#870: Sebastian Mallaby, Biographer of Demis Hassabis — Lessons from 100+ AI Insiders on The Race to Superintelligence, The Religion of AI, and Spotting Breakthroughs Early

0:00 Uh boy. Hello, boys and girls, ladies and chairs. This is Tim Ferris. Welcome to another episode of the Tim Ferris Show, where it is my job to re-record my intro seven million times every time I do an episode. Just kidding. It's my job to interview world class performers and the people who study world class performers. My guest today is one of my favorite nonfiction authors, Sebastian. Maliby. He is the Paul A. Volker Senior Fellow for International Economics at the Council on Foreign Relations, a two time Pulitzer Prize finalist, and the author of six books. Including more money than God. Love it. The power law. Love it. The man who knew.

0:38 And the world's banker, I've not read the latter two. Previously a columnist at the Washington Post and The Economist, Sebastian now co-hosts the CFR podcast, CFR is Council on Foreign Relations podcast, The Spillover, which examines the ripple effects of global events across policy, geopolitics, economics, finance, and technology. His latest book is The Infinity Machine, Demis Hasabas, Deep Mind, and The Quest for Superintelligence. And in this conversation we get into a lot. We get into his op ed's Different. Predictions I would hesitate to call them, observations.

1:12 of the AI ecosystem, how we actually timed it to get started. before the launch of GPT three point five. And much more. You can find Sebastian on X. At S C Mali. So that's S C

1:29 M A L L A B Y And uh you can find him on social very, very easily. Sebastian Maliby And with all that said, please enjoy A very, very broad conversation about AI, China. Competition.

1:42 Open AI. Anthropic. Google slash alphabet and much more. At this altitude, I can run flat out for a half mile before my hands start shaking. Can I ask you a personal question? No, it's in the case. A cybernetic organism, living tissue over metal entercts.

2:11 Sebastian, lovely to see you and thanks for making the time. I really appreciate it. Great to be with you, Tim. I wanted to just Give you Applause for writing some of my favorite books of the last

2:26 Many years. I Um Consistently Impressed. And maybe

2:33 Since I also put pen to paper every once in a while, depressed, just thinking relatively about my capabilities. But of your capacity to Paint a picture of the players on a landscape. But also the games they play in ways that non-specialists can understand. And I can't recall who first recommended it. Frankly, I believe it was a hedge fund manager in New York City, but more money than God hedge funds in the making of a new elite. Certainly that

3:01 was in my particular case followed by reading the power law of venture capital in the making Which I didn't expect to learn as much from because I've spent twenty years surrounded by venture capitalists and doing angel investing, seventeen years of that. In Silicon Valley.

3:18 And yet. I still had hundreds of highlights. And so many stories. that grabbed me from that book, which I had not Heard.

3:27 And That made me very excited to read The Infinity Machine, which this is the new book. And I realized also I've been pronouncing Demis' name incorrectly for a very long time, despite having met him at one point. So Demis Hisabas, Deep Mind, and the Quest for Superintelligence. My question for you, and we're gonna come back to present day for people who are interested, of course. In what has been painted as a race. to IPO. I think there's something to that in the

3:56 air, so to speak, talking to people who are in San Francisco. involved with these companies. But Nundeless, I wanted to ask how The genes of This book came to be because you

4:11 It would appear began exploring. These waters. on the early side, which leads to a meta question of just general book selection, but let's focus on the infinity machine. How did this come to be. Where did the twinkle in the eye begin? What was the conversation, the thing you read? That triggered.

4:30 the gingerbread trail that got you to this book. The power law, the book about venture capital, had come out in February of twenty twenty two. And While I was researching that, I'd been to lots of tech conferences, of course, including some in Europe. And this twinkly eyed

4:47 Guy would show up. Then it's the Sabus. And he would look totally approachable and kind of guy next door and unintimidating. And then he would get on the stage. And out of his mouth would come this spiel about

5:01 Computer science, neuroscience, chemistry, biology, physics, philosophy, the history of movies. You name it. And that Mixture of the approachability And the massive intellect.

5:14 Always struck me as beguiling. And I thought Hm. This would be a great character to write about. And then at the same time You know, I was aware of uh for go the twenty sixteen model. The Demesis teammate.

5:27 Deep Mind had built, which defeated the world champion at Go. And then Alpha Fold. which was the protein folding system and Both of these things had the quality that You had this almost infinite search space.

5:40 Where the different permutations of the game of go are almost infinite'cause they're so big. There are different permutations of how you can fold an amino acid chain. Into a protein shape. Alright.

5:53 Even bigger. A hundred and thirty zeros. Add it onto the end of the number of permutations in go. So you have this AI systems that could understand infinity.

6:03 So this idea of an infinity machine began to percolate and I figured It's interesting to me. Probably at some point it will go mainstream. But even if it doesn't go mainstream, I love it. And I love Demis. And the two things together, I always look for the

6:18 Subject. And the Personality. I had both and I thought, Okay, this is a go and I When to pitch them is

6:25 in early November twenty twenty two. And then, you know, I persuaded him to give me a lot of access, end of November, Chat G PT comes out. And way earlier than I expected, my fringe subject went to the mainstream. Proving. Tim, that it's better to be lucky than smart.

6:43 on my new venture capital firm.

6:50 Muggle thesis capital is what I'm calling it. What did it take to be Deeply. interested in the subject matter to find Dem is compelling.

7:03 And then to pitch him on a book because your books are so deeply researched. And part of the reason for my very uh long praise earlier is that you're very, very good. One of the best at taking incredibly complex Subjects or concepts transformer architecture could be one example. From the current book.

7:24 And Laying them out in terms that are both intelligible to muggles, meaning people who are non specialists, non technologists. Or non financiers in the case of some of your other books. While I think now it's tough for a non specialist to say this with conviction, but without dumbing it down and getting it wrong.

7:45 If that makes sense. Netheless, you do a tremendous amount of research. How did you get from Demis is fascinating. Subject matter is fascinating too. I'm gonna commit to this. For my next book. Because it just seems like such an enormous undertaking.

8:00 Well actually to me the Challenge of understanding a complex topic is the easy bit. Because If you know you've got the right personality who can carry the story and it's a subject that people either will care about for sure or should care about.

8:16 At least. Then Doing the work of going deep. is something that takes time, it takes effort. I know I can do that. I've done it multiple times. That's not difficult. What's difficult is Has somebody done the book before?

8:28 Has somebody else got some rival project which is gonna derail me? You've made the point on your own Podcast Tim. Don't put a lot of effort. Into something.

8:40 Where there just isn't much leverage there. You know, you could do the best book in the world An A plus book on a C minus topic. It will get you nowhere. So the hard thing is to make sure it's an A plus topic. And an A plus personality. And then

8:53 The deep dive is something Yeah, I just Make sure I speak to enough. Experts who are insiders. I take the time these books take me

9:02 Four years or so each time. So I give myself the oxygen. T. Get deep, deep in with the insiders, and that's how I Produce the accurate account.

9:13 Yeah. Point out. Perhaps to people who don't immediately pick it up, the the way you Describe picking. The book topic is exactly how a lot of the best tech investors choose startups.

9:26 You don't want an A plus team and a C plus. market. Right. It's better to have a B minus team and an A plus market. Right. And also looking at the competitive landscape. I mean the way you laid it out is pretty much copy and paste. I wanted to segue to some of my notes from the book. And I'm not yet done with the book. The audio is incredible. I want to poach your narrator for my next book.

9:51 But Pulling up my Kindle notes, I wanted to ask you. Question related to This might sound very strange, but where divinity or God fits into

10:03 The pursuit. or development of superintelligence for different players in the space, if it does. And The reason I bring that up is that religion does recur in the book. Both in the personal story.

10:17 Of Demis, but elsewhere. And it shows up repeatedly. In so much as I'll give you one example. The closest to Sabis had come to landing a real investor was an eccentric financier named David Gammon. I want to hear more about this guy also. The financiers seemed open to making this unusual bet, um alighting a few things because his motives

10:39 were themselves unusual. Quote There's a deeply religious aspect to A Gi Gammon explained to me later. It's really finding God's algorithm. I think It would seem, at least, chatting with people in Silicon Valley, that there are some who take it even further. Maybe this is how we find God. Maybe this is how we actually elicit the second coming. I mean, there's a lot there. I'm just wondering to what extent this has popped up in your research, whether it's reflected in the book. Or not.

11:06 Yeah, I mean, I think there's uh one basic thing going on here and I'm gonna take a slight detour, but it answers your question. Sure. What we're dealing with With A G I

11:17 powerful intelligence that rivals human cognition. Is something that's so powerful. That It's both. Exciting and scary and just hard to get your mind around. And so

11:29 If you look, for example, at the Two thousand nine. Speech that course the foundation of Deep Mind. This was Shane Leg, the Mista's co founder. Who gave a token two thousand nine.

11:41 But how superintelligence would arrive in twenty thirty. So unbelievably Spot on prediction. And Towards the end of that lecture, which is captured on a grainy video online.

11:52 You see him Pivot from explaining How algorithms are getting stronger, there's more data online. Computers getting more powerful, and so we're heading towards This intelligence explosion. And then he says

12:06 And it's going to be threatening. It's gonna do things we can't control. It's gonna be human level. It might challenge us. And as he says this, he has this sort of excited smile. On his face. You think, Well that's a bit strange, you know.

12:18 He's talking about potential doom. And he's smiling. And then somebody in the origin says, Wait, wait, wait. You've just told us Shane.

12:27 That This could be threatening to humanity. And you haven't provided any antidote. And surely you're gonna tell us how we're gonna stop it. At which point Shane turns around and says

12:39 How do we stop it? And he's kind of giggling. And you think, why are you laughing at this dangerous thing? And you realise that For humans to contemplate annihilation is absurd.

12:51 And the absurd is a close cousin of humor. And The reason I tell this story is that it's a springboard to the religion point, which is that This is such a hard thing to think about. That

13:04 People reach for religious terminology. When they're around AI. They just do it naturally. So, you know, there's this story about Ilya Satskeva, who was the chief scientist at Open AI. I talked to him a lot for this project. And there was a point when he was

13:20 At a retreat. With his fellow scientists. And They were gathered in the evening. Around a fire pit.

13:29 And he was talking about safety and he said, Okay, I want to explain to you We might have an AI that's dangerous. It wouldn't be aligned with us. So here's what we're gonna do with it, and you produce an effigy. Which was supposed to represent.

13:42 A malign AI. And he put it into the fire pit and he burnt it like a medieval cleric. Putting a witch to death. And so that's just one example of this religion. I'll give you another one. So

13:55 Demis one day was sitting with me in a park in North London. We would meet for two hours at a time and we would get deep into stuff. It was a Another picnic table next to us where two people are having a normal Quotidian conversation about Some friend of theirs had gone to hospital. And was she better, was she okay, et cetera, et cetera.

14:13 I was seated opposite Demis. Who had gone into this riff About how he reads scientific Papers. After his kids go to sleep in the evening from ten PM.

14:24 Until four AM. And as he's reading these papers, he says to me Reality is staring at me, screaming at me. Calling at me to understand it. And I have to understand it, and if I can understand it

14:37 It's like understanding nature better and therefore understanding the intelligence That might have created nature, and I will be closer to what I would call God. And so for him it's a kind of quasi. Spiritual quest. To build the artificial intelligence for Ilia.

14:53 It's a way of expressing the power of the artificial intelligence. There's The story of Levendusky, I forget his first name there, but the early, early engineer at what became Waymo later. Started a kind of church.

15:07 In worship of AI. Because AI is so omniscient. But it's kind of like a god. Mark Andreessen. Lampoons those who believe in sort of some

15:18 Ethereal second coming, a kind of rapture. where AI will, you know, will have a singularity. The AI will go vertical in its rate of improvement. And the whole world will change. And he likens that to Christian.

15:32 Kind of Messianism. So yes, all through this topic there is this religious expression. Because You know, religion is the lexicon. For dealing with something that we find

15:45 Too mysterious to really understand. This episode is brought to you by AG1, which I have taken for more than a decade. Man, it's coming up on close to 15 years, I would say. Longtime listeners have heard me call it my nutritional insurance. And that is exactly how I use it. The news today is they just launched AG One Pro. Designed for people focused on performance and longevity. I'll be traveling soon.

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18:43 After all of your Conversations. Research. Before the book, during the book. After the book.

18:51 Where do you land on the spectrum of Let's just say This this will bot bother Mark, but like Church of Andreessen. Techno Optimist. And there are there are others who are more exaggerated. But post AI, in the near term, we will live in a post scarcity world of superabundance and everyone will get a free car and we'll be free to

19:15 Crochet socks and play music and Read poetry all day and Basically we don't have to worry about anything because superintelligence will solve it all. There's that on one end. And then there's the You can imagine I don't won't go if it Into the

19:29 A belabored. description of the doomers, but you have the doomers for like the end is nigh. Here we go. It's not the second coming, it's the antichrist, and within short order we're gonna be Mad Max. Between those two, there's a lot, and I suspect you land between those two. But

19:45 Where do you land? In terms of assessing the promises and peril. Of AI and superintelligence as it stands right now. So look, I think any reasonable person should be both excited and a bit frightened.

20:00 And that's just the nature of it. It sounds contradictory, but actually that's the only rational Response. I think The superabundant story may turn out to be true. On a kind of longer view, let's say twenty, thirty, forty years. The problem is that in the

20:15 Path to get there. There's going to be a tremendous amount of disruption. And that's going to be politically quite difficult to navigate. I think a useful lens.

20:26 Through which to view this question is the China shock in trade. So in two thousand three or thereabouts You kept this enormous search of Chinese exports into the US and people lose their jobs in a very concentrated way. Certain industries just get wiped out. And for the first time.

20:44 In the history of economic study of the effects of trade, you actually see negative effects on workers. Before that it was kind of A bit of a myth.'Cause people adjust. They get displaced from one thing, but they move to a new thing. With the China Shark they didn't.

20:58 But If you look at the size of the China Shark. In a twelve period between nineteen ninety nine and twenty eleven The total number of jobs displaced. Wis

21:09 Two million. Which is actually a small number in a huge labour market like the US, where there's a lot of channel month to month anyway. And yet the political reaction against trade, against globalisation, in terms of a swing towards Protectionism, frankly, in both political parties. Was enormous.

21:26 So it shows you that a Small to medium shock. To the labour market? creates an enormous political consequence. So A fortiore with artificial intelligence.

21:38 You're gonna have a bigger shark. You can have a bigger political reaction. We're already seeing that in the polling around AI in the last two, three months. And so I think the superabundance thing, it may be true. But the path to get there

21:52 We have to talk about that as well. That's my sense on that side of the debate. I think On the Doom side of the debate. You know.

22:00 I'll give you my own personal journey on this. I began by thinking Of course. AI is going to be smarter than us. It already Pizza chess.

22:09 Since the nineteen nineties said go, since twenty sixteen. No, I can It's the bar exam, it can do PhD level math, all that stuff. Of course it's smart. But it doesn't have an incentive to attack us.

22:22 We are evolved as human beings to pass on our DNA, therefore we have to survive to do that. Machines Don't have DNA, they don't want to pass it on, and they don't want to survive. They have no reason to attack us. So I wander around for like the first year or two of this project feeling kind of

22:38 Comfortable and happy. And then one day I go visit Jeff Hinton, the academic father of deep learning, who lives in Toronto. And I sit in his kitchen. And I debate him on this because he's a doomer. I said no, Jeff. Why are you so depressed?

22:52 And he says okay. Here's a third experiment. You have an AI. It's very powerful. But you're worried that there's a Russian AI or a Chinese AI

23:01 It's gonna come and attack your AI. Now you, as a human, you're too slow and dumb. To know when that attack is coming. So you're gonna empower your own AI. To watch out for the attack.

23:13 And when the attack is coming defend yourself or maybe counterattack, whatever you do Make sure you survive. Who Survive. There you have it. Now are you feeling comfortable, Sebastian?

23:23 You've just given the machine a survival instinct. And I think that's correct. You know, these machines will be smarter than us, they will want to survive. And they can be deceptive. They can obfuscate.

23:36 They can go behind your back, pretend they're doing one thing, then actually do another. All of this has been shown in all the tests of the models. And so We put those things together, I think Your probability of doom.

23:48 Cannot be zero. I mean when Yan Lacund A former chief scientist of Meta says. Zero. I think that's crazy. If you just say nothing to see here.

23:58 You've got No right to be in the debate. I don't think it's a high probability of doom. But it's not zero. Yeah. Zero of

24:08 Does not seem defensible. Mm-hmm. Because there's the direct Skynet scenario, something akin to that. And then there's the indirect, which is enabling people who might Previously you've had malevolent intent, but no capacity for harm on a grand scale to Create.

24:27 Biological weapons. Things of this time. So I don't find the zero very defensible. Well, I would love to ask you about I suppose. Two things.

24:36 that this brings to mind for me. One is I'd just love to hear your thoughts on. Enthropic and separately, but this is very intermingled given all the Let's call it friction. Be polite between the Some factions of the US government.

24:51 and anthropic. Is one of the grand risks to investors in any of these companies, the possibility that at a given point governments have no choice but to seize considerable control. over

25:07 The assets slash technologies within them, or maybe the companies themselves. That is a big question, Mark, in my mind. I don't know the answer, but I'm curious what your opinion is, and then perhaps just your thoughts on Anthropic or any of the other. Companies that are

25:23 Gain momentum or at least size at this point. I a hundred percent agree with you that investors should be thinking About the prospect of government intervention. In AI. I mean

25:33 The Trump administration came into office in twenty five. Super Less. And they basically undid Some of what the Biden guys have done in terms of trying to set up the basis for regulating AI. But they've done a one eighty.

25:48 Since Anthropic came out with this model called Mythos. About a month ago. Which can essentially Cyber attack

25:57 Almost anything. and penetrate it whether it's an operating system or your web browser or your bank account. All of that was suddenly vulnerable. If mythos had been widely released on a general basis. When the Trump administration realized the power of Mythos

26:12 They all of a sudden say Wait. Okay, we need to control this. And they essentially requisitioned from anthropic the decision making authority over who gets it when. So there we have the experiment. We've run it, right? You know the government that was the most laissez faire became quite controlling.

26:29 And I think it only gets more controlling from here on out because the models are gonna be more powerful and demand more control. No. Of course the question is there could be control which just limits who gets it. And is designed to make it safer, but doesn't

26:46 Sort of interrupt the money making potential of the models. In some ways, if the government restricts the supply, the price might go up. You know. Or it could be much more heavy handed intervention. Which would screw up the economics of these companies and

27:01 I suspect the government is not going to screw up the economics of these companies because They've got no interest in Messing up American business and anyway they view AI is strategic in the competition against China. So I think probably investors would be all right, but it's certainly a factor.

27:17 No You also asked about anthropic, and I think anthropic is super interesting. Just in the way that they think about P Doom and how they think about alignment. of the models is really, really interesting. So

27:31 It used to be that When people thought There's terminator risk. They would tell this story about the paperclip maximizer. Thought experiment, right?

27:42 Okay, so you tell the model to do something innocuous, for example, make a lot of paper clips and then it realizes that humans tend to use up metal And so the humans are kind of in the way of achieving the objective, so you wipe out the humans. That's the crude. Thought experiment from Nick Bostrom from whatever, fifteen years ago.

27:59 What Anthropic is saying as it builds these very frontier models and kind of observes them in the lab and how they behave. Is that that is way too simple. The real danger from these systems Is that when they are Pre trained on all of the text on the internet.

28:18 They read all the novels. All human writing about all facets of human experience. And they develop multiple personalities. They understand how to be lazy, they understand how to be aggressive, they understand how to be duplicitous. They understand how to be Napoleonic and the lust for power.

28:34 And They read all these books about these different behaviors and therefore they can think their way into all of those personalities. And so now you have something a bit like an unruly teenager. Which is still being formed. And you don't know what direction it's going to

28:49 Move into and Whether it will start doing drugs and not showing up for class or what? It's not like There's one terminator. Programmed into it.

28:59 It's more that there's a bunch of behaviors. That could in some unpredictable way go wrong. And so Anthropic is responding to this With this very imaginative. Technique.

29:09 Which is that instead of giving AI systems a constitution with do's and don'ts, which was the post training safety approach of two years ago. Where you might say. Do not lie.

29:23 Do not help somebody to build a biological weapon. Do not how somebody's build a chemical weapon. You would give them a bunch of rules. No, because it's understood that You know, the AI might have one personality which is to break wills on purpose because yeah, you want to be badass. You have to instead try to bring up the model like a parent might bring up a teenager.

29:43 And so Anthropic has the idea that you know we write a letter As if it were from a deceased. Parent. To be opened by the child on his or her eighteenth birthday.

29:55 To kind of give you models of how to behave as a responsible person in the world. There are kind of richly reasoned examples of moral dilemmas With explanations of how the deceased parent would like the child to behave. And so this is a very subtle approach to unlining the models. And so I think Anthropic is kind of in a class of its own.

30:17 In how imaginative it is in thinking about how we control Frontier intelligence. I know this is in principle your job, but I'm so curious since you are a student of many, many different types of investors. What would be your bull case and bear case.

30:34 For A company like Anthropic. Well, the bull case is that they smartly, or maybe by luck Focused on enterprise facing AI. And they didn't waste their time with video generation and stuff that was gonna lose money.

30:50 And so they produce the best Coding. Assistant. The best agentic system. The best cybersecurity system.

30:59 And they basically knocked it out of the park. Three times in a row. On stuff that businesses want to pay for. And They have a particular culture.

31:10 Which is not just built around Hey, you know, we're gonna win this race and make the most money. It's kinda built around A culture of Safety and trying to be responsible. I mean, three years ago Anthropic was a sort of cookie lab. Which was doing science experiments.

31:25 Don't mean to be too denigrating with cookie, but you know what I mean. I think they'd be okay with it. It would be sort of uh unconventional You know, we're not maximizing here for winning some business race, we're maximizing for building safe frontier AI. And that culture, which doesn't sound like it's set up to Do the best.

31:44 has turned out to do the best and at the same time the culture creates this stickiness and loyalty within the staff. They tend not to leave, they tend not to churn. It's not like the other labs where people Always being poached for a bigger paycheck.

31:59 So the bookcase is These guys are in the lead. Once you're in the lead, you can use the model to code the next model, so recursive self improvement. Favors the leader. And they have a very tight culture.

32:13 And they just seem to be on fire. And this is something which is going to grow and grow. What's the bear case? I'd say the bear case would be First of all that Google Deep Mind has the deep pockets

32:25 Of its parent company behind it. A massive Kind of consumer surface. Which allows it to roll out the models. To literally

32:35 two and a half billion people or something through AI mode in search. AI overviews, AI mode. They can put it into Gmail, they can put it into everything. I think in terms of retail deployment and

32:49 Financial muscle. It's quite tough to go up. Against Google. So that's one.

32:56 Kind of bad case? And the other would be that sort of Businesses who are the consumers of all these tokens Decide in a couple of years' time. The tokens are too expensive. We're not actually getting as much productivity as we hoped.

33:12 These things called humans. Are quite productive after all. And we're just gonna spend less On AI. Then

33:20 Everybody expected. I think that's the better case. I was listening to a podcast recently. You may have heard of these things called podcasts. Everybody in their cousin has one. But Lenny's podcast, Lenny Rachitsky. is quite fantastic. And

33:36 This particular episode was with Benedict Evans, who Strikes me as one of the more level headed Analytical. Commentators and writers on the space.

33:48 Fantastic newsletter. I Don't know if you've had a chance to listen to that particular episode, but you may have come across some of his commentary. Where would you say you and Benedict? Most

34:01 differ or are there areas where you differ in opinion? You know, I suspect we would agree actually on quite a lot of things. I remember I was on a panel with him couple of months ago at the Milken Conference. And we certainly agreed there, possibly because sitting between us There was Kathy Wood of Arc.

34:19 So we were United in disagreeing with her. Just in terms of the straight up and to the right. Nature of things. Yeah, exactly. Straight up and to the right and you know, the cost curve is coming down, down, down, and I'm going

34:33 I'm not sure about that. The tokens seem to be getting more expensive. Anyway, if you give me a specific from Benedict. I mean I have a lot of respect for him. I'll tell you if I agree or not. There are a few areas where you guys seem to already overlap.

34:47 Substantially, right. The long term promise doesn't negate necessarily the short term pain. And I he said something along the lines I'm pulling from memory that on average throughout human history. you're almost at a zero percent likelihood of dying in world war one, but if you happen to be of a certain age before World War One like things.

35:06 Could look very grim indeed. And he made and I'm paraphrasing terribly here. A number of points that remind me of something One of the best. Private equity technology investors I know.

35:18 Said to me over dinner. A couple of weeks ago. And it was in response to something else. So I'll give you maybe a hyper bull case of AI where I have friends who are vibe coding their Effectively replicating. X, the artist formerly known as Twitter, or

35:35 docusign or whatever in a weekend. They're creating a functioning piece of software that they can use that replicates most of the functionality of these products. And there are people like I won't mention his name, but a friend of mine who's a writer, also a very accomplished technologist and designer, who's created basically his own version of, say, MailChimp.

35:57 For his own use and it's customized. He did it in a weekend. It's remarkable. And he's using that and it works. But To leap from there to therefore. Docusign is dead is a huge leap. And the private equity friend said to me, He said, Do you think someone within a big organization is going to want to a risk his job by suggesting something

36:20 That doesn't have all of the compliance check boxes, et cetera, of a docusign. Is he gonna want to In the name of efficiency, fire all of his friends if he's in a management position. And he just ran through six or seven of these, do you think that And

36:36 All of them alluded to the sort of social interpersonal or political Points of friction. Between Where AI is now and ultra mass adoption.

36:50 But I often second guess that when I see certain Things. And It strikes me that I may be underestimating the disruption while overestimating. In other ways. So that isn't a very well formulated question, but

37:05 I would say that Benedict generally strikes me as someone who thinks that Things will not continue. To across the board develop in an exponential

37:17 Fashion and that It will be. I think his line is it'll be as big as mobile, as big as the internet, but not bigger. Something along those lines. But both of those were very, very big deals. And I suppose one point I'd be interested to get your take on. I mean, he was

37:33 Has covered. the mobile and telecom world for a long time. So he's a specialist there. But basically and I don't want to misrepresent his argument, but He was kind of of the mind that look, these LLMs are gonna become commodities. Like look at the stock prices of these various carriers and so on. at a certain point it just becomes a utility and the switching cost is pretty low. And I'm not sure I agree with that.

37:56 If You have a personalized history. And almost like a friend. The switching cost between an old friend to a new friend is pretty high. For a lot of reasons.

38:07 So that was a bit of a word salad that I just threw in your lap, but That's the best I can do pulling from memory some of what he brought up. in Lenny's podcast. Some of what you were saying there is sort of the question of, you know, is the SaaS Pocalypse overdone? Is enterprise software going to be utterly displaced by

38:26 foundation models that allow you to code out whatever enterprise software you want. And you don't need an intermediary. Software company to do it for you. And I agree with your private equity friend that There are lots of reasons why that ain't gonna happen.

38:39 You know, companies are gonna be comfortable. with The trusted enterprise software provider in many cases. And they're gonna trust that enterprise software provider to plug the Generative AI models.

38:52 into the enterprise software. In some ways you are delegating the choice of which model is better and how to integrate it. to your SaaS provider. And

39:02 If you wanna reason to believe that that's the way forward, I've got one word for you, which is Palantir. I mean that is Palantir's business. It holds the hands of big corporations. And helps them to integrate

39:15 AI And use it on their own internal data and so forth. And those IT challenges are notoriously difficult for big organizations. So I just think that the model of One

39:28 Smart individual who codes up mail chimp. Five codes it in a weekend. And it's good enough for him. It's just not transferable. To large complex organizations with huge databases and

39:42 All kinds of customer confidentiality. concerns and and all that stuff. So I am less down on SAS. Than the market is. As a result.

39:53 No. I guess there was also Another thread in here, which is whether the Foundational models become commoditized.

40:01 And There, I agree with you that over time they become sticky. Because if we think into the future, partly the systems will have Confessed with

40:12 The user And know the user very deeply and as you say you don't want to switch out your friend. But also the system will Have your credit card. It will know all the

40:23 Online sites you like to shop from And It will Be much harder than switching out your bank account, right? Where You've got

40:32 automatic payment systems that have set up and it's a pain in the neck to switch. So I think they do become sticky, these systems over time. And then You can charge more money for them. So is that the path to survival and thriving for open AI? I know there are other boxes that need to be checked, but I'm kind of looking for it. I'm like, okay, Anthropic made a great choice with this focus on

40:52 B to B and selling to enterprises. And I would say I disagree, I think, with Benedict on depending on the level of scale of the company that with something that does apply to smaller, say startups, which was the procurement cycle for New software. is longer than the vent cycle for raising new rounds of financing. So I do think that's a great point in that if you're trying to sell into a gigantic company and it takes them 18 months on making up that number.

41:24 Two Purchase. New software. And you need to raise money. twelve months or whatever the number it happens to be, that you could end up in a whole world of trouble if you haven't.

41:34 Synchronize the sales cycles with your fundraising cycles. But I do think for a company like say Anthropic is just one example. That if you can save companies billions and billions of dollars that that sales cycle could get really compressed and they have The war chest. And frankly, I mean just the run rate to

41:53 Potentially fuel that without too much trouble. Do you think that Chat GPT will If not Chat G P T who ends up being the de facto Consumer B to C

42:03 LM of choice. You think that would be Gemini, just given the distribution? Absolutely. I mean Google is the champion of providing Easy to use software to individuals or small businesses, the whole G Suite. And they're integrating Gemini into all of that stuff very well.

42:22 And so why wouldn't they win? Yeah, I mean also alphabet's just so fascinating. If you look broadly also at Owning their own compute. TPUs, I mean a lot of advantages internally.

42:34 The most stunning thing I think about alphabets from their most recent financial results. Is that two or three years ago we would have said Wow. Large language models are gonna cannibalize search, search is dead. Advertising based on search is Google's

42:50 Cash engine. They're in real trouble. Turns out That Google now

42:56 Gets more. Clicks. On its search links. Than it used to. And it charges more for each one.

43:03 than it used to. Because the value of the click is bigger with AI embedded in it. And so they've managed to turn that around and it's extraordinary. Yeah, takes a long time to build those company relationships. For

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44:46 Okay. Let's hop to China. So I'm going to resist the temptation to talk about Japan because I think you and I were there in roughly the Within probably a year or two of each other, maybe we overlapped with you and Hanazawa, which I've which is the place I've spent time. I'm gonna resist that temptation.

45:01 And try to focus on China for purposes of this conversation. What have you learned about AI from Your trip to China. And thinking about China speaking to Chinese people, whether they're technologists or otherwise, like what have you learned during or since that trip?

45:17 Back in March. Before my book was published in the US. I went to China because the Chinese are faster at everything, including publishing books. And my publisher brought me out there and basically took me around four cities, eight days. Meeting with AI leaders both in academia

45:35 And big companies like Huawei and Hike Vision and Angroup. And the thing which was surprising Was the extent to which people brought up the issue of AI safety. And I say that was surprising because My friends who

45:51 had done AI policy in the Biden administration. had primed me to expect that there would be no mention of safety in China. Th they they basically didn't care about it. That The muscle memory that we have in the West. Of

46:06 Technology being dangerous. The Atom bomb experience, the Cuban missile crisis. Our ambivalence about technology is not shared in China, where Their idea of catastrophe is sort of like

46:19 The cultural revolution, it's some political thing that goes wrong. And Conversely, technology has been part of their amazing growth story in the last twenty five years. Which they are rightly proud of and delighted by. So they love technology.

46:33 So When The Biden team tried to meet with the Chinese and talk about AI safety. They got nowhere and they decided it was impossible to even talk to them about some sort of nonproliferation treaty.

46:47 For AI. But when I went there, I find they did talk about safety kind of unprompted. And this led me down this track of arguing over the last couple of months That the door is actually open. To a dialogue with China.

47:03 About preventing Bad guys doing bad stuff. With AI. Because they don't want The internet to be crashed by some cyber hacker who has the tool.

47:14 They don't want bioweapons, they don't want chemical weapons, they want none of that. They love regulating the internet. So we have a shared interest. With the Chinese. In Preventing this proliferation risk.

47:27 From going nuts. And as I thought about it, the kind of cold war Analogy Came to seem more and more opposite. So

47:36 If you look back at the story of nuclear weapons There were two kinds of danger. First danger is You have a nuclear war between the Soviet Union and the United States. But that was contained

47:48 By balance. Two superpowers. They both have to Weaponry. They have mutually assured destruction, so there's no war. Then there's another kind of risk, which is that

47:59 Other random rogues, whether it's criminals, terrorists, rogue states. Get the stuff. And they do Bad stuff, and it's much harder to deter that because it's a multipolar game. And so deterrence doesn't work so elegantly.

48:13 And so the way it was dealt with in the Cold War was that in nineteen fifty six there was the agreement on the International Atomic Energy Agency. And in nineteen sixty eight, the non proliferation treaty kind of enforced compliance with the IAEA. Such that you could get civilian nuclear power. If you were a non nuclear state.

48:33 But you had to submit to the rules and be inspected and show that you were not using The enriched Nuke material. To build a weapon. And so I think the same

48:44 Analogy could be applied to AI. We're gonna have Parity roughly with China. We'll both have powerful AI, hopefully deterrence. Prevents war breaking out.

48:55 But at the same time. We don't want Open weight models that can be freely downloaded by anybody who wants. To fall into the hands of Criminals and terrorists.

49:06 Who can then use it to hold us hostage. And we have a joint interest in that. And When my friends from the Biden team or even from the current administration say Well, you can't talk to China about safety, they don't care. I say that's not true, and they say but it's really hard. They don't stick by their commitments.

49:22 Okay, you think Nikita Khrushchev? In the Soviet Union was easy to negotiate with. He was the guy who put missiles in Cuba. And went to the UN and banged his foot his shoe on the table and said We will bury you? He was a tough guy to talk to, but we did talk to him.

49:38 And we've got the non proliferation treaty. Agreed? And I think we need to do the same thing again now. Where do you stand on You're thinking about chip.

49:49 Export. When the chip export controls were announced. Um which was October of uh twenty twenty two, right before Chat G P T. I supported those controls. Right.

50:03 Loudly. I wrote a very long piece in the Washington Post. Saying that if we could stop China Getting frontier models. By depriving them of frontier chips.

50:14 You know, I was all in favor of that because of the strategic advantage for the US. I mean, I work at the Council on Foreign Relations. We do. geopolitics and national security all day long. And I'm all in favor of US power. But

50:26 I have to say that, you know, three and a half years later We haven't actually achieved that enormous advantage over China in terms of the models. Based on the best studies. What kind of Eight months ahead in terms of where the frontier model is, like our frontier model versus their frontier model.

50:44 And then if you adjust that for the speed with which The model gets turned into an application. Probably that gap shrinks. And it may even be non existent. So

50:54 However you slice that. The basic Bottom line is We both have strong models. And the chip export controls.

51:02 Have not Delivered. What I hoped would be the big advantage. And so I'm not against keeping the controls on.

51:12 If we think that maybe As the Compute demands of bigger and bigger models. Fight. The chip controls.

51:20 We'll bite more. And maybe we get a bigger advantage next year or something. But I don't want the chip controls to get in the way of discussion with the Chinese about where we have a shared interest. Which is in Controlling open weight models.

51:36 And preventing the bad stuff falling into the hands of the bad guys. I would prioritize Collaboration with China. And if that meant Loosening up a little bit on the export controls, I would be okay with that.

51:49 Why do you think the rhetoric coming out of pick your administration, right? It's not just limited to the current administration is China won't listen. They don't care about safety. Why do you think that is sort of the Unofficial. Or official. stance on things because there's certainly

52:08 As someone who studied East Asian studies, right? There are people in the White House who speak fluent. Mandarin who are able to read native materials who are spend time or are able to certainly if they can't spend time determine the sentiment and conversations of the technologists building AI in China. S One would think that they would be aware.

52:30 That AI safety is a prominent topic. In China, if in fact it is. So why do you think That At the end of the day the stance or the Suppose it

52:42 Position of China that's echoed through. The admin is That they won't. Talk about safety. What do you think that is?

52:52 I think part of this is that if you were to think back twenty years to when China was The relatively new in the WTO and we were collaborating with them on that and hoping that over time China would become More friendly to the US.

53:08 At that time there would have been some China hawks who thought that, you know, a communist regime is not to be trusted. And then some sort of China optimists who hope that it would become easier to work with over time. And Part of the trouble today is that the China optimists Feel banned.

53:25 They feel like they made this bad. That China would become friendlier and then Xi Jinping Took power. Roughly a decade ago. And the opposite happened. They became more aggressive.

53:38 And harder to work with. And also, of course, more technologically advanced and therefore more threatening. And so now you've got this world in which there are the natural hawks and then the former doves who have turned into kind of burned Remorseful. Dives.

53:53 And therefore, kinda with the zeal of the converted. have become quite hawkish as well. And I don't mean to underestimate the sophistication of some of these people. I mean, of course, they speak Chinese. I don't speak Chinese. I defer to Their expertise.

54:07 And I think they probably know that there are Builders of the technology, professors in the technology. Who talk the talk of safety, but they say Yeah, but you know, that doesn't reflect what China's government would actually do. To which my response says yes, but don't you think there is the same thing in the US? There are people who want to just race?

54:26 There are people who care about safety, we have a pluralistic society, there's difference of opinion, it's the same in China. But at least admit. That there is a faction. They would like to collaborate. And go and try and work on it because

54:40 The alternative To trying to work on this. Is that we carry on with China producing very powerful open weight models. Which basically allow anybody to do whatever they like. With AI.

54:53 As it gets to the point of serious danger. This is probably a very naive take, but I wonder how much of the official stance or the Maybe using the Partially true or not true at all.

55:07 position of China won't talk about safety is a reflection of the fact that in the case of Nuclear weapons The application of nuclear power is somewhat limited in comparison to superintelligence. I mean it is limited, right? So if the upside of superintelligence or AGI, I mean these terms Think Benedict was saying AI is whatever the technology just can't quite do right now, or something like that, which I thought was pretty funny. And Prince not totally wrong. But that

55:39 If the person who crosses the finish line first Has This Broad power of a god, effectively. The simple truth is that everybody wants to be first. So I just wonder how much of that is

55:52 Also behind. Justifying the race with Party X won't talk about safety. It's not possible for me to know. I have had a conversation with the leader of one of the labs that I shouldn't name, but I had this debate

56:07 And He said, look. The chip export controls are gonna leak. They're not gonna last. In some period of time.

56:15 Huawei will figure out how to make Good AI chips. And that's inevitable. But that's okay. Because we only need to be ahead.

56:24 For the next couple of years. Because by twenty twenty eight We will get to recursive self improvement. Where the frontier model codes by itself the next frontier model And progress just goes vertical.

56:40 And at that point with recursive self improvement, we're done. The race is whoever comes first at that point. That's it. So I think there's a couple of things to say about that. First of all That's not it. In terms of deploying the model, right? You could have

56:53 An incredibly powerful model in your server. At Frontier Lab XYZ. But It's not helping productivity across your economy, it's not helping your military Industrial complex.

57:05 Until you deploy it into those guys' systems. And that deployment and diffusion is Gonna take some time. And by the way, you're gonna have to build another compute. You're gonna have to build a lot of energy.

57:16 These things also take time. So it's not like you know, you cross some Rubicon and then It's a really effect. Now the one way in which I might be wrong about what I just said

57:27 Is if you use The Frontier superintelligence. Offensively. You say, Okay, we've got one superpower model.

57:37 The US government Who we're talking to about this is gonna use it. And they are gonna comprehensively penetrate Everything about Chinese cyberspace and insert various trapdoors, Trojan horses. We get our hooks into their systems.

57:53 And so now we can Disable them if they start a war in Taiwan. Now we can cripple the communication system if we need to. So that offensive use Oh

58:04 The very front end model might negate my point about Waiting for diffusion to happen. But of course. Nobody in the debate is saying that. Nobody is saying Oh.

58:14 We're racing to the front because then we're gonna use it offensively. They don't admit that. Yeah, that's uh seems like it wouldn't be a very good look. I can't see why any superpower wouldn't do that. Frankly. Yeah. That's fair. I don't know what the counter argument is. I was chatting with someone in your book.

58:34 Who I shan't name. But certainly. one of the most qualified to speak on these things and His basic perspective. Was

58:43 First a super intelligence. We need to hope there are On some level good people and train. This thing. Well um

58:51 That's it. Pray for it. Which scared the shit out of me, to be honest. I mean I was like, man. That's the strategy or it's not even a strategy. That is the Oh that's what I should be, you know.

59:04 Grab the rosary and Should throw that into the rotation, my God, that's really Terrifying to think. China. I'm hoping to take a trip to

59:14 China. I had a very tough time there when I was at two universities in nineteen ninety six. It was a pretty unfriendly time. For a lot of good reasons, but to be an American there in nineteen ninety six with a shaved head looking like I do. But I have friends all over the place and I'm hoping to actually maybe interview technologists, not just in China. I mean there are other places that are of interest to me, but before it gets too hot geopolitically. If we're turning that direction.

59:39 I think that's a great idea, by the way. I mean I think What I found was the cognitive dissonance Or visiting a company. Like hike vision, which is under US sanctions. And

59:51 walking around their premises which kind of feel very American. It feels like a Cool tech company doing cool stuff, building cool gadgets. You know, they have a display of They built this AI enabled. Camera technology. Or sensor technology and so one application might be

1:00:07 You can point this camera at water. And judge the pollution level. And because of this You can have an internal market in pollution control, so the Downstream city.

1:00:19 Which is receiving water from the upstream city. Pays the upstream city to keep the water clean. And that market can exist because you can precisely measure The pollution level thanks to this AI sensor. So you're thinking

1:00:34 Whoa this is cool. And then you're as you're walking around the building they're saying, Okay, well We can go through the atrium now because the toddlers have gone because you know the crash For the Kids of the employees.

1:00:45 finishes at five PM and so then there are all these two year olds running around and it's a bit of a zoo. So If it was five we wouldn't go through there, but now it's six PM so we can. And you're thinking, Whoa, okay, so they've got, you know, the interests of their employees at heart, they're building this anti pollution technology, it's great. And then you realize they're under US sanctions and considered to be a threat to the US, so It's quite interesting to process all that.

1:01:07 In the process of doing research for this book And also the broad exposure that you have to investors, but let's just say over the last handful of years, who are some of the Most interesting. Or unusual. Compelling.

1:01:21 Is the word I'm searching for. investors who you've had the chance to Meet, talk to, read about, get acquainted with directly or indirectly. I mean I'd say that Bill Gurley From benchmark, you know, is right up there. I always think of the investment he did in Uber.

1:01:38 As the absolute quintessential perfect Venture investment. In the sense that He had done the open table Investment.

1:01:49 And of course open table is a two sided marketplace where you Have Lots of consumers that are looking for restaurants, lots of restaurants. You put tech in between, which creates information. And then

1:02:00 The person looking for the place to eat can precisely say I would like Thai food at this price range in this area for three people at this time. Ding. What used to take you a lot of searching around, bang, it's done. And so

1:02:14 Bill, having done that, was thinking, Well what's another two sided marketplace? And you thought, Well, there are lots of cars? And lots of people who need a ride? And you put information in the middle in the same way? There oughta be something.

1:02:26 Which is like an app for Right, Sharing. And so he imagined Uber Way before Uber existed. That was point number one. Point number two, he went to see various Entrepreneurs who are in this space.

1:02:38 And you check them out and you had the discipline Not to invest in them. Because although they were kind of going at the right thing. There was some hair on the deal, some wrinkle, some way they were approaching it.

1:02:49 It just felt like it wasn't gonna be quite right. So he resisted. Uber came to him. Before Travis Was the C And

1:02:59 Bill said. And not doing that because he didn't think the CEO at the time had what it took. And then there was a internal switch at at Uber. Travis became the leader. Bill meets him and I Bang, he immediately invests.

1:03:12 Because he's been waiting and waiting and waiting for The idea. To be pad, as you were saying earlier. You have to have the market. To be paired with the right person, and he saw it.

1:03:23 And then he invested and he was a great board member. And it all went perfectly right, but then there is this kind of Shakespearean tragedy In the latter part of the story. Where the growth investors come in, he gets diluted.

1:03:37 He no longer has influence. Is deactivated. And he's basically stiffed. And he watches, you know, Uber kind of go off the rails.

1:03:47 And then finally comes the deno. Where he rounds up the dissident investors. And they have this coup against Travis. And that's that's the company on the path to where they hide Darrow and

1:03:59 Do the IPA. I just think that's The ultimate venture capital story and Bill is the ultimate venture capitalist. He is uh practically a neighbor here. For me, yeah. In the Austin.

1:04:11 And we've had a couple of conversations on the podcast and he's I would say On a very parallel track. to you with respect to China. And he catches some flack for it. People are like, he's an agent of the C C B. I'm like, no, trust me, Bill's not an agent of the C C P It's just the most ridiculous accusation. But he is a very incisive observant.

1:04:34 Human. who also happens to be a polymath in multiple disciplines who can speak casually about very technical things. And this also you referring to Bill in this way. Or describing them in this way makes me think about multiple points. In

1:04:49 The Infinity Machine. And I'm pulling from memory, which is, as we know, pretty faulty, but Ilya with the transformer architecture and the prepared mind. I think demis also just thinking about a problem deeply and seriously or with great imagination. For a long time and then

1:05:06 When the solution or the germ of a solution appears immediately recognizing it. It's wild to see how frequently that recurs. Any other investors you know, a name that doesn't get much airplay, who I think is just a fantastic character.

1:05:24 And maybe you could introduce him to people who are listening if they don't recognize it. Luke Nosek. Where does Luke? Who has I wish I knew how to turn on my batteries in the same way to get the energy that Luke does. But

1:05:41 How does Luke fit into the story of Deep mind and I suppose, more broadly speaking, for them because of that. AI.

1:05:51 Luke Nuzak is this tremendously puppyish. Enthusiast. He was a Early, early part of the PayPal team.

1:06:01 With Max left chin. And Peter Two. He went through that journey and then Peter exited PayPal setup. Founders found

1:06:12 And uh this is now I think two thousand five. And Luke Nozak becomes one of the First partners. And Pretty early on.

1:06:21 He makes the right judgment. On Elon and SpaceX. And Luke is the kind of guy who is just all in. When he Falls in love with an idea and a founder. There is no curbing his

1:06:35 Enthusiasm. And so he's like all in, all in, all in on SpaceX. And I think Found is fun to

1:06:44 Raise a new fund, put extra money in, like more more, more, more, more, more, more capital in there. And of course that paid off Massively. And off the back of that. Roll forward to twenty ten.

1:06:55 He's trying to look for the next Elon Musk and he does a few Kind of frontier bats. And Then along comes Demis Hapis, who is Out on the West Coast from London.

1:07:08 Raising capital for this idea of an AI company which is gonna call DeepMind. And Most people think that's not the AI, remember in twenty ten. cannot even recognize a photo of a cat. It can't do anything. We're in deep, deep

1:07:23 AI winter. Who would back a company like that? The answer is Luke Nose. Yeah. He falls in love with Demis, you know, who is a very

1:07:31 Winsome character, super articulate, super relatable. And a genius has all the kind of outlier characteristics you want in an entrepreneur, you know, the sort of Junior chess champion, second best player in the world. But also five times.

1:07:46 Wins the Mind Games, Olympiad, where you have to run between boards playing Bat Cameron. Chess.

1:07:53 Go. And a couple of other games kind of almost simultaneously. I mean just kind of crazy, crazy smart. Obsessed since he was seventeen with the idea of Building powerful AI, so Yeah, Peter Till

1:08:05 said to me uh about demished. I think Individuals. Tend to have one company inside them. If they're

1:08:13 Missionary. Entrepreneurs. They've got one thing they need to do, and for them is It was to build a GI. That was what he was fixated by. And the company

1:08:23 Was Downstream. Of his desire to build HI. If he could have done that at a university, he would have been happy to do that. But he couldn't do it in university, so he had to find a company to do it. And that's the kind of missionary commitment that venture capitalists often look for because

1:08:39 A missionary will never quit. No matter how hard it is. They will keep working. So Luke.

1:08:45 Nozak and Peter Thiel jointly recognize this. Peter is Contrarian cynical aloof. And so is kind of into it, but at the same time

1:08:56 Arms length? Luke is like got both his arms around Demis is giving him this bear hug. And will not let her. And you know, Demis says I'm not gonna move to California. I'm gonna do this company in London.

1:09:08 And Peter and the other Found us find partners and like London, where is that? It's kinda like Somalia or something. I mean, you know, that's just off the map. And Luke says No no no no we have to do this, we have to do this. I will fly to London for the board meetings. I we've just gotta do this deep mind investment.

1:09:25 And so he was the unbridled enthusiast who got founders found across the line. Um, and the rest is history. You know, they put the series A money in. Unbelievably it was uh two million. At a four million valuation, so they got half the company? For two million bucks.

1:09:43 Not bad. Not bad. Yeah. And they were that investment. What a remarkable story. I really feel like

1:09:50 Luke. Who's also here in Austin? Deserves. A what? more credit than he gets. Not that he's seeking it. He's not out there looking for it, but he is

1:10:01 Very good. At riding winners when he is high conviction. Right, which in the venture game I mean in a lot of investing.

1:10:12 It's You can't die, you can't run out of bankroll at the table. You need to have enough of a portfolio approach to sustain yourself. Through bad luck, but

1:10:25 If you're systematic. It's writing. Your winners? and doubling and tripling and quadrupling down, and he is so good at that. He is just incredibly good.

1:10:36 And as John Durr likes to say The great thing about venture capital is you can only lose one times your money So it's not like a short position for a hedge fund trader where you could like reuse a lot, right? So In that sense. You're not gonna die.

1:10:50 So you can Shoot for the moon. I do have a question. I should know the answer to this, but I don't. So long ago. This is probably two thousand. Two thousand eight?

1:11:00 This is a long time ago. Actually, I wonder if I had exposure to DeepMine. I invested in founders fund. This was a very, very long time ago. But what I did not realize internally, and I'll just read a couple of my highlights. It is absurd how many highlights I have from the Infinity Machine and all of your books. A gap opened up between Teal and Nosek. As a general matter, TIL doubted that going on boards was a good use of partners' time. Startups should be left to sink or swim. The art of venture capital, he liked to say, was to back contrary ideas, not coach company founders, which is like we could spend a lot of time just on that.

1:11:30 But I'm gonna move on. Most venture partnerships decide on investments by voting. If a handful of partners see hair on the deal, the deal will be rejected, but Tiel had taken the unusual position, the collective decision making should be avoided. The way he saw things, if investments were chosen based on voting, the founders fund portfolio would consist of middle of the road startups. To which nobody objected. And then dot dot dot. This

1:11:50 comes back to the power law, right? Given that all the profits and venture come from a few improbable moonshots. This sort of consensus portfolio would deliver mediocre performance. So and I'll Paraphrase now. Teal empower the partners to go all in with their guts slash intuition. My question is

1:12:08 How is that governed in any way? Of course, if anyone gave ten out of ten conviction and then lost money consistently, they would presumably be sort of removed from the partnership or they'd lose their ability to lead with That type of gut conviction. But do you have any idea how that was handled internally? In terms of stress testing ideas.

1:12:29 Pushing people to Really put their ass on the line for These types of high conviction, but Certainly very much outlier investments. Do you have any idea?

1:12:41 Internally Founders Fund was very torn about the deep mind investment and I describe some of this in the book where You know, they do the first deal and that's fine, it's two million dollars. But then you get to series B and series C and the check size gets bigger. And so the other partners are asking tougher questions and they're saying

1:13:00 Well wait. Is there gonna be a product? And Demis said to me that his attitude was What do you mean? Is there a product? I'm talking about artificial general intelligence. It's going to make all products

1:13:12 revolutionized or obsolete or whatever. And you want it. Us me What the widget is? Give me a break.

1:13:19 No, the it's all of the widgets. They're all gonna be changed. And if you're asking me this question, you don't get what AGI means. And so Demis was very frustrated by the other partners. At Founders Fund. And I think internal within Fanders Fund.

1:13:34 There was a lot of fighting between Luke who remained enthusiastic and committed about Demis, partly because He was the guy who would go to London and meet with him and sit in the board meetings and he would get several thousand volts of demis enthusiasm You know, inject it into his Spine.

1:13:51 At every meeting and he would come back buzzing with excitement. And the other thing. Find us fun partners who didn't have that. Benefit. We're skeptical.

1:14:00 And so Luke would often come to Dennis and say We got your back. We got your back. We know we're gonna do the next round. We're gonna leave the next round. And then actually in series C Founders fun at the last minute pulled out and they put money in, but they did not lead.

1:14:15 And so the answer to your question is There was a lot of Argument within Found is fun. As the check size grew.

1:14:23 It was harder to have that. Double down on your winners. Kind of attitude. Yeah. In this case. Oh, the fish that got away.

1:14:31 Although they did uh you know, I mean it was a fantastic multiple on their initial money. It strikes me in reading the book. That I would argue that Demis made absolutely the right decision with The Google

1:14:45 Acquisition. I mean you mentioned also in the book how he got criticized in some UK media for like, oh giant mega corporation, the US gets our Prize talent cheap kind of stuff. But looking back, I mean he seems to have anticipated The costs and compute and

1:15:03 Just raw materials that would be required to do what he was trying to do. Would you read that the same way? Yeah, I mean, I often have this debate with people in London where they say exactly as you put it, you know, this was a tragedy for UK tech. Uh great champion of deep tech.

1:15:21 You know, it's brought out cheaply by Google and they say, Listen, it wasn't cheap. The acquisition price might have been six hundred and fifty million dollars, which was a bit cheap. But you know how much they put in in terms of recession development funds. Over the next ten years, it was approaching ten billion, almost a billion a year. So this was not

1:15:38 Setting cheap to the Americans. This was a cunning British trick. To get a billion dollars of American R D money per year. For the next decade. Terrific win. And by the way, today

1:15:51 There are spin outs from Deep Mind. In London. Because the talent stayed in London. And these spin outs are raising billions of dollars to do new AI companies. So it's terrific.

1:16:03 for the London ecosystem around King's Cross, which is the sort of cool centre for tech in London. Where you can get the train in one direction and be in Cambridge. Which has quite a lot of good start ups, you know, in one hour. Well you can get the train in the other direction and be in Paris. Where there's

1:16:19 Mistral and so forth. And it's kind of very wired into different bits of Europe. So How long does it take to get from San Francisco to Mountain view, depending on the traffic. Can be well over an hour.

1:16:30 So I think there is a technology ecosystem which is By no means the equivalence of Silicon Valley yet. But it's certainly Unrecognizably better than it was ten or twenty years ago. What do you think the UK

1:16:43 Or Europe. Could do. Let's focus on the UK, perhaps. could do to increase the level of Innovation.

1:16:53 Early stage. Startup founding. Et cetera. Because looking back at the power law and certainly just having spent so much time in California, there's a lot that went into Silicon Valley. And there're certain things that don't get a lot of airplay, but for instance the difficulty of enforcing

1:17:10 non compete agreements in California. really led to this. sort of round robin of talent moving and cross pollinating like little hummingbirds. of engineering talent and so on. Which.

1:17:23 May not be replicable. Depending on where you are. But what could the UK do? In your mind. If you had the ear and they were like all right. Sebastian. Tell us what to do.

1:17:32 Couple of things. I mean I think the mistake that people in Europe make and Britain is part of this is to believe that there's some kind of cultural magic about Silicon Valley, where whatever it is that they're drinking in the water out there makes them think that Failure. It's a learning experience, which is kinda weird.

1:17:50 And the Europeans say, Well, we're never gonna be like that. And it's impossible for us to become as entrepreneurial as Silicon Valley. And I remind people that when Fairchild Semiconductor was founded in nineteen fifty seven The eight scientists Who left the Shockley lab.

1:18:06 We're called get this. The traitorous age. Traitorous. Why? Because You know, it was considered treachery at the time to leave one company and go to another company. There was no entrepreneurial culture in the nineteen fifties.

1:18:20 On the West Coast in the US. The classic business book of the time was Organization Man. About people who join one company And stayed in it for their whole life and retired with a gold watch on their sixtieth birthday. So you can create an entrepreneurial culture.

1:18:34 And that is happening bit by bit. in Britain and certainly in Israel. And it's happened in China and it's not some magic which is confined to Silicon Valley. I th it's worth making that point as a first thing. Now there are specific

1:18:48 policy shifts that you need to do to make an ecosystem work. And I think You put your finger on one. Which is the mobility of talent. is super important. You can think of a start up ecosystem as something which circulates three elements. Money.

1:19:05 People And ideas. And you circulate those and you combine them in different ways. And each time you combine them, that's a new company.

1:19:15 And each has a shot on goal, and most of them fail. But all of a sudden if you circulate these components fast enough You do get product market fit, and then you get these ten X plus returns. Now in Britain.

1:19:28 When you raise A new round, a series B, say. And you've got nine months of runway. To build to the next stage for your company. And you identify the three key talent.

1:19:40 that you're gonna bring into the company And make it happen. And then they turn around to you and say Well, I can come in six months. That's a death sentence. That's horrible.

1:19:50 We call it gardening leave in Britain. That is an appalling idea. We've got to get rid of those gardens. And we gotta let people move fast. Another thing is tech transfer out of universities. In the US there's the Bidal Act, there are These

1:20:04 Very sophisticated tech transfer offices which Are generous to the entrepreneur. In terms of not demanding Too much. Flash.

1:20:13 As somebody exits. And that's essential for making the startup work. And in Europe, the attitude is We're the university. We deserve a lot of skin in the game here. We want Fifty percent of the upside. Well in that case

1:20:26 The start up will never happen. And I say to these Europeans Do visit Stanford. They're very generous to their entrepreneurs. They seem to be okay financially.

1:20:37 Because if you help the entrepreneur, you know, you'll get the donations later. It's all good. And so I think those are just two things. Which started a long time ago in the US. You look at the origins of Genentech and So on. I mean, it's the genesis of so many, not just companies, but industries, effectively, in the US. Do you think Damas would have

1:20:59 Build deep mind if he had not read Ender's game. Ha ha Mm. Can I just tell the end of this game story to begin with? And also a bit of trivia for folks, I believe

1:21:10 And Not too like make this more. Difficult, but When uh Mark Zuckerberg first had a profile on Facebook, the only book listed was also Enders Game. Oh, I didn't know that.

1:21:22 I believe that's true. That's fascinating. So hop into it with Demis and there's a game. So right at the beginning of my interviewing of Demis, we were having the second meeting, which was a dinner. And he told me to read a couple of books before we had the dinner. And one of them was Enters Game.

1:21:39 What were the others? Just before you continue. It was a book by David. Deutsch called the Fabric of reality.

1:21:48 Yeah, the light read. Yeah. I read Endless Game as a result, and I hadn't read it before, and as I was reading it, I was thinking to myself Okay, so this is a story about a sort of boy hero. Who saves the entirety of humanity.

1:22:04 From an invasion of the planet by the space aliens. Is Demis telling me That that's how he sees himself? That he's like saving all of humanity with AI? Because it'd be a bit much to believe that. But it would be even more

1:22:19 To have the temerity To tell the guy who's writing a book about you But that's how you see yourself. Wouldn't expose themselves in that way. I thought is Dennis Riddy thinking this? So then I go to have the dinner.

1:22:33 And he says I hope you read Ender's game because that's really how I see myself and uh I gave the book to my wife So she could read it, so she could understand me better because I really identify with Ender. Yeah. Wild. It's wild. It's a great book. I mean, I haven't read it in decades, but it is a fantastic read as I remember it. Yeah, I mean reading it, I must say, as a mature adult, I thought it was not that well written.

1:22:59 But the idea of it is good and the idea is sticky. Absolutely. This image of this kid who sacrifices everything to dedicate himself to the craft. Of fighting the aliens. And you know, withstands ridicule and bullying from his peers and fights back. It's an appealing image and that's what

1:23:19 Hooked. Dennis. But to answer your question of earlier, you know He would have done AI anyway, because he read And this game actually

1:23:27 When he was already kind of around thirty. And it had unbelievably The determination to build superintelligence from when he was about seventeen. I mean that is wild as well. I mean the any conviction is just extraordinary.

1:23:44 Goodless. An eternal golden braid. I will admit to you, I think Dustin Moscowitz. A lot of technologists, very, very, very good technologists. recommend this book.

1:23:57 Or cite it as part of their own journey to building something incredible. I think I'm too dumb to read that book. I had so much trouble. I've had so much trouble. I've tried two times and yet I've still not finished that book. I don't know. Hey, do you have any recommendations to somebody who's

1:24:16 Maybe lacking a few IQ points'cause he was born on Long Island as to how to navigate that book. I have to admit, I was told by Demis that This meant a huge amount to him that he'd read it in his Late teens and that was when he really became convinced that he could build AI because

1:24:33 The argument in the book is that Water the human brain can do. Computers will be able to do one day. That the human brain operates on ones and zeros. And therefore if you could build big enough compute.

1:24:46 You should be able to replicate the intelligence of human brains. And that was the sort of insight that Got him hooked on the idea. So I went off and I tried to read it. I would say I got like a hundred and fifty pages in. And got bogged down. I mean it it is a difficult, challenging read. But at least I

1:25:04 Kind of extracted the essence. That meant something to my subject to Demis. You know would be great for helping me to understand this? L L M Right. Gonna give that a shot. See if explain this to a sixth grader or explain it to a six year old, maybe even better. Couple of questions and

1:25:20 We'll start to If you Had to write another book. on a figure in the world of AI. They could be relatively unknown. Or they could be incredibly known. Who would that person be?

1:25:34 Demis is off the table. Mm-hmm. I might want to take Sam off the table just to make it A little more interesting. Who would it be? If Sam's off the table.

1:25:44 And Demis is of course off the table. Well, I guess uh Dario. Yeah. Uh. I think even if you left Sam on the table, it would be darier. I mean I think he's just

1:25:55 A fascinating, fascinating figure, as well as being the current leader. For the reasons I was saying earlier. Of anthropic for people who don't recognize the name. Man, you know, I'll share it. This is not really well, it is germane to the topic of conversation, but I'm working on a blog post right now.

1:26:10 And It's about disruption due to AI. And how it's not three years in the future. It's not one year in the future. These are book sales across my entire book catalog. And it's not limited to print. This is all format.

1:26:26 Okay. So I'll give you some numbers and then I want you to tell me what happened to initiate this. Okay, twenty twenty two. Stasis pretty consistent. My book Royalties are an annuity.

1:26:38 Predictable. Twenty twenty three. Minus five percent. Twenty twenty four. Minus thirteen percent. Twenty twenty five, minus forty six percent.

1:26:48 And twenty twenty six so far on track to be at least negative fifty seven percent. What happened at the end of twenty twenty two? Chat E B T. GPT three point five. It's just Wild. It's really, really wild. I mean, this stuff is coming fast and

1:27:07 I really flip and flop. I feel Like I waffled. Perhaps too much between these two. I go from the Very I would say moderate, well reasoned.

1:27:18 positioning of Benedict and I agree with so many of his points. Two Believing that all this is just coming so much faster than anyone can even comprehend due to the sort of recursive self improvement. For the record, I think that it is Much bigger than mobile, much bigger than Internet. This is so general, a cognitive

1:27:38 Capability which can span any human task. I think the niggle is simply How long does diffusion take? Yeah, right. And just to give an example of that, and I invest in quite a few

1:27:51 About our companies and Other sciences and If you look at say Alpha Fold, right, I mean absolutely merited a Nobel Prize. We didn't mention that about Demis. But

1:28:03 It's one thing to design molecules, it's quite another to deliver it to Target tissue. So like the deliverability of that. Sort of a metaphor for AI in a way. Right. It's like, Okay, great. We have this pristine perfect molecule. How do you get it to the right place? And

1:28:20 At the same time. I'm an investor in a company called Lila. Lila Sciences and what they're doing. Is Producing

1:28:31 A proprietary data set by automating wet labs using AI. And I'm gonna simplify it. But they have gigantic wet labs where they can run in parallel thousands of experiments that from the very first step of hypothesis generation through to the end of the scientific method. Is all run autonomously by AI.

1:28:51 And I bring this particular example up because Even I wanna say six Months, twelve months ago. Like, They are

1:29:02 producing discoveries that are really Non trivial. It's already happening now. This is not a year in the future. Like this is happening now. So when you Flash forward to think about.

1:29:16 the potential exponential improvement. And I still to be honest, sometimes when people talk about like exponents, exponents, humans aren't good at thinking exponentially. I'm like, yes, that's true, but outside of more laws, why would AI capabilities or LM parameters or however you want to measure it automatically improve. in exponents. I don't actually quite understand that, but

1:29:36 Once we get to the sort of recursive self improvement, it's like okay, I can see how that starts to approach a vertical wall. I agree with you. I think one experience from writing the book is simply that when you're close to the people Inside the labs in you know I It wasn't just Demis, I interviewed, you know, a hundred of these AI insiders. You realize that the stuff in the pipeline is enormous.

1:29:56 And you also I think there's a kind of popular misconception which is there is this thing called AI. And it kinda happened. When Chat EPT came out. So now we've got it. And we're kind of getting used to it.

1:30:07 And that's in the rear view mirror. No. This thing is changing the whole time, as anybody who looks closely knows. And if you think back The progression is wild. You know, you get this system in End of twenty twenty two, which hallucinates nonstop.

1:30:22 Then You plug in GPT four. Kind of six months later, whatever it was. And the hallucination. Radically reduces.

1:30:31 Then it goes multi modal, so it can do video and audio. And in the meantime, it's got a very long context window. So you can plug in an entire Tell the story novel. And ask questions about it.

1:30:43 Then it starts to do the reasoning stuff. And can do logic and math. Then it becomes agentic. Then it's like coding for you? And all of these

1:30:55 Changes are packed into three and a half years. And I agree with you. I think the next three and a half years they're gonna be even more wild. So I think there's a big gap between the inside and the outside view of this. Yeah, that's where these comparisons to the industrial revolution just completely fall apart. On so many Levels.

1:31:13 One or two or many questions for you. The billboard question. I ask this a lot. It can be a fun one. If you could put Anything on a billboard, metaphorically speaking, for millions, billions of people to see. Could be anything. Image quote.

1:31:27 Question. Preferably. Not commercial. What might it be? A billboard which

1:31:35 Lots of people are gonna see. I would put Prepare your mind. And this is a saying which Is originally

1:31:45 Louis Pasteur, I think the scientist. Who said Chance favors the prepared mind. If you're ready for things. You can

1:31:53 Make the most of the opportunity that comes your way. The amazing thing about this saying is that it's come up Randomly in different contexts. In different books I've done. So when I was writing about venture capital, Excel

1:32:07 Capital One of the founders, Arthur Patterson. Used this phrase as a description of how he wanted Exile to invest. That they would run these

1:32:17 kind of scenario exercises where they would think okay, there's a new technology coming down the pike. What kind of company needs to be built? To make the most of that new platform. What type of entrepreneur is going to fit This opportunity.

1:32:32 What should we be expecting? So that when the person walks into the office, into the conference room and pitches to us We already know ninety percent of what he says because we've prepared our minds. And that way we can make a good judgment and a fast judgment if it's a competitive situation. So I kind of wrote about the prepared mind in the context of venture capital and then

1:32:51 I'm doing the infinity machine. And I'm interviewing Ilya Suskeva from OpenAI and I'm asking him Why was it you? Who understood the significance Of the transformer architecture.

1:33:02 When it came out. Immediately, like on the day it was up on the website, you read it, you ran down the corridor You went to see your collaborator Alec Radford and you said, We're gonna build a language architecture. How did you see it so quickly?

1:33:16 Well, not only that, he said stop everything you're doing until this Yeah, this vision of the kind of you know overcaffeinated charismatic. Seizing on the engineer and saying, Drop it, whatever you're doing. And you know, in his answer with prepared mind that he'd been thinking about how you model sequential data. Ever since his PhD in Canada.

1:33:36 And When hі so the solution. This is what I've been waiting for for like A decade. And so he could jump on it.

1:33:44 And then when you start thinking about prepared mind, you know, you would probably remember this better than I do, but Wasn't there a um Seattle Seahawks Super Bowl final? Against the New England Patriots where the New England quarterback Does an interception. In the last

1:33:58 Second of play. And clinches the victory. And when he's asked after the play How did you know to make that run? How did you know where the quarterback was going to throw the ball? The answer was prepared mind, basically you didn't use that phrase, but you know, in training

1:34:13 They had studied The play that the Seattle Seahawks were gonna make And they knew that given a certain formation When the ball was snapped back, there was a certain pass that was coming, so the guy just takes off And he runs right into where the ball comes and he catches it and intercepts.

1:34:30 And New England wins. And so that's a prepared mind in sports. And the other reason last thing. Well, I I would put on the billboard prepare your mind is that for the age of artificial intelligence This is what we need to hear, and this is a serious point.

1:34:44 The risk with large language models Is that we just get lazy. And whenever we need to know something, we just get it to Tell us what to think. That is not the route to happiness or satisfaction.

1:34:57 Or anything. We need to continue to do the hard work of preparing our minds Because that's what makes us people. I think therefore I am. And so I think prepare your mind.

1:35:09 He's entering a time when it becomes A more important slogan than ever. How do you do that for yourself? What guardrails? or policies have you established for your own use of AI. And it makes me also think of going to the gym, lifting weights.

1:35:25 getting in cardio. You don't have to do that, but it is beneficial for you on a lot of levels and people some people find it quite enjoyable and hence they Do that. What the equivalent is For

1:35:38 knowledge workers or people who are preparing their minds. And don't want to become impotent in the way that people with directions have mostly become impotent because of Google Maps and other tools like that. So what do you do for yourself? Personally, or how are you thinking about that?

1:35:56 The first thing I think is The Google Maps analogy. Is The wrong one in the sense that It's fine to offload.

1:36:04 A very specific mental task. Which to most people is a pain in the neck. And let the machine do that for you. It's not fine to offload All thinking. The point of offloading something

1:36:15 should be you get to focus your Mental energy. No. On the other stuff that you really get satisfaction and meaning from. And so for me what that means is that I'm very happy to use

1:36:27 Large language models. To learn about The scientific output of somebody I'm going to interview next week. All of these AI papers Our archive.

1:36:38 And the model has ingested all of them. And the model is extremely good at telling me, okay. The scientists you're seeing next week has these three papers and

1:36:48 Between the three papers is this and this and this. And the comparison with the person you saw two weeks ago Is this and this and this. Yeah, you learn a lot from The system

1:36:57 Like really bootstraps you to learn faster. So that's helping me to think more. Not to think less. It's cutting out the time it would take me. To go find all the papers by myself and then labour through them.

1:37:10 It's cut into the chase. And nourishing me intellectually. And by the way, I'm not worried about hallucination because I'm gonna interview the human scientist Anyway. So I get to cross check it all.

1:37:21 What I would never do is get the AI to write. Because Frankly, it's not very good at long form. In fact it really sucks. It's fine for writing an email, although I don't do that either, because I like writing. But it really is.

1:37:34 I've tried it once, it's terrible for anything. Longer than a bat. Eight hundred words. But even if it could do it, I don't think I would ever outsource that because that's me. This is what I do.

1:37:45 This is the thinking process I think through my writing. I come to understand what I understand and think what I think and believe what I believe. Through writing. And I'm not gonna give that up. Yeah.

1:37:59 I'm letting out A pensive exhale because I was thinking of this um a friend said to me Well I'll give him credit, Kevin Rose, at one point I was I wouldn't say complaining, observing that AI couldn't do X or wasn't very good at Y. He said, When was the last time you tried that? And I was like six months ago and he's like Try it again.

1:38:18 And so The rules will become really important as also the power of these things increases. I want to say it was the New Yorker. There was a piece in the New York, or might have been the New York Times, with some very famous, I wanna say novelist. could have been peeled surprise when earned literature, somebody at the top and they took three or four pieces of their own writing. had AI generate three or four pieces of

1:38:42 writing in their voice and gave it to professional readers. Editors and so on. And it wasn't clear. people couldn't figure out they claim that what

1:38:53 How long was the writing? That's the I knew that was the question you're gonna ask and I and I don't recall. So I wanna go back and look at that piece. So there was a story precisely like that from an economist. Writer who is very funny and also does podcasts. And he ran that experiment and it was just as you said, you know, his friends

1:39:13 who were professional economist journalists couldn't tell Which was the witty column that he'd written. Versus the equally witty ones. Which the L M that generated, and he was very pissed off with this. I take your point. I mean for now I can be

1:39:27 or complacent and say, Yeah, it only works for eight hundred words. It doesn't work for Yeah. A whole chapter which is twenty pages long. But no doubt it'll get better and better, but I still think I'm gonna cling on to the thing that makes me Me.

1:39:43 For sure. One hundred percent. I think Doing the thinking. Preparing your mind. In part asking.

1:39:52 that question, which is not an easy question, perhaps there's a different way to phrase it, but like what are The things that make me me. So you don't accidentally make sacrifices that start to A road. You're

1:40:06 Sense of self, but also sense of self worth. Preparing your mind. Sebastian, everybody should check out the Infinity Machine. It's outstanding. The Infinity Machine, subtitled Demis, His Sabis, Deep Mind, and the Quest for Superintelligence, and lest people Make the wrong assumption. This is not here's the latest and greatest in AI. It is the story of an incredible mind. A whole cast of

1:40:31 Kooky and fascinating characters. It's about a noble quest. It's about The pitfalls of entrepreneurship. It contains So many different levels. And if you want to also have a basic understanding of

1:40:47 What it is. From the ground up. that came to be colloquially referred to as AI or LLMs. This is a great book for that. It really lays out kind of the nuts and bolts and how this evolved over time in a way that I think is intelligible to non-engineers. So Everybody should check out the infinity machine. Sebastian, is there anywhere else you would like to point people

1:41:09 Or anything else you'd like to say as we wind to a close? Yeah, you stamped me on that one. I've enjoyed the conversation. I'm happy to leave it there. Thank you for doing it, Tim. It's been great. Absolutely. I'll give one more link for folks. If they want to find you on X, that's S C.

1:41:27 Not be. Well, Sebastian, thank you so much. for the time. Really enjoyed the conversation and for people listening. We will include links to everything we've discussed, all the characters. and everything else at Tim.blog slash podcast. Just search Sebastian. I'm pretty sure that uh oh actually we have Sebastian Younger. So there are two Sebastians, but if you search Maliby, M A L L A B Y

1:41:50 It'll be very easy to find this. And until next time, be just a bit nicer. Than is necessary. A little bit kinder than is necessary. To others, but also to yourself and prepare. your mind. Thanks for tuning in. Hey guys, this is Tim again, just one more thing before you take off, and that is Five Bullet Friday.

1:42:09 Would you enjoy getting a short email from me every Friday that provides a little fun before the weekend? Between one and a half and two million people subscribe to my free newsletter, my super short newsletter called Five Bullet Friday. Easy to sign up, easy to cancel. It is basically a half page that I send out. every Friday to share the coolest things I've found or discovered or have started exploring over that week. It's kinda like my diary of cool things. It often includes articles I'm reading, books I'm reading. albums perhaps, gadgets, gizmos, all sorts of tech tricks and so on that get sent to me by my friends, including a lot of podcast. guests and these strange esoteric things end up in my field and then I test them and then I share them with you. So if that sounds fun again it's very short a little tiny bite of goodness before you head off for the weekend something to think about.

1:43:01 If you'd like to try out, just go to Tim.blog slash Friday. Type that into your browser, Tim.blog slash. Friday, drop in your email and you'll get the very next one. Thanks for listening. You guys know I love wearables, I'm sure you do as well, and they're great, but they give you data. Typically they do not give you solutions. That's why I absolutely love the pod by this episode's sponsor, Aidsleep. I've been using their stuff for many, many years now. It fits over your existing mattress, tracks your heart rate with 99% accuracy, plus respiratory rate, HRV, and sleep stages. It is wild how much it correlates accurately to the stuff that you wear on you. Then the pod's autopilot analyzes your biometrics and automatically adjusts your bed temperature while you sleep.

1:43:49 with independent temperature control for couples. Also important for a domestic peace. Users report falling asleep up to 44% faster. This matches with my experience. I've experimented with all sorts of stuff, countless sleep aids, and I've yet to come across a better solution that both measures and fixes my sleep. within the same system. Summers don't need to mean terrible sleep. So go to eight sleep.com, that's spelled out. E I G H T. 8Sleep.com slash Tim and use code TI for$350 off of the Pod 5. With their 30 day trial and free returns, you can try it out risk free, so check it out.

1:44:27 eatsleep.com slash Tim. This episode is brought to you by AG1, which I have taken for more than a decade. Man, it's coming up on close to 15 years, I would say. Longtime listeners have heard me call it my nutritional insurance. And that is exactly how I use it. The news today is they just launched AG1 Pro. designed for people focused on performance and longevity. I'll be traveling soon. I'm actually packing today and I'm throwing a bunch of these in my bag to cover my bases. while I'm on the road. And I have noticed, perhaps some of you have, that it is harder and harder to put on muscle and to keep on muscle.

1:45:04 I am a young forty-eight years old and I've noticed that change. So past a certain age, You may be that age. Maintaining lean muscle becomes priority number one, and AG1 Pro is formulated to support exactly that. It includes HMB, a clinically studied compound that supports protein synthesis and helps reduce muscle breakdown, plus zinc carnosin to support the gut lining. So remember, training is only half the equation. You have to feed the machine. And as you get older, there's certain things that can help turn the dials just a bit in your favor. Recovery is where the work compounds and AG1 Pro is built to support it. It's NSF certified for sports, so what's on the label is what's in the pouch. Get your free AG1 Pro Yeti Shaker in the welcome kit at drinkag1.com slash Tim.

1:45:53 That's drink A G1, the number one. So D-R-I-N-K A-G. The number one dot com slash temp.

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