Okay, so then it goes to, they play the Chinese guy. Now, 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 player in the world. Is the Chinese guy just smoking cigs while he's doing this? Because that's why I met. He's actually a pretty young looking guy. But the crazy thing is, as he starts to put the pressure on the Chinese guy, they cut the feed in China.

28:54No way, really? How badass is that? They cut the feed of the broadcaster. They're like, no, we will not show. We will not lose face like this. And they call that in the movie. They're like, this is like the Sputnik moment where China was like, wake up call. We're getting into AI. And so this actually triggered the AI race for why China got so into it and how they cut the feed so dramatic. I thought that was incredible. That's crazy. Okay, awesome. Okay, so then they go, they continue with games. Let's fast forward. They do StarCraft next, which StarCraft's interesting just from a, why StarCraft?

29:23Because both players are playing at the same time. So it's not turn by turn. Is StarCraft like a fighting game? I don't know what it is. Yeah, I think it's called like a MOBA or whatever. It's like basically a game where, you know, you have a map. Got it. It's like Grand Theft Auto a little bit, but... You have a base. They have a base. You got to attack their base with characters. You got to 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 you're acting like you don't know what you're talking about I don't play that but anyway so there's this big character, here's what he does I don't play Starcraft but you know I've been around enough dorks to know alright so it doesn't actually beat the best Starcraft player in the world that guy wins, okay but it was a good showing anyways then I think what's just what's the next step, what's the next step 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?

30:13All I know is that no one had ever solved it. And basically within days or weeks or something like that, they solved something that took 50 years to get up to that point in progress. Actually, it took years, which is cool. I didn't actually realize this. So Demis is basically talking about, they're like, all right, we did good in games. But he's like, before AGI, he's basically like, AI-assisted science is going to be the thing. And I don't think this gets talked about very much nowadays. like maybe AI could cure cancer. But this guy is seriously like, no, AI should cure cancer and all disease.

30:45It's not clear how math can, or math or that type of like - How chat GPT cures cancer. It's like, that link seems very broad. Why do you need more data and more effort? Like, it's as if like 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 like soup up the drug and throw it 550 more times. You know, that's sort of how in your head you think cure cancer. They're not like, can you math your way out of it? Correct. Now, what I've realized in watching this and hanging out with AI people is one of the most important things in the world is basically prediction.

31:18So I remember I invested in this guy who was a self-driving car entrepreneur. He had worked at the Uber self-driving car team and he took me to this little garage and he had this like golf cart. This was in like 2019 or 18, right? This was pre-pandemic. Even before that, maybe, yeah. I remember, I met him. That was probably the time. It was right before I started my phone. So 2018, 2019, you're right. And he drove me around in a self-driving golf cart in a self-storage facility. So it's like, you get a peek of the future. Like, whoa, that was amazing. This is, you know, before Tesla had it and whatever.

31:51But like, you know, it wasn't perfect. You could only do it in a very controlled environment. But he basically said like, look, everybody's working on this knows there's these like four or five steps of self-driving. And I didn't, I don't remember all of them, but one was like, you know, so it's basically like vision. So you got to see the world. Then, based on what you see, the next step is prediction. So, okay, I saw that 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 like basis of self-driving is planning, prediction. There's like an action step or whatever.

32:20There's like five steps. So that kind of planning and prediction step is the key to how AI affects all these industries. So, ChatGPT is planning and prediction of what is the next token, or let's use word. What's the next word that would probably go in this sentence? You know, the roses are red. I think it's going to be red because I've seen roses are red so many times that my prediction score very confidently would say the next word in the roses are is red. Okay, great. How do self-driving cars work? Same thing. If I see a car there, my prediction is it's going to be here in the next one second.

32:55So therefore, I need to do a new action. The same thing applies to science and curing all these diseases, which is you need to know what a protein structure looks like. based on the shape of the protein structure, you can then, if you can predict the protein structure, then it's not so hard to figure out what should you attach to it to either like destroy that protein or soup it up and make it more strong or whatever, right? You know where to bind on the protein. Okay, so I didn't know about this thing, but it's called CASP. So CASP is this competition that had been going on for years. And it's basically the Olympics of protein folding.

33:30So if you do like a sequence, you're like amino acids. It's, oh, it's got this amino acid, this amino acid, this amino acid. You get just 10 amino acids. Cool, you know what's in it, but you don't know what it looks like, okay? You don't know the structure of how it's folded up into this like little tiny knot, a very unique structure. When you say folding, figure out the shape of the knot. The shape of it. And you need to know the shape in order for what? To design a drug that's going to do anything to it. So you could kill it or grow it or shrink it. Like imagine I said, hey, you're going to park this car at this address.

34:01Cool. but if you don't know what the garage looks like you're just going to smash into the house right like you might know the location of it but you don't know where to park the car so how do you park the drug that's going to attack this that's going to either kill it or enhance it you need to know what the shape of it so the way they do is one by one so they create this competition to be like can anyone use computers to predict the protein folding because doing this manually is untenable and for years if you look at the graph it was like you know like kind of this like 20 % 30 % prediction accuracy for like a decade.

34:33So Demis decides, he's like, this is what we're going to do. We're going to throw our resources behind this. And the first time they do it, they win the competition, but they're like, great. We're trying to go to the moon and we just have like the tallest ladder. The ladder doesn't get you to the moon. And so they were actually incredibly disappointed. And he's like, this was like a bitter taste of we really tried. We won, but not by enough to even solve the protein. We're like, we're here to solve the protein folding problem, not win the competition. And to solve it, you need 90 % plus accuracy.

35:06And he describes this like the next year where they basically are like, so we went back to the drawing board, try to come up with new ideas. And I thought there was a cool CEO moment. So he was like, I know when you need to come up with a creative idea, you can't force it. Like squeezing it doesn't make creativity come out when you just push the team. We need an answer now. Like that's not going to get the best idea. 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. So they used constraints, but what they didn't do was basically like put everybody into fight or flight mode.

35:41Because when you're in fight or flight, it's kind of like why your best ideas come to you when you're in the shower or when you're relaxed or when you're in your sleep or when you're on a walk. Because the brain, like you have two modes. One is executive mode where you're doing tasks. And that's good at doing tasks, but it's not good at making new connections between existing fuzzy data. Dude, that's so interesting because this is how Henry Ford, so Henry Ford, one of the things, basically there's an engine block. So it's a block of metal and you put cylinders in there and that's how a combustible engine works.

36:13But before that was one block, it used to be two blocks and it kept breaking. Imagine two blocks and screwed things together and it was holding them back from taking over the world. Henry Ford got a team of four engineers of the company of thousands of people. And he goes, the story is that he brought them to a small office. He goes, this is you guys' workshop. And they're like, what are we doing? He's like, you see that big ass block of metal? Figure out how to put four holes in there and four pistons and make it work. And they're like, Henry, sir, that's impossible. He goes, I'll see you guys at a quarter.

36:44And apparently the story is, is that he went back like eight quarters in a row. So it was something like two years. And then finally they got it, but 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. Exactly. And this is also how, if you read about like Steve Jobs with the, he was like, no keyboard on the phone. And they're like, but the BlackBerry, you know, keyboard, like you got to write emails. He's like, no keyboard on the phone. And they're like, but how would we, the accuracy, I mean, screens today don't, he's like, no keyboard on the phone.

37:15And so then they had to go invent multi-touch and figure it out. So he gave them the constraint, you got to do it in this, These are the constraints. But then I give you the time to go explore and figure out like which path might work. That's interesting. And they also did this with the game thing, by the way. When they did the Go thing, the first one was, again, train 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 going to do new novel things, you got to assume we were not going to have a database of 100 ,000 good humans at doing this to use.

37:47And so they did. They created AlphaZero, which could win in chess and Go. just by playing itself like 10 million times or whatever. It figured it out. And so similarly here, they were like, you got to go back to the drawing board. And he described, he goes, first, I'm going to give them the constraint. Second, I'm going to let them be creative and try to go to the drawing board, figure out multiple different possible ways this might work. He goes, and then when they pick one, he goes, 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.

38:21He goes, and that's when it's time to push. I've seen it so many times before, and we'll explode through. 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 do you push and when do you not push. Dude, that's so great. We're learning all these techniques and I'm putting it all together. Hermosi had this cool thing that 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, their conversion rate is actually going to drop from 50 % down to, you know, it'll drop 20%, so down 10 points.

38:57But eventually it will go up if you pick the right thing. And so the question is basically make sure you pick the right thing because if it's going to go down 20%, that means you need it to double its improvement in order for it to be worth it. So you pick the right thing. Otherwise, you're just back to square one and you went down 20 % for a quarter. Right. And so knowing that these J-curve progress things exist is important because the amateur would panic. The amateur would not go forward. That was actually my biggest learning this year, running a company. It was like, expect new things to suck or bring everything down.

39:29Therefore, make your project selection perfect or high quality. Right. And so he, anyways, they end up crushing the thing and they show kind of like how they did it. They end up getting 90 % prediction accuracy and they basically solve the single protein folding question. Now there's also like multi-protein and there's like variations and there's like all these other, now they moved on to harder things. But it's pretty crazy that the line graph was like, you know, 20, 30%, 23%. And then it went to 90 in one year when they like went back to the drawing board and figured it out. And how ecstatic they were.

40:03They're like, you know, this just changed the world. People don't realize this yet, but this just changed the world. And it's reminded me of your inflections thing, which you should say, what is your, describe your inflections thing for entrepreneur. I think it's one of the best like axioms or principles you have on entrepreneurship. ship. Yeah, basically. And I didn't invent this. I think it was Maples, Mike Maples, I think. 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.

40:36And so there's a handful of inflections that matter. There could be regulatory inflections. So during COVID, BetterHelp and all these telemedicine things existed because we changed the rules on who doctors can serve. It could be cultural inflection. So 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 that had GPS on their phone. Therefore, they could call an Uber wherever they were. And there's 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 culture-changing company to exist.

41:16And so I think this, I think this alpha fold stuff where figuring out the protein folding is a massive inflection. And I didn't really know what the businesses were around this, but I kind of like Googled afterwards. I was talking to Grock and asking it about this. So there's some pretty cool companies. I didn't realize, first of all, Google has their own company they spun out from this. So isomorphic lab. So basically Google has spun out this company that is basically trying to cure all disease. That's the mission. No big deal. and their thought process is like, well, with AI, we can, you know, from first principles change the way that drug development and discovery works.

41:52Because if we can predict how the proteins fold, then we can have a way higher hit rate on the targets we designed with the drugs. Then we should be able to simulate if it's going to work with it. Before we even get to clinical trials, we should be able to run, you know, hundreds of thousands of simulations to see how effective this can be, get the probability of success higher. So that when we enter a trial, We have a way higher hit rate. And this company, by the way, their first round of funding was$600 million as they spun it out of Google and DeepMind. And Demis is the CEO, I think, of Isomorphic Labs.

42:26And so there's a world where Google becomes the drug company that cures. Like right now, they're working on malaria and these different things. Is he the CEO of DeepMind as well? Yeah. Wow. The H1 on isomorphiclabs.com, the headline is 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. If I was doing a Sarah's List episode right now, Isomorphic Labs would be one of those where I'd be like, go be a PR person there. Go be a junior account manager there. Yeah, does the cafeteria workers, yeah, you guys have a cafeteria?

43:02You literally show up and you 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, whether it's in any job you have, I need to be at this company. Because I can't think of, you know, how many companies have a more noble mission, but actually a shot of cracking it because there's a new tech vector to go chase. So how does the documentary, like where does he leave it? The end is weird because it's actually like the beginning, they're still in the beginning stages of what they're doing, right? So it's like they end the documentary, but it's like the AI stuff is just starting to work.

43:39So they end it with, after the alpha fold thing, people, like all these, like it was a big thing in the science community. And so all these researchers and drug companies were like, hey, can we get access to this? Because if we know protein structures, this will be tremendously helpful. So they're like, oh, we should set up like a service where you can request a protein. And then we tell you how it's folded and then blah, blah, blah. And then Dennis was like, can we just fold all the proteins? And they're like, what? And he's like, how long would it take to fold all proteins known in existence?

44:09And they're like, I'm going to do that in like two months. He's like, well, why don't we do that? Let's fold them and give it all away. And he's like, let's just make it open for anybody. Let's go run the computer, fold all the proteins, give it all away. And so that's what they did at the end. They folded 200 million plus, basically every known protein in existence. And they made it available. And the end is basically like researchers from around the world showing up on their Google Analytics, like logging in. They're like, we have 100 ,000 concurrent users. We have, you know, they now have 3 million users.

44:38and that's everyone from like someone in Africa running a small lab to universities to Eli Lilly who are all using them to be smarter and better about how they do medicine. Dude, how are all the guys who work at isomorphic labs and DeepMind and Denimus, how are they all not like Andrew Tate looking dudes, like the most tan, like Jack dudes ever? Because like if you can cure - Taking peptides? If you can cure all disease, Like, how are they not like the hottest people on earth? I think the way you become that smart is you don't care about stuff like that. Right? No, you become that smart because you are bullied.

45:18But now you're going to seek revenge. And the issue with bullying going away is that none of these nerds are going to exist. You know what I mean? It's like, I know we're getting close when Demis is 6 '4 and has visible lats. Yeah, why does he not look like Adonis? That's my question. I think when Larry, I don't pay attention to the news too much, but when Larry Ellison and Masa's son and Trump and Altman did this thing where it was like, you know,$100 trillion or some ludicrous number, it was under the premise of like, this is going to cure disease. And Larry Ellison, I do know that Larry Ellison's in his 80s, I think, or close.

46:01Looking good, Larry. Close too. And he's looking great. And his wife is like a 30-year-old. But for some reason, they don't look like that much of a different age, even though there is literally a 50-year difference. And it was under the premise of Larry's interested in solving death, and therefore we must do that. Whenever I hear that, I just think that's just words that are meaningless. But now that I know a little bit more about the topic just from you now, is that actually a legitimate thing? Well, I'm glad you're asking me, because as a pre-med student, I'm clearly an expert of this. No, it's hard to know.

46:32As someone who took one class on this 15 years ago. Somebody got a C in physics, had to repeat in the summer. It's like on Instagram when people report, like you see like Instagram videos of people with their children and like the kids like on an iPad are screaming and someone's like, well, as a mother, I could never, it's like, dude, you mean as a human being? Like, I don't care, okay? You don't, as a mother does not mean that you are right. shots fired but mom not special yeah as a as a father like brother i everyone's a father okay i don't care there's a line where they're talking to like one of the ogs of artificial intelligence and they were saying like you know what are your predictions and he goes it's hard to predict what's going to happen as we make this intelligence into super intelligence he goes it's like asking a gorilla to explain Einstein's theory of relativity.

47:28And when I heard that, I go, oh yeah, we're going to be the gorillas out of this whole thing, right? Because clearly, if you're making intelligence smarter than any human, you're creating the next race. It's like, to an animal, if they just saw a human at first, they'd be like, yeah, it looks kind of skinny. They got a little funny little extra appendage on their hand. You know, all right, cool. They walk up right. Oh, cool. But they're pretty slow, actually. And then you're like, fast forward, you know, 200 years. And, you know, you see the blue angels flying above you. 200 years? Yeah, I don't know.

48:04No sense of time. 2 ,000 years maybe or 20, I don't know. Speaking of gorillas, we are a few brain cells away from gorillas. But just like what humans have done is like kind of incomprehensible to any, to our closest animal, you know, relative. That's what's going to happen here, which I think is pretty crazy. All right, let's take a quick break because I got to tell you a story. Let me tell you about the first time I tried to run payroll for my team. I was using a traditional bank and you know the type. It's got a janky interface. It's built like a 2002 tax form and it was open only during business hours.

48:35And I hit send and it froze. They flagged the transaction. They locked my account. They put me on hold for 45 minutes. And then they told me I got to visit my local branch. And that was the day I started looking for a new bank solution. After asking a few founders what they were using, I found out about Mercury. And so now my payroll is two clicks. I can wire money. I can pay invoices. I can reimburse the team all from one clean dashboard. That's why I use it for all of my companies. And so do 200 ,000 other startup founders. And so if you're looking to level up your banking, head to Mercury.com and apply in minutes.

49:04Mercury is a financial technology company, not a bank. Banking services are provided through Choice Financial Group, Column N.A., and Evolve Bank & Trust members FDIC. I don't know if you listen to Mark Manson. He's the man. Basically, he wrote this. He did a podcast. I think it was his second most recent one. It's about it's a Q &A, maybe. Finding Your Purpose, Failing Better, and the AI Future. So it was basically like an end-of-the-year Q &A, which we actually did as well. And he tells a story about how he built an AI product recently. And so someone asked him, what do you think about the future of AI?

49:34And he was like, well, I just built an AI product. And I realized a few things. One, AI is amazing in that 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 99.9 % better at people than human things. You still need these experts. And AI can be great, but it's not an expert. But then he also said, there's maximalists who think that AI is going to come really soon and take over the world and we're all going to be worthless. And there's other people who think that it might happen over many decades, but we're probably going to be fine.

50:06And he was like, I tend to be in that category. And the reason being is that when a lot of people think about AI, they think that it's just going to take all of our jobs and we're not going to work anymore. but human desire is not fixed. And when you're thinking about AI, oftentimes people think desire is fixed, meaning once you hit a certain level of productivity, you will not do stuff. And he's like, that's just false. For example, if we look at the Industrial Revolution, people said the same thing when certain stuff started happening. And then you look at like the Victorian area where we started getting electricity, things like that, people made the same claim of, we're not going to work again.

50:39We need universal income and all this stuff. And he's like, humans just always want more. and because of that, I don't think that there's ever going to be a point where we are useless. It's just going to be different and I thought that was a really great perspective on it and 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 is not fixed, we will evolve. 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.

51:11I don't think I'm going to be reading that one. Yeah, yeah. I mean, it's a crazy documentary. And I think, you know, my meta takeaway is I love that they were filming this the whole time. I'm glad that smartphones and video and these video platforms are so popular now because imagine 10 years from now, I think we're going to have 10 times the number of like documentary behind the scenes, building it type of things. Right now, it feels like a fluke whenever this happens. For example, we did a podcast about the Kanye documentary. and the craziest thing about the Kanye documentary is not about Kanye.

51:46It's about the guy who just decided, you know what? I'm going to just film this young guy in Chicago over a 10-year period because I think he's got something here, which is like one of the greatest calls ever. Before Kanye was Kanye, this guy started filming and I think we were lucky that that ever happened. That's like a lottery ticket level win for society that that guy just decided to film this religiously when there was no reason to believe that he should do that. Conor McGregor did this on his way up, and he's like, I'm going to be the best. You know, like, yeah, I'm a plumber now, and there's never been an Irish champion, but I'm going to do it.

52:23And he basically started filming a documentary. And because of that, 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 that they did this, and I hope more people do this. That was my big picture takeaway. It was really not even about DeepMind itself. And that, I was going to say that, that the need for human craft goods. So for example, you could buy anything you want, but some people still want the handmade shit from Italy and they want to know the story behind it. And when you're talking about the story about him playing the Chinese guy and the Korean guy, like there's still, a human is half of the story.

53:03And arguably, I mean, not arguably, it is necessary to the story. We are still drawn to stories. and story is in my head is sort of an analogy to like where humans fit into this thing. We're still drawn to these like human elements of all of these stories, which makes me believe like, well, we have to be part of this experience and like, we're not going to be completely outsourced because it's what the most interesting part is that this genius guy has called his shop this whole time and has been interested in this for years. Like that's actually the most compelling part. Yeah. Yeah. Although, you know, I think you don't want to be relegated to like, well, we'll still make handmade goods.

53:38it's like that's the 1%, 99 % is the mass manufactured things. You also don't want it to be where, well, we'll always be interested in human entertainment and it's like, but everything else will be done by the AI. No, but I don't mean that. But I mean like... You know, like 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 like run by a computer that's way safer than a pilot. Great. I'm glad there is a pilot, but like the computer could fly. But I just think that I'm not, I mean, part of me is nervous, but I do like, well, a big part of me is actually nervous.

54:10Most of me. It's like when people say, well, some people say it's not that big of a deal. Most don't. Few people got their head in the sand. 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. There's also this funny thing that happened on the documentary point. Did you see the founder of Robinhood talking about his documentary? No. What'd he say? So I didn't know this. Vlad from Robinhood, when Robinhood was getting started, he put up a Kickstarter saying, hey, I'm going to try to build this company that's going to change the way the financial markets work.

54:55And if you guys fund$10 ,000, we'll film it. Because how cool would it be to see Steve Jobs building Apple? How cool would it be to set a scene, you know, these guys building Google? Like, that's what we're going to do. And then it didn't hit its Kickstarter goal, and they didn't do it. Isn't that crazy? The Kickstarter project's still up. You can see the trailer. By the way, I can see why it didn't get funded. The trailer was garbage. But the idea and him being like, he's like, yeah, in hindsight, that was right. That would have been awesome. But we didn't hit the 10K. We only got to$2 ,000 donated, so we didn't do it.

55:26So funny. Oh, my God. I mean, did he actually compare himself to Steve Jobs? Or was he saying like… I don't remember what he said. In the Kickstarter, but I think he's not comparing himself. He's just kind of like trying to get you excited about why should you care about this company you've never heard of? And he's like, well, imagine if the great companies had had this at the beginning. You would have wanted that, right? You know? Oh, my God. That's so funny. He called his shot. He just didn't like nobody cared. But yeah, but think like I've talked about this. I love doing home movies. So I try to like every day I take like a three-minute video of my family of us doing something and I have it on like a secret YouTube channel.

56:03What's it called? Sam's Super Stop Secret channel, don't look.

56:11But all the videos are unlisted. You can even see if you wanted to. But because a YouTube short can be three minutes now. And so I'm doing three. Because the problem with a lot of these videos that you take with your family or with your friends, they're just like 10 seconds. And you're like telling your friend like, wait, repeat, hold on, do it again. Versus like, here we are. Like, remember when you're a kid and your dad's like, here we are, Christmas morning. 2004. We're doing this. And those are the best. Those are the best videos. And so thank God, like we have these phones because that's really what a video should be.

56:42It's like a three minute to five minute video of someone narrating, saying what's going on. And you're not, 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? Are you? 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. I think it's super cool that these guys believe 20 years before anybody else. I think it's super cool they filmed the thing. I think the breakthroughs they're doing. I like seeing use of AI that's not all the same, which is like today the ChatTP, the ChatTPT experience is so dominant that it feels like that's what AI is.

57:23And it's kind of like early internet, like getting online and being like, AIM or AWOL News, like this is the internet. and it's like, no, dude, 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. And I walked away being like, oh, man, if I was kind of young and just trying to figure things out, if you're high potential and you don't know where to go, like I got two words that'll probably make you a billion dollars. Computational biology. Just go there and just go play around.

57:54If you're an entrepreneur, like forget building a GPT wrapper, build an alpha fold wrapper. I think you could build a multi-billion dollar, like what Cursor did. Cursor basically said, they didn't make the model. They were like, we'll take Claude, but we'll just wrap this in a tool that programmers can use that will be very useful for programmers. Go do that for pharmaceutical companies. Go do that for research labs. Go create, or you realize that with protein folding, people are going to want to test protein, like the actual protein synthesis in the real world. That demand is going to go up 100x.

58:25Go 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. I was like, man, there's so much opportunity for anybody who wants it. I got two words for you. I thought it was going to be like, suck it, but it was computational biology. You led me down a path. I thought you were going one way, not the other way. That was great. This was a great episode. All right, that's it. That's the pod. I feel like I can rule the world. I know I could be what I want to. I put my all in it like no days off. On the road, let's travel, never looking back.

59:04All right, my friends, I have a new podcast for you guys to check out. It's called Content is Profit, and it's hosted by Luis and Fonzie Cameo. After years of building content teams and frameworks for companies like Red Bull and Orange Theory Fitness, Luis and Fonzie are on a mission to bridge the gap between content and revenue. In each episode, you're going to hear from top entrepreneurs and creators, and you're going to hear them share their secrets and strategies to turn their content into profit. So you can check out Content is Profit wherever you get your podcasts.