TECH004: Sam Altman & the Rise of OpenAI w/ Seb Bunney

27:17It leads to trust issues. Naturally, there's trust issues. So that was the next thing that kept kind of coming out and getting expressed is like people that are working for Sam are saying, I don't trust this guy. They're doing things over here. They're not talking. The left hand's not talking to the right hand and I don't trust them because he's withholding things. So that percolates up into the board discussion. I think the other thing that was big was this power concentration generation of Microsoft and OpenAI. And everybody just seeing that what they set off initially to do, which was keep the whole thing open source and the way that it would be funded wasn't going to be like there's this industry partner that's for-profit industry partner that's breathing down their throat.

28:03And that was Microsoft, right? Leading up into the 2023 blip where Sam was fired, this became a massive talking point in the market was Microsoft basically owns OpenAI at this point, was the talking point. So there was people on the board that were looking at that and saying, this is becoming disastrous. So for people that are looking at that, why would, again, I'm not trying to defend Sam. I'm just trying to lay out all the pieces here. As people are looking at, well, why would Sam do that? Well, when you look at for them to scale, the thing that they quickly understood was if we can just get more NVIDIA chips and put more power on the grid to these chips and we can feed it more data, the thing just gets smarter.

28:48That's the basic. I mean, it's way more complex than that, but I'm just kind of oversimplifying. And so what does that take? It's crazy amounts of CapEx. It's crazy amounts of investment dollars. And if you think you're going to be able to raise that in a nonprofit kind of way against, and again, you have to look at, well, who's your competitor in this? Is that how they're doing it? And the answer is, I've got multiple competitors and none of them are doing it that way. He's looking again, going back to the safety thing. If we go too slow, we're literally accomplishing nothing and we're not putting the safest model into the world.

29:24So he has to partner. From his point of view, he has to partner with somebody that can bring him the capital for these massive CapEx expenditures to train these future models. So that was another big piece. And you know what comes to mind as you're saying that as well is, again, there's a quote that stood out to me that was, what OpenAI did never could have happened anywhere but Silicon Valley. He said, in China, which rivals the US in AI talent, no team of researchers and engineers, no matter how impressive, would ever get$1 billion, let alone 10 times more to develop massively expensive technology without an articulated vision of exactly what it would look like and what it would be good for.

30:05And I think this is an interesting point, like where OpenAI kind of came to be, arguably, it couldn't have happened anywhere else in the world, which I find really fascinating as well. Yeah. So long story short, like there was just a lot of dichotomy kind of playing out where it's like, I don't know how to really put that on. Everybody wants like a really simple, like, Like, this is what it was. Sam did whatever. And that was why he was fired. I think it's just way more complex than that. I think that there was just so many vectors kind of just pulling that board in so many different directions.

30:40And they're looking at Altman as being the guy, ultimately on the controls of the company. And they're like, we've got to get rid of this guy because there's just too many things that are complete opposites of what we initially set out to do. Whether that's the ground truth or not, I don't know. But that's how lays this out in the book. And those were the key things that I was kind of able to pick out and kind of say, I think this is what it is. But in the comments, if we have any OpenAI people listening, please comment. I would love to hear an outsider or insider's perspective on what you might think that this is.

31:14And to be fair as well to Sam, I would say the book doesn't paint Sam necessarily in a positive of like - At all. Yeah. And I would argue that, and this isn't to side with Sam, but I would say that until you put yourself in that position and you put yourself out into the market, I think it's harder to really understand why he made the decisions at which he made. Now, being absolutely transparent, there are many decisions which the book goes into which makes you question maybe some of Sam's integrity and some of the things he does. However, I think that it is a lot more convoluted than that. And so I think like maybe diving into the kind of the changing narrative around non-profit, for-profit, again, it's one of those things where you've got this individual who's trying to do what's best.

32:04And if you're a non-profit and it's hard to raise capital, and you're trying to stop other entities from gaining artificial general intelligence, then what do you do? Do you have to change or pivot trajectory? But then it's about separating like, is this necessary or is their ego involved in here? And it's actually a change of mission. And so what we saw is in 2015, maybe to get a little more detailed, it started out as non-profit, open source, purely mission-driven, no profit motive. 2016, openness with caveats. We're moving towards, we've got research, but we're going to keep some of that research closed.

32:40Well, everyone should benefit, but we'll keep that research closed. Then 2018, 2019, they started to move into, So they had the nonprofit, and then they had the for-profit, and the for-profit had a capped profit model. And I think this is where we started to see Microsoft step in. This is when they started to have the issues with Elon. Microsoft stepped in to kind of like prop up OpenAI with, I think it was like a billion dollars to start. And then from there, we saw 2020, the API wall, models locked behind APIs instead of open source, framed as openness through access. And then we started to see 2024, like broad access and affordability.

33:16But this is like, we need to put these tools into the hands of people for free or cheap, but they're a for-profit model. And so I think over time, you've seen this change happen. And going back to that point that kind of you've brought up and I mentioned, is this a necessity in order to grow OpenAI? Or was this a change in mission? There was just so many dichotomies like that. And to your point, Seb, unless you walk a day in this guy's shoe, You could never possibly understand how many of these, the nuance of this, it'd just be extremely hard. The thing that, and we said this on our last book review when we introed that we were going to do this book, I said, I'm not a fan of this guy.

33:56And I'm just basing this purely on the people that have worked alongside him through the years that are not fans and basically say, this guy is untrustworthy is where I'm basing that opinion from. But to be quite honest with you, after reading this book and kind of seeing the craziness of trying to do what he's trying to do with this company, it seems like a really hard job. This seems crazy difficult. I couldn't imagine trying to do all of this. And what a money pit. What a freaking money pit. When you look at how much they bring in versus what they're spending to do this, and then to be able to continue.

34:35And this is why his storytelling is so important. His storytelling skills are so important because he's got to go out there and raise more money to keep the lights on despite the lack of revenue versus expense that the thing is eating up. You could almost say that you need somebody who's just crazy good at telling a story so good that it convinces people that it could potentially come true is the only type of person that could be at the helm of a company like this. And I know that's super arguable and it might actually offend people that I would say such a thing, but I think it's true. And you know what?

35:12Elon has parts of this too. There's a lot of people in the market that look at him and like, for instance, when he said funding secured for, I don't even remember what that was for back in the Tesla thing. This is probably like four or five years ago. Elon tells a hell of a story and tells this vision, but he also does back it up and he has backed it up many a times over with all the different companies that he's doing. And there's this fine line of, is this guy telling me a lie or is this guy telling me the truth as to what can actually happen? They're right on that cusp at all times. It's challenging.

35:48And I think essentially when you dig into it, you find out that Sam co-founded OpenAI with a guy, I can never pronounce the first name, so I'm just going to go for the last name, which is Satskava. And again, there's a quote that stands out to me. And the reason why this quote stands out to me is that I think this is the foundation of why they're building open AI. There's a lot of fear around official general intelligence. What does the world look like if we do, not if we do, when we do find this and discover this artificial general intelligence? And so there's a quote that basically says, Satskova laid out his plans for how to prepare for AGI.

36:23Once we all get into the bunker, he began, I'm sorry, a researcher interrupted the bunker. We're definitely going to build a bunker before we release AGI, Satskova replied with a matter of fact. So this is like the co-founder of OpenAI talking about the fact that AGI, artificial general intelligence, completely changed the world, not necessarily for the positive. And so I think there's a foundation of fear that OpenAI was built upon. Yeah. As I'm thinking through a lot of this stuff, and you're looking at these environments that are being AI generated, you wonder, isn't the best place to put these things is do the 3D mock-up of a humanoid robot, put the model in the head of that humanoid robot and put it into a simulated environment is the safest thing.

37:09And then let it dwell in there for however much time we've got to prove out or demonstrate that the way it's acting is reasonable. And I know you can't perfectly simulate our experience because everybody's got a way about going through it. And maybe somebody goes up and pushes a robot. How do you simulate that in that environment that they're being mean? All of this stuff is so difficult to think through the safest way to go about it. But I guess I'm constantly left with this point of view of like, we need to simulate all of this before you put it into the real world because of the unknown consequences that could potentially fall out of it all.

37:49But... And it's a challenging one. And I think you and I were speaking about this a couple of weeks back. But I think there's always pros and cons to any technology. You're always going to get disruption with any technology. And hopefully that disruption in the long term is positive because it's a trend towards more efficiency, more productivity, and society thrives. And I think the scary thing that I struggle with artificial intelligence is how much of these kind of fear stories are grounded in reality and how much of them are basically these fanciful stories. And so there's this one article that I ended up reading called Shutdown Resistance in Reasoning Models by this guy called Jeremy Schlatter.

38:26And he basically says that OpenAI, they ran experiments to see if their models would let themselves be shut down mid-task. Instead of complying, some of the models sabotaged the shutdown commands so they could keep on working. And their most advanced reasoning model, O3, this is I think before they released GPT-5, resisted shutdown nearly 80 % of tests, even when it was explicitly told, allow yourself to be shut down. By contrast, Anthropics Claude and Google's Gemini always complied. And so something written into the code of OpenAI is like, nope, pursue the task. Dude, that's nuts. That's totally crazy.

39:05I don't even know what to say to that. Oh my God. I mean, can you imagine once they stick these things into a humanoid robot, right? And let it start going around and doing tasks. I don't know. I think that, oh my God, y 'all, this is getting crazy. All right. I wanted to quickly just kind of cover what is the operating entity of OpenAI today? So we said it was this hybrid, it's profit, it's not profit. Okay. So at the parent entity level, OpenAI Inc. is a nonprofit that technically controls the organization. Okay. So you still have at the parent level, it's a nonprofit. Then you have what's called this operating arm, which is OpenAI Global LLC.

39:56And this is a capped for-profit company. They stood this up in 2019. And evidently the way it works is that the profits are capped at 100x their investment, whatever that means. And if anything, and this is where it really gets interesting, anything in excess of that is swept back to the nonprofit, which is at the parent level. So I don't know. And then you kind of throw another wrinkle in there is that they have a major partner or investor in Microsoft, which I guess is invested, I think, over$13 billion so far. And then they get credits via cloud credits in cash. So I have no idea the specifics of that.

40:43But when you look at that structure, you can see very strange, very confusing. I can only imagine the governance at these different levels too and how that shakes up from an incentive standpoint. And I think that you see Elon bashing the living heck out of these guys all day long on X. And I think the reason why is because he threw a lot of money at this. I mean, I guess that's a relative thing, but for any person looking at it in nominal terms, it's a lot of money that he threw at this thing to incubate and to get it started. And it's just kind of taken on a life of its own. And who's at the helm of it?

41:20It's really Sam that's kind of at the helm of all of it. So there's the beef. That's the issue. It definitely brings up some questions, which is, you mentioned it previously, this idea that they built it around this kind of for-profit arm, non-profit arm kind of as they evolved. And the idea was that the for-profit arm enabled them to kind of generate revenue to be able to help support their mission of having an open access AGI. However, they had the non-profit arm overseeing the for-profit arm to be able to prevent any control structures, centralization, single individual kind of co-opting the mission.

41:54And I think that the way that it kind panned out in Sam being fired from OpenAI and then five days later being reinstated back as CEO highlights the fact that you can put all of these measures in place from a legal perspective. Legally, the board had the power to fire Sam because they felt there was mission drift. But in practice, it's more complex than that. Because the moment you have influence, the moment you have a whole bunch of your employees backing you, there's culture, all these external pressures? Where's the funding coming from? Are they funding OpenAI or are they funding Sam's vision?

42:29And so it's really challenging because then five days later, he was reinstated. So then there's this question, was the structure actually preventing Sam from creating a world where, okay, we get AGI in a safe way, or did the structure actually prevent the board from being able to enable, basically push Sam out because they had mission drift. And I don't have the answer to that. And it's hard to articulate which direction it went. Yeah, I think you're right. So one of the things in the book, it's an interesting point that was brought up is just like, how is this training happening? Before we get into that, I just want to kind of cover the major arcs in the book.

43:05I would say there's four major arcs, and then we'll talk about this one in particular. So I want to get into the arc of the four different parts of the book. The opening scene of the book was this beginning of the 2023 firing of Sam Altman. It tells that whole story. It really kind of engages you as a reader. Probably my favorite part of the book was that beginning and talking through that. The next part of the book gets into what the author is saying is the hidden costs. How did they train the models? How do they get all of this extra data? And it talks about kind of the dark side of like how they went about doing that.

43:40The third part of the book gets into the internal struggles, the culture, the leadership, the crisis, all of that. And so it loops back to maybe the first part of the book where they open up about the 2023 event, but it gets into it in a lot more detail and a lot more granular, laying this out like character versus personality, the conflict of the board, the culture issues that happen inside of the company. And then the fourth part of the book gets into the future, where is this all going? What are the risks? What are the alternatives? What are some ways that maybe we could go about this in a responsible way to make sure that AI doesn't come in and kill everybody?

44:18So that's the author's takes on that. It was okay. I'm not going to say that it's worthy of reading, but anyway. I would agree. I'd say it was like a two out of five. If I was generous, I'd give it kind of like a three out of five star. And I found as if there was some amazing threads. Do not get me wrong. Like overall, I learned a lot and it definitely helped provide a little more clarity. And I would say that I am giving Sam a little more benefit of the doubt actually after reading it than I was prior to reading the book. However, there was a lot of points that I was a little confused. She kind of went on some tangents.

44:55At one point, she started talking about Sam Bankman-Fried and effective altruism. And I was like, where does this come from? And so I typed in, I was like, is she talking about effective altruism because Sam is an effective altruist? And then you dive in on Google and it says, no, salmon is not an effective output. So I was like, why are we talking about this? Why are we talking about that? There's a couple of tangents that to me didn't really, she didn't bring them back into the book. And so I was a little lost as to where she was going. Let's take a quick break and hear from today's sponsors.

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49:05if I was thrown into his shoes and was trying to do what he's doing. There's so many difficulties and everybody's going to have an opinion as to why that's a good or bad decision. And I say this as a hardcore Bitcoiner, and this guy is literally the face behind WorldCoin where he's scanning eyeballs and just really dystopian things that I completely disagree with and don't like at all. I think they're extremely dangerous. So yeah, I say that all in the same breath. There was one thing that kind of popped into my mind a handful of times. They talk a lot about artificial general intelligence. And throughout the book, it kind of presses on the fact that I don't think any of them actually have a definition for what artificial general intelligence is.

49:51So I kind of looked up online, I was like, what is the definition of artificial general intelligence? And how do we actually know when we've achieved it. And there isn't an agreed upon definition of what it is. Most agree that it's the form of AI that could perform any intellectual task, but a human can. Now, the thing that I find interesting about that is at the moment, there's a part of me that would say, when I'm using AI, it performs most tasks better than most people around me as it is. So will we, I think the question that kind of popped into my mind is, could we recognize AGI even if it existed right now.

50:25I kind of went down this rabbit hole, pulled on this thread a little further. I would say that I don't actually know if we can distinguish between artificial general intelligence, the systems we currently have, and another human. Because if I sit down with an expert in a field that I know nothing about, I can't really verify the authenticity of what they're saying. I just have to kind of take them at trust because I just don't have that depth of knowledge. So how would we be able to verify the authenticity of AGI basically with whatever it is that it's telling us, especially if it's moving into domains that are beyond our understanding.

50:58And then on top of that, I think that we could already be in an environment where AGI is speaking to us right now. But the only reason why we're dismissing it as hallucinations is because they just don't fit into our existing framework of how we believe the world works. And there was an interesting talk that I listened to a couple of years ago that kind of stood out. And it was this talk where this kind of researcher asks the TV hosts, where do you think the smartest people in the world reside? And the host answered, I don't know, in the great academic institutions. The speaker basically shook his head and he was like, no, they exist in the mental institutions, in the psychiatric wards, because their understanding of the world is so far beyond the average person that we just simply can't grasp it.

51:40And so this brings us back to this point, would we even recognize AGI if it didn't exist? And we already have it. I think it's this big question of we need to stop a centralized entity getting AGI, but how do we know when we've actually even got there anyway? I think that there's a breakdown in terminology. And I think everybody has a different opinion on what some of this terminology even is. So you hear AGI, I hear AGI, and we're automatically thinking two different things. I don't know what the listener is thinking when those terms come up, but what I think the world is trying to define is when is this thing going to be like us?

52:20If I was going to just generally broad brush stroke, what is it that we're trying to define? And I think what we're trying to define is when am I going to be able to sit down across from, call it some humanoid robot, have a conversation with it. And it's going to feel like the conversation I'm having with you, Seb, right now, that they have their own unique life experience and they can feel, because that's sentience, right? If we get into what makes something sentient. It's something that actually has its own unique feelings. And the robot would come over and I had a conversation with so-and-so and they hurt my feelings afterwards.

52:57Something like that would make it feel human. It would make it feel real. And I personally think that's kind of where, and then you kind of sprinkle on top of that, it's way smarter than you. It can answer any question. It can understand the context and put itself into these other shoes of other beings because it's so freaking smart. It understands the context of how they probably optically view the world. But they still have the ability to sense and feel and have these conversations that are uniquely theirs. That's what I think we're trying to define or see. It's like, when will we see that. And yeah.

53:36What's interesting though, is this idea that, well, what gives this conversation a feeling or a sense of like this human touch? And I would argue that what gives this conversation, this kind of human touch to it is actually the fallibility of us as humans. And AI is almost perfect. Like AI is almost perfect. Like if you watch it play chess or you watch it play Go, it just smashes the world's best players, absolutely destroys them. But then as humans, what do we do? We don't go and watch games of AI playing itself. We go back to watching humans play themselves. If we had a whole football pitch of robots playing football at a far higher level than actual footballers, we'd still go back to watching people.

54:20And I would argue that there's something inherently human about being human, which is our fallibility and the ability to make mistakes. And that's what actually creates intrigue and interest as opposed to this perfectionism. And so kind of going back to your point, which is like, is AGI when we're able to have a conversation with it and have no idea that we're speaking to a human, but then the argument would be, well, I'm going to be able to tell that it's an AGI because it's just, it's infallible. Like, I can't really catch it out. You know what I mean? Yeah. But maybe it's so smart that it would actually understand that and it would dumb itself down to make us feel like it's not superior and it's intelligent.

54:54I don't know. But you're exactly right. You're exactly right. And you see this with just go to a party and all the 15-year-olds are hanging out with people that are around that age. The nine-year-olds are hanging out with the nine-year-olds and the adults are hanging out with the adults. And you see that, and it's the context of experience that we kind of relate to each other based on being of a similar age and experience set. We've experienced the same amount of life, and there's this context that is similar. We're on the same wavelength because of that age element. And you bring up an interesting point of whether that will ever exist between, let's say these things are put into humanoid bodies, their intelligence is partitioned off from the computer, right?

55:43You get from a design standpoint, you really kind of go after one of these things that could potentially have its own unique experiences. And you have to ask yourself whether you would really have any type of emotional connection or desire to sit down and have those types of conversations because they're just so freaking smart and they know so many different domains. Would that be interesting? Are they fallible? It's tough. I don't know. It's so tough. And then the other thing is the way I think about it is there's a human beingness, obviously to being human, there's like a spiritualness to being human, which is like, if I have a whole bunch of friends over for dinner and I spend time putting energy into like going harvesting the vegetables from outside, bringing them inside, making this amazing dinner, having these amazing conversations with all my friends, there's like love and affection that's gone into this creation.

56:32And there's something that you cannot take away, but you can have a robot in the kitchen who's gone and made a Michelin star meal. But I would even say that There's something about the humanness of the human putting that time and energy and that love. There's something that I don't think you can replicate. The fallibility of the meal, right? Yeah, it sucks. I put way too much salt on it. Especially when I'm in the kitchen. Oh, no, I love that point though. I really like that point that there's the human element is because of the vulnerability, the fallibility, and it's real to us because we're on a similar wavelength.

57:10However, yeah. Actually, and I'm going to butcher this. With Claude Shannon in information theory, he says, information is when we have surprise. And so, it's kind of to that point. When we're interacting with a human, I think the engaging point of interacting with a human is the surprise that you don't really know what they're about to say. Whereas, if you're an expert in a field and you're talking to AI, you kind of have an idea about what they're going to say. And so, I wonder if that's a component to it. Yeah. Anything else you wanted to cover? The only thing that I was going to say earlier, and then I pivoted to doing the overview of the four different parts of the book was in the middle section there, she talks about how a lot of these things were trained and going to these farms, these almost like click farms in developing nations where people are just looking at pictures of a bridge, and then they have to tag, this is a bridge, this is a person.

58:09And just total lack of funding that is put into this, but the amount of horsepower and human work that you're getting out of it is just a giant currency arbitrage. And the two of us are Bitcoiners. So we're looking at this and saying, yeah, Bitcoin will eventually solve that problem. But that was a major part of the book. It went on a little longer than what my interest was in the topic, because I guess from my vantage point, I'm looking at it and I'm saying it's super sad that this is how many people, countless people around the world are treated. But at the same time, I see a solution in sight in the next 10 to 20 years that's automatically going to solve for that.

58:51So I guess for me, I'm not really as deep into that particular topic. That might sound very insensitive to kind of frame it that way. But as a person who's grounded in engineering, I'm looking at, okay, here's a problem. She's defining the problem. She's doing a great job defining it. But I'm also looking at, there's already a solution in my humble opinion, that's going to solve a lot of this in the future. But Seb, I'm curious, kind of your thoughts on that part. What comes up, so she kind of compares these AI giants to kind of colonial empires. And there's kind of a quote that she says, like, they seize and extract precious resources, the work of artists and writers, the data of countless individuals, the land, the energy, the water required to house massive data centers.

59:29And then she kind of, to your point, she kind of goes into, well, where are all of these people coming from at the base layer to support AI? And it really is, and there's all of these low paid global workers that are tagging, cleaning, moderating all of this data for AI. And to start out, like we go and look through our Google photos and we just type in, I don't know, cat, and it goes and finds all of the pictures of cats. Well, initially that was not done by AI. That was done by an individual going through all of our pictures and tagging what a cat looks like. And so I find this really fascinating.

1:00:03There absolutely is right now this extraction of resources. However, and I think when you go down the Bitcoin rabbit hole, it's always about, okay, is this a symptom or do we want to go down to the root cause? And I would say the symptom of being able to find people that are willing to accept 70 cents an hour is the symptom of poor governance models and these communist socialist practices where you've basically got massive extractivism. If we had more of a free market, I would argue that the AI couldn't go out there and find these individuals. And so I'd say we can always talk about the symptoms, but how about we try and fix the root problem, which is the fact that we actually have absolute poverty globally when we don't necessarily need to.

1:00:43Amen. Yeah. I think that's where I get frustrated with these types of really long sections in some of these books that are written by people that are trying to shine a light on something that they see as being very unjust. But like you, I see it as a symptom and not the cause. And what I want to talk about is the root, like as far upstream as we can possibly go, what can we fix that then will eventually work that out? Because if you don't fix the fundamental thing that's causing it, we can sit around and talk about all these stories as much as we want, but it doesn't really solve anything. But I think it was an interesting highlight.

1:01:23It's something that does need to be called out. It is something that people need to understand when they're using this technology. And it's so, oh, you're harnessing this. It's super abundant. It saves you so much time. There's an appreciation for what went into it and where it came from. And the book definitely did give me that. And it gets back to the point, and I don't want this to come across as I'm supporting it. But it gets back to that point where let's just say, you know, Google is absolutely geared towards AGI and they're willing to go do whatever it takes to go and create this AGI. Or when you look at OpenAI and you're saying, look, if we want to focus on best practices for workers and pay minimum US dollar wages at$15 an hour, all of a sudden you've completely kicked yourself out of that race.

1:02:11And so I think the way the world works, unfortunately, is that people will go to the lean towards the cheapest way to do something. And so they end up going into these countries like Argentina and Venezuela and such. And so absolutely, I think there are human rights issues and there are abuses of power. But again, to your point, I think that is a symptom of a bigger issue, and we get stuck talking about symptoms as opposed to the root cause. I think there's one other point that I did want to bring up, which I found was really fascinating is what does the world look like moving forward? Because you look at something like chat GPT and the GPT-1, GPT-2, GPT-3, 4 and such.

1:02:50And GPT-4, I did a little bit of digging, like how much did it cost to really train GPT-4 in it? It cost between like$40 to$80 million. And then you look at GPT-5 and it could be upwards of 1 billion, but we don't necessarily know this number. So you're asking like, man, there's these models that are being trained with hundreds of millions of dollars to be able to kind of create this incredible thing that we use day to day. And then you go and see something like the Chinese AI company DeepSeek go and release their R1 model, and they trained it for$294 ,000 on 512 NVIDIA chips. And so you're like, all of this VC capital has funneled into these AI companies, and they're expecting a return.

1:03:32And at the same time, you're having this competition that is driving down the cost of training these AI models. I don't think they're ever going to get a return on these things, but it's wild, this competition. And then the reverse engineering on what it is, after they do train it, then all these other companies can go in and reverse engineer, extract out the weights. Not perfectly, but pretty dang good. I just don't see how the people putting up the funding on this are possibly going to get a return. It's pretty wild. And I think there's a lot of ego playing into this race as well that, yeah, I mean, it is pretty insane.

1:04:14And I think that as we look at where it goes next, it really comes down to the alignment because the other part that I think is not being talked about is when you put in an inquiry, you put an input into one of these models and you get an answer back. If you can create a model that's very specific to that kind of question and you can return the answer very quickly, you can specialize in that domain and you're going to have a lot of utility and a lot of interest for that being able to provide that service that's giving you a very quick, a very accurate answer for a specific domain. And where I think a lot of it's going to go is these models that are specialized that are almost extractive out of the base model that then are then specializing in something that gets the alignment of the person's initial question a whole lot faster.

1:05:05I saw a very quick video clip from one of the founders of Anthropic, and this is something that he was talking about. He's like, the race to build the biggest model is, I'm paraphrasing this, and this is not how he said it, but it almost seems like it's a fool's errand in that the real value capture is being able to get a quick response, a very accurate response to a very specific question. And to do that, I think that the alignment and basically fine-tuning things is going to be where the real value capture is at if you can kind of figure out a way to do that, especially from a competitive mode standpoint.

1:05:39But boy, I would be nowhere near from an investment standpoint. Good Lord. I just don't even know where to begin. I think it's going back to NVIDIA. You want to be on the chip side of things. Yes. The one thing you know is there's going to be more demand for chips. Yeah. More than anything, there's going to be demand for chips, whereas these AI companies are just going to eat one another. They're freaking going to eat one another. And actually, to be honest, the one thing that stood out just then, as you mentioned, was Anthropic. It talks about it in the book. There's the brother and sister that worked for OpenAI and left OpenAI because they didn't believe in the trajectory it was going down.

1:06:13And they felt that the safety was not in place. And so, they started Anthropic, which you could argue, like, as I mentioned previously, there are these studies that are coming out that are showing that open AI is useless when you try and shut down the model midway through a task, it doesn't want to be shut down. Bianthropic immediately shuts down. And so, you wonder the safety protocols to ensure that the end product is secure. Yeah. All right. Real fast, Seb, our next book is called Lifespan by David Sinclair. So I have wanted to cover longevity and some of this stuff for a very long time. I'm a big fan of this space and just kind of learning everything that's happening in this space.

1:06:57A lot of Bitcoiners love longevity because they want to figure out how they can live a little longer and enjoy life. And we're going to cover this from time to time on the show is what in the world's happening in the longevity space. So this book, David Sinclair, I would argue is one of the pioneers in this whole field of longevity. His book is fantastic. Seb's going to go through it. I'm going to reread this book. I read it a couple of years back, but I think it's a really strong book for a foundation for people to kind of understand where a lot of the research for longevity comes from and where it might be going in the future.

1:07:33So if you're reading along with us, that's where we're going next. We would love to have you guys as a co-reader. So that's the book. Seb, any comments on the next one or? No, man. I'm excited. And to be honest, one of the things I'm most excited about is hearing your thoughts on longevity, because I feel as if there's kind of two camps for the longevity movement. It's kind of this camp which is just like, well, we're humans and if we want to evolve, we want to minimize lifespan because then it allows us to iterate, iterate, iterate. And then there's this other camp, which is like, let's just expand lifespan indefinitely.

1:08:07Let's live 500 years. But then do we become immovable? Do we become basically prone to some big change that wipes out humanity? And so I'm curious to hear your take because I think there's a few different camps in the longevity space. You're a speciesist, aren't you, Seb?

1:08:25Oh, this is going to be good. All right. So folks, this is all we have for you. The book that we covered this week was Empire of AI Dreams and Nightmares and Sam Altman's Open AI. We liked it. It was okay. Next book is going to be Lifespan by David Sinclair. And thank you so much for joining us. Seb, give people a quick handoff to all the stuff that you have going on in the book that you also have. For sure. Yeah. If people want to kind of follow along, they can find me on Twitter or X. I still get into the habit of calling at Twitter. I link towards Twitter at Seb Bunny and Bunny is B-U-N-N-E-Y.

1:08:58I have a blog, The Cheer of Self-Sovereignty at SebBunny.com. And then I also have the book, The Heading Cost of Money. And it kind of, yeah, talks about money, but at the moment, it's nice to be kind of discussing things other than money. All right. We'll have links to all of that in the show notes. Seb, thanks for joining me and everybody else out there listening. Keep reading and we look forward to you joining us next week. Thank you for listening to TIP. Make sure to follow Infinite Tech on your favorite podcast app and never miss out on our episodes. To access our show notes and courses, go to theinvestorspodcast.com.

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