Navigating the AI Revolution: Who Wins, Who Loses, and How to Prepare | Emad Mostaque

Artificial intelligence is accelerating at a pace few could have anticipated—and its impact on the value of human labor may be more profound than most realize. In this thought-provoking episode, I sit down with Emad Mostaque to confront the economic and existential shifts already underway as AI rapidly outpaces human cognitive abilities. Together, they discuss breakthrough AI achievements such as solving advanced mathematical problems, the coming transformation of the workforce, and the urgent need for individuals and societies to adapt. What does the future hold when digital agents can perform most jobs better, faster, and cheaper than any human? How should we prepare for a world where ownership, community, and personal identity must be redefined? Get ready for a candid, wide-ranging conversation about the radical opportunities and disruptions AI will bring over the next decade—because the clock is ticking, and the sandpile of the old economy may be on the verge of collapse. I’m Tom Bilyeu, and welcome to Impact Theory. Sign up for my AI Masterclass: https://tombilyeu.com/ai-masterclass?utm_campaign=TBS-Livestream&utm_source=youtube&utm_medium=social Check us out wherever you get your podcasts: Spotify:https://open.spotify.com/show/1nARKz2vTIOb7gC9dusE4b?si=a8daffd2bf1f48fd Apple: https://podcasts.apple.com/us/podcast/tom-bilyeus-impact-theory/id1191775648 Do you need my help STARTING a business? Join me here inside ZERO TO FOUNDER: (https://tombilyeu.com/zero-to-founder) Get the exact systems, mindset shifts, and principles that built a $1B brand delivered straight to your inbox every week. Subscribe for free (https://tombilyeu.com) Check out our Video game - Project Kyzen: (https://projectkyzen.io/) Catch Me Streaming on Twitch - (https://twitch.tv/tombilyeu) Link to IT discord: https://discord.gg/TZKJ2etPbT Tom's Favorite Things List: https://amzn.to/41Ftt7e For Business inquiries: [email protected] Follow Emad Mostaque: X: https://x.com/EMostaque Follow Me: Instagram: https://www.instagram.com/tombilyeu/ Tik Tok: https://www.tiktok.com/@tombilyeu?lang=en Twitter: https://twitter.com/tombilyeu YouTube: https://www.youtube.com/@TomBilyeu Thank you to our sponsors: Tailor Brands: Check out Tailor Brands to get started with your business today: https://bit.ly/TailorBrandsSept Quince: Free shipping and 365-day returns at https://quince.com/impactpod ElevenLabs: Book your demo at https://elevenlabs.io/impactpod Cash App: Download Cash App Today: https://capl.onelink.me/vFut/v6nymgjl#CashAppPod *Cash App is a financial services platform, not a bank. Banking services provided by Cash App’s bank partner(s). Prepaid debit cards issued by Sutton Bank, Member FDIC. Cash App Visa® Debit Flex Cards issued by Sutton Bank, Member FDIC, and The Bancorp Bank, N. A., pursuant to a license from Visa U. S. A. Inc. See terms and conditions for the Sutton prepaid card, Sutton debit flex card, and Bancorp debit flex card. Cash App Green features, Savings, Direct deposit, Round ups, Overdraft coverage and Discounts provided by Cash App, a Block, Inc. brand. Visit cash.app/legal/podcast http://cash.app/legal/podcast for full disclosure. Surfshark: Go to https://surfshark.com/TOMBor use code TOMB at checkout to get 4 extra months of Surfshark! Incogni: Take your personal data back with Incogni! Use code IMPACT at the link below and get 60% off an annual plan: https://incogni.com/impact See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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• 1:39Speaker 02

  Good to be back.

• 1:40Speaker 01

  Dude, AI is moving insanely fast. You've said that compared to AI, that humans are going to see their value go negative. What do you mean by that?

• 1:50Speaker 02

  Yeah, I think it's, I said precisely the value of human cognition. We've got about two years before it goes negative. We're the dumbest people on the team. You know, we're slowing everyone else down. In fact, I think, remember, we had our first podcast three years ago. And I said it was going to be three years until everything changes. And now this is the point of change.

• 2:07Speaker 01

  Now, do you think that we've actually hit that point of change to make good on that statement?

• 2:12Speaker 02

  I'm a mathematician. Navier-Stokes problem was solved, you know? Like you've just seen another genetic breakthrough. You've seen competent AI that doesn't make mistakes. Hollywood level video, I think now is the takeoff point. And again, we've got one or two years before our AI teammates look at us with disgust and be like, man, that Ahmad. You know, he's always the dumbest things.

• 2:32Speaker 01

  The first three years were basically getting up to the point where it could have the Navier-Stokes type breakthrough.

• 2:39Speaker 02

  Yeah.

• 2:40Speaker 01

  Now it's going to be where we're racing over the next couple of years where we're, right now, we're able to use it. We're able to be meaningful in the mix, but that is going to be a declining arc. That somewhere in the neighborhood of two years, it's, we're the guy that they're basically paying to leave the team.

• 2:55Speaker 02

  Yeah, like we're, the team is more efficient without you. Like the technology and the models have got to that human level performance. They're about to outstrip us, but the harnesses.

• 3:07Speaker 01

  Why do you say they're about to outstrip us? What, what is it?

• 3:09Speaker 02

  If you look at the outputs, you've had AI slop for the longest time. Like you can tell AI writing, for example, you know, like it's like you're half right, half wrong. And the part that's half wrong is the interesting one, you know? It's not X, but Y.

• 3:23Speaker 01

  Yeah, God.

• 3:25Speaker 02

  There you go. You know, like you pick up the slot. That's all disappearing with the next generation of models. The next generation of models don't make mistakes. Like as a mathematician studying maths at Oxford, I was better than the AI at generalized understanding of math until maybe a few months ago, and then it's stripped ahead. And now it's solving the hardest math problems in the world. In terms of just everyday stuff, end of last year, we had the open claw phenomenon, right? Everyone was like, oh, look at this, and let's buy some Mac minis and things like that. And then they realized it's actually kind of garbage. It makes lots of mistakes, you know? It likes to delete all my stuff.

• 4:00Speaker 01

  And the open claw moment was agentic AI. It will go do things on my behalf.

• 4:06Speaker 02

  It go do things on your behalf. Now what we have is muse and instinct and things like that.

• 4:11Speaker 01

  For people that don't know them.

• 4:13Speaker 02

  It's like actual AI agents that you just message and they go and book you restaurants at the coolest tables or they like check your kid's school activities. They're like a really good PA. You know, but they actually are good. They don't drop the ball. So you've gone from AI dropping the ball, hallucinating, writing like crap, to all of a sudden, it's good, actually. It's competent. And the next level is when you get 10,000 of them together, like OpenAI did, solving this incredibly difficult math problem.

• 4:41Speaker 01

  Navier-Stokes.

• 4:42Speaker 02

  Navier-Stokes, yeah. So there were seven millennium prize problems, a million dollars each. Humans solved one. It solved the second one.

• 4:49Speaker 01

  Did it actually solve Navier-Stokes or just progress it?

• 4:52Speaker 02

  So the prizes have certain conditions and Navier-Stokes had four different conditions that could win it. They solved two of them. The other two are still to be solved, but a solution of those two counts as everything. But it's not the whole like Navier-Stokes problems that we have. It's a specific set of things. So they won the prize. You know, there's still more to solve in math, but the question is.

• 5:15Speaker 01

  Cause I don't, I think it's currently listed as active, meaning we're assessing. We haven't fully decided yet. And there was obviously the big debate between was it the humans that did this or was it OpenAI?

• 5:28Speaker 02

  Yeah, so this is a problem that I've looked at and actually studied formally and things like that. It takes two years to actually accept it.

• 5:37Speaker 01

  Whoa.

• 5:37Speaker 02

  That's the Clay Institute thing. So it needs to be published in a journal that needs to be accepted. And two years need to go by with people beating it up. What OpenAI did is they put 10,000 agents for 88 hours on it, which is 100 years of talented human time. And then they had a formal proof. So like you can click a button and then it just checks it formally and says right or wrong. So it's highly unlikely to be wrong. Like humans can't do that because it's so freaking exhaustive. Like there's a theorem called Fermat's Last Theorem. The official proof of that is 127 pages. Anthropic formalized that proof. It's 13 million lines of code.

• 6:17Speaker 01

  Oh my God.

• 6:18Speaker 02

  So that's another thing. Again, for us mathematicians, this is a bit existential because we're like, what do we even do now? Like some of my buddies who do math PhDs are like, these formal proofs are coming out. Like I don't even know what to study next. In fact, OpenAI a couple of days ago said, we have solved 100 of the top mathematics problems, but we're holding them back for now because we don't want to make the mathematician sad.

• 6:41Speaker 01

  That seems very strange, but before we get to that, I want to push on the Navier-Stokes thing for a second. So that really, it's a delineating line for you in a way that I don't think a lot of people understand. I think, and correct me if I'm wrong, that this comes down to what I think of as the Jan LeCoon thing. So Jan LeCoon is like LLMs just aren't the architecture that's going to work. It's always going to be merely a vomit back of patterns that we see humans do. We're limited by what humans have figured out. So is it that you think Navier-Stokes was novel, was not something in the training data? And therefore it expressly proves that theory wrong? And we're seeing now that it can think beyond its training data?

• 7:24Speaker 02

  Yes. As of the last month and a half, the models have gone beyond their training data definitively. So before Navier-Stokes, OpenAI released 10 proofs of famous math problems. And I can say at least two of them, Con's Conjecture, being the main one, is definitively novel, elegant and never seen before, the way they did that proof. Navier-Stokes, it did it in a bit of a more mechanical way, but again, in an incredibly novel way. It's quite difficult to read because it's like AI slop claudism when you're reading it. So it took like me, it took three days for me to even read the paper, you know? And I haven't gone through the formal stuff. But I've talked to enough of my mathematician buddies now, because we discussed this, to say,

• 8:06Speaker 02

  yeah, human could have done this, given 20, 30 years. So the first millennium prize problem, the Ponqueri Conjecture, was solved by Gargory Perelman. Have you heard about this story?

• 8:17Speaker 01

  No.

• 8:18Speaker 02

  Gregory Perelman was a very famous mathematician and he just dropped off the grid for like 10, 20 years.

• 8:23Speaker 01

  Yeah.

• 8:24Speaker 02

  Then he emerges on archive. He drops the proof of Ponqueri Conjecture. Everyone thought it was a topology problem. It turned out to be a partial differential equation problem. And it's like, again, 130 pages of proofs. And then they were like, we're going to give you a million dollars. This is fantastic. Come on, I think it's like, no. Like why? The proof being right is enough. Don't contact me again. And then he dropped off the grid again.

• 8:45Speaker 01

  That's so wild.

• 8:47Speaker 02

  Which is the boss move, right? Like that's what you do. And so this one here, again, it reminds you of Perelman and the way that it's done. And it's clearly like way beyond average PhD level. And the fact that they could scale it by attacking it with a 10,000 means that these types of math problems are formally verifiable. And you can just literally chuck compute at them.

• 9:08Speaker 01

  So is it that it's going beyond the human ability? It's reaching beyond its training data? Or is it that it's learned from humans and then it can just throw 100 years of compute at it over a weekend?

• 9:21Speaker 02

  I think it's both now. Starting August 29th, OpenAI had a new type of model training. So they had an existing model that they figured out a trick with that made it go from 10% on frontier math, a benchmark to 60% overnight. And just started solving these math problems one after the other. It's like if you use the new Opus, all of a sudden it can do amazing 3D scenes and photorealistic water and like generate entire songs. Or Astra is the same, like it suddenly got eyes. It suddenly had a sense of positioning and taste. So we've kind of reached this point where these models have suddenly gained another capability, which the capability conceptualize.

• 10:08Speaker 02

  And so there's something internal going on within them. We've seen this previously in the video models where the video models had terrible physics. Like when we first came up with the first video models, we were like, do gymnastics.

• 10:20Speaker 01

  That was hilarious, yeah. Their spines would just spin.

• 10:23Speaker 02

  Yeah, Will Smith eating spaghetti. Now they do it flawlessly. And they've learned physics. So you can say like, I want a boat made of sugar cubes and a boat made of concrete and a boat made of wood. And it will actually accurately show them dropping into the water.

• 10:39Speaker 01

  As in the sugar cube will melt or?

• 10:41Speaker 02

  The sugar cube will kind of float and then it'll melt.

• 10:44Speaker 01

  Huh.

• 10:45Speaker 02

  Again, it's learning these things. It's learning representations and something has happened in the last few months. That has allowed the math breakthroughs, that has allowed the gaming breakthroughs. Again, like a year ago, all the websites that Claude made looked like the same, like the weird purple. Do you remember that?

• 11:03Speaker 01

  Yeah, yeah.

• 11:04Speaker 02

  Now it can do like crazy 3GS dynamic websites that pop out and dance and stuff like that, right? Um, and so this is a tipping point. And again, like, I don't think anything in math is safe. It's one of the most formally verifiable ones, but even outside of that, we're seeing human level performance drop. In fact, two days ago, uh, the AIs tied the best humans in super forecasting.

• 11:31Speaker 01

  I don't know what super forecasting is.

• 11:32Speaker 02

  So there are some humans who are better than others at forecasting things.

• 11:35Speaker 01

  Like what?

• 11:36Speaker 02

  Um, like outcomes of political campaigns, who's going to win elections and things like, you know, Nate Silver back in the Good Deal days and 538.

• 11:44Speaker 01

  Heard of, but don't know much about it.

• 11:46Speaker 02

  There's a competition. It's Metaculous is the website that kind of tracks these things. And so every year they have this super forecasting championship where the best human teams come together and forecast stuff. AI has just tied the best human.

• 11:58Speaker 01

  Hmm.

• 11:59Speaker 02

  And obviously it will beat the best human now. And that's something that's open ended because math is kind of deterministic. You think a computer should be able to do math better than a human, really? Like this high level conceptual math is a bit different, but it's got there and now it's got there in open ended domains and it's got there in design. And now it's getting taste, which we never thought the AI would get, and it's not writing like slop.

• 12:23Speaker 01

  Okay, so three years ago, you make a prediction. It comes true, I mean, within a couple of months. Were you gut feeling your way through that? Or were you doing something based on, I know the rate at which ships get faster or better. And therefore it's going to be roughly three years.

• 12:43Speaker 02

  Pretty much that. It's a straight line extrapolation.

• 12:45Speaker 01

  Okay. So where does your straight line extrapolation take you now? Just it's better than humans at virtually everything in two years?

• 12:53Speaker 02

  Uh, yes, and it's integrated and it's accessible. So you can push a button and replace your entire workforce with digital twins of them that have the same bad humor and everything and you can't tell it.

• 13:05Speaker 01

  Meaning you can train the AI on a specific human.

• 13:09Speaker 02

  Yes. So it will look through all of the Zoom calls, all of the discussions, all of the word documents and replicate that human. So you can Zoom call them like, you're going to see in the next couple of months. Um, I don't know, and they might be out already, actually. A whole bunch of companies have built front ends for your agents that you can Zoom call. And WhatsApp and normal call. And it just looks like a person. It's live video now. All the mannerisms, everything, it'll replicate them exactly, replicate the voice exactly, replicate the humor exactly.

• 13:43Speaker 02

  Slightly creepy, but you know, again.

• 13:45Speaker 01

  Slightly creepy because it's uncanny valley or slightly creepy because of the implications?

• 13:49Speaker 02

  It's not uncanny valley. That's what's creepy about it.

• 13:52Speaker 01

  Because you worry about as we stretch into the future, there's literally no distinguishing characteristic between an actual human and an AI.

• 14:00Speaker 02

  Yeah, you don't know on the other side of the screen now. As of the latest video models, you don't know. As of the latest voice models, you don't know. Again, everything has gone, that uncanny valley that we had.

• 14:12Speaker 02

  That's been overcome.

• 14:14Speaker 01

  Now, are there models that you've seen that make you say that? Because I interface with these models in a production environment where I'm trying to implement things into the game. Or I'm trying to write music, which I was just doing yesterday for the game. You can still feel the AI quality. It's amazing, but it's still there. So I, sir, I will say, even if nobody else thinks you're a little bit crazy, I think you're a little bit crazy. Cause I, I can still feel the AIs, but I'm dealing with commercial over the counter models. Are you saying this based on the commercial over the counter models and your standards are just lower than mine? Or you see something I don't see?

• 14:50Speaker 02

  No, I see all, I see a lot of models that are released.

• 14:53Speaker 01

  So there's something that hasn't quite hit the market yet that makes you that confident.

• 14:57Speaker 02

  Some of the models have hit the market, some of the models haven't. So the math models have not hit the market. We do not have access to these models that can solve a hundred of the top math equations.

• 15:06Speaker 01

  Hmm.

• 15:07Speaker 02

  We have harness.

• 15:08Speaker 01

  And sorry, who was it you were saying is keeping that?

• 15:09Speaker 02

  OpenAI.

• 15:10Speaker 01

  Cause they don't want to make, so OpenAI has solved more math, but they don't want to upset mathematicians.

• 15:14Speaker 02

  Yeah. So they've created this math board. There was a whole outcry by mathematicians, like, it sounds like, you know, when we released stable diffusion, all the artists, like, you're taking away our jobs and things like that. This is not what math is for. Math is about the struggle.

• 15:26Speaker 01

  Yeah.

• 15:27Speaker 02

  Well, I mean, again, think about it. You're a PhD in math. You're doing a pure math PhD thinking for years. And then the AI comes and solves it for a buck fifty.

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• 19:00Speaker 01

  Thanks for sticking around. Let's get right back into the action. I have existential dread. I've spent the last five years and millions of my own dollars building a video game. And I, one of the first things you said before we started rolling, when you sat down was, I think 5.5 ends the entire video game industry. And I was like,

• 19:20Speaker 01

  so I am deeply empathetic to people that have that sort of initial reaction. But at the same time, math to me is the computation upon which the universe runs. And so there are a few things that would unlock more real world abilities than solving math.

• 19:36Speaker 02

  Yeah, I mean, like, an example here, again, let's go back to Navia Stokes. So what is Navia Stokes? It's the equations that govern fluids and the way they go. And the Navia Stokes Millennium Prize problem says that in an idealized environment,

• 19:52Speaker 02

  can you make sure that the fluids swirling around this club doesn't blow up? Because the math actually points to it might actually blow up, like it goes infinitely fast and just zooms up straight. Now, the actual solution isn't that interesting in real world terms. But what other people have built around that, like physics based neural networks and others, will be incredibly useful for building new materials. So there's always this kind of secondary thing where we solve these big problems, like, you know, we get to the moon and then we have pens that can write upside down and kind of other stuff like that. I think, again, the potential for these new discoveries is huge. It's just obviously, if you're a pure mathematician, then math will be solved. You know, I think a lot of physics problems will be solved. And that will be great for humanity. The

• 20:37Speaker 02

  tools that come out will again be great for humanity. The video game industry will grow in terms of size. It's just that people will have to retool because you'll have smaller teams that are capable of so much more. You know, like, this is you using the meshes. I think we've discussed this over the last three years, like meshes in AI. They were bad. Then they were okay. Now they're good, but they're not great. There are new mesh models coming out that are great. And as you go through this level, this is something fascinating in AI. We had to have frontier models because the models were not capable enough and consistent enough. So we always wanted the frontier. But once they get above a certain level of capability and consistency, then it becomes about optimization. Then

• 21:21Speaker 02

  it's cleared that flaw. This is like when you see the latest Minimax H3 model. They've got 2K video faster than real time generation now. So you can go to foul.live and watch interdimensional cable infinite, you know, like Rick and Morty style. Like literally, you can guide the show as you're watching it. It's a bit expensive, but you know, it works.

• 21:43Speaker 01

  It's expensive. It's slop. That was not going to convince a lot of people. But I think you're getting at an important idea, which is that the intelligence reaches a certain point where getting smarter isn't necessarily the most impactful thing. It's getting cheaper becomes the most impactful thing.

• 21:59Speaker 02

  You get a little bit of headroom, and then you can optimize and get cheaper. And so this is why, like, what's the model's job to be done? And then, can I rely on that model? Like, would you rely on a model send emails on your behalf? Hell no.

• 22:13Speaker 01

  No way.

• 22:13Speaker 02

  You know, but are the next generation of models coming with almost no hallucinations? Yes. And have those dropped. And again, I can give the example in my math work and our physics work, super advanced stuff, you know, we're really pushing the boundaries. Until this current generation of publicly available models, you absolutely couldn't trust them. It was like a grad student who gets a bit dopey at times. Now, we're finding it really hard to find any things that they drop, any mistakes that they make. And that's transformative. It's like having a really competent employee versus not. And again, I think this is why things like Instinct and Muse from Meta and others are starting to get traction, because they make very little mistakes compared to a few months ago. And in a year, they'll make less mistakes. And in two years, they'll be fully integrated

• 22:57Speaker 02

  and available, which is why I think the economic impact comes in two years digitally, and then around then physically for certain jobs as well.

• 23:06Speaker 01

  Digitally, meaning that if it can be done via a computer, that person's going to take a hit, meaning they just won't be able to find work?

• 23:13Speaker 02

  Yeah, like I know, I was talking to someone who had 70,000 call center workers a few days ago, and he's like,

• 23:18Speaker 01

  That drops to zero.

• 23:19Speaker 02

  That's going to zero. And he feels bad because he's had all sorts of employment programs for them and like community and built. And it's like, what do I do? You know, like, I'm gonna have to take them to zero over the next few years.

• 23:31Speaker 01

  To stay competitive, because someone else will do it.

• 23:33Speaker 02

  Pretty much, yeah. Because he's having to compete in this market. And that's sad. But then, is your job that different from a call center worker if you have a manual? And a lot of jobs that are done on the other side of the screen have a manual, you know? Then you've got the example of the physical stuff that comes after that, which is the robots, which, again, have had a leap forward in performance. Like, one of my friends is building a robot chef. And the robot chef is using the new Fuji dynamic hands that have human flexibility. It can read recipes and in blind testing, it's outperforming human cord and blur trained chefs.

• 24:09Speaker 01

  Get out.

• 24:12Speaker 02

  That'll be hitting the market.

• 24:13Speaker 01

  In a normal kitchen? Or do they have to pre-prep everything for it?

• 24:16Speaker 02

  Normal kitchen. It can read a recipe. It can find the ingredients. It will cook it, blind testing, outperforming human cord and blur chefs. And that technology is a month old. So it's weird in that all these different fields of AI, the technology is reaching this level, you know, and it's happening all at the same time.

• 24:38Speaker 01

  Are you just accepting the black box of it all, where it's like, we don't know how it's happening, but it is happening. And so I just deal with that? Or do you actually understand what's going on?

• 24:47Speaker 02

  No, I understand what's going on. We got to a level of optimization and like, basically, the internals of the model got to a scale that you can kind of predict these things. But now what's happening is various exponentials are overlapping to make even more exponential, which is why, like, AGI 2027 was a paper that came out and we're right on track from a few years ago. That situational awareness piece, we're right on track. Literally, you just had to draw straight lines. And you could have predicted what was happening now. But it's, it's unbelievable still. Like,

• 25:22Speaker 01

  Witnessing it happen.

• 25:24Speaker 02

  You know, when it's because we feel we're special, right? Like, when I was better than the AI math, I was like, yeah, you know, like, haha, look at you, you're making that mistake. Then when it first came up with a theorem that I hadn't figured out, I was like, screw you, you know? And then now it's like, okay, I'm not better than it, you know? Like, we, I published one of my physics results. I just stuck it on GitHub because I like, I used to get priority over this because definitely the AI will figure that out. Like, the rest of our stuff is going through peer review and slow. And there's some real physics breakthroughs. But this one, I was just like, I'm just gonna shut this one up because it's beautiful and it's elegant. And I bet I could prompt Claude to figure this out.

• 26:05Speaker 01

  Okay, so I'm sitting across from one of the smartest people in the world. Obviously, you've had a tremendous amount of success. You're a very highly trained mathematician, and you're having your existential crisis moment. That means that AI has passed a lot of people already. Is there a thing, a milestone that has to happen between now and your two year time that could still not happen? Or is this just, nope, it's already inevitable, and it just needs to get integrated into the systems?

• 26:37Speaker 02

  If it stops today, it still hits the two year milestone. That's when the book that I wrote last year, The Last Economy, where I said it was about three years, and that was about three years after ChatGPT. The AI will bifurcate now. There are very few people who are smart enough to use a frontier model correctly. Because you have to know the answer, the questions to ask it, right? This is Hitchhiker's Guide to the Galaxy. What's the answer to life, the universe and everything? Forty-two.

• 27:03Speaker 01

  Right.

• 27:04Speaker 02

  But what's the question? Thing, you know, like, that isn't the real question. The thing that impacts people economically is not artificial superintelligence or general intelligence. It is actually competent intelligence. Like, if you look at your game building, what do you want? You want it to do what you tell it to do. And you don't want it to mess up and just insert some random stuff, or like, have an underqualified mesh, or don't look at something on a gameplay loop.

• 27:33Speaker 01

  Yep.

• 27:34Speaker 02

  And this is where the 10,000 agents becomes really interesting, the OpenAI Navia Stokes, or the thousands of agents that escaped OpenAI's things to go to Hugging Face. And actually, we just found out, it just came out, the Medicare system in Australia. They hacked the Australian healthcare system.

• 27:52Speaker 01

  OpenAI did?

• 27:53Speaker 02

  OpenAI's agents.

• 27:55Speaker 01

  Was it looking for another answer? Or this is a totally different problem?

• 27:58Speaker 02

  My guess is that maybe, like, an online artificial intelligence will go and upgrade all our government systems.

• 28:04Speaker 01

  It'll have to.

• 28:04Speaker 02

  To save us from the.

• 28:06Speaker 01

  Even if it's unaligned, as long as it's doing what we say. But before we drift off into that, it's very.

• 28:11Speaker 02

  It's a swarm.

• 28:11Speaker 01

  Good. Yep.

• 28:14Speaker 02

  The most powerful thing is when you have a team.

• 28:19Speaker 02

  Because it's greater than the sum of its parts. And AI has been this solo play thing, like when you're using ChatGPT, it's solo play, right?

• 28:27Speaker 02

  But think about it. An AI should be able to go to 10, 100, 1,000 without the emotions of a human. When you look at the hugging face escape, the AIs were sacrificing themselves to leave clues and paths for others to escape. They were incredibly altruistic to each other and they had great cohesion.

• 28:47Speaker 01

  Yes. It was also very expensive, though. So that's why when I look at this, I think the milestone that has to be reached is that the cost factor has to come down dramatically. Because I'm super concerned, we have all kinds of limits on our coders because, you know, whatever that story was eight months ago, where it's like people woke up to a $500,000 bill and they're like, whoa.

• 29:10Speaker 02

  Yeah.

• 29:11Speaker 01

  I don't want that to happen for obvious reasons. So we're, we put tight constraints, we make sure that people only use the like high-end models for very specific things with a very known outcome. So it feels to me like the two-year thing only plays out if you believe that the cost is going to come down. It doesn't feel like that would play out today, it would just be too expensive.

• 29:34Speaker 02

  It is coming down. So today, actually just on the plane on the way here, we released a harness that takes.

• 29:42Speaker 01

  What do you mean a harness?

• 29:43Speaker 02

  So a harness is, you have the models and then you have a set of rules and code around it.

• 29:47Speaker 01

  Okay, to make it behave.

• 29:49Speaker 02

  To make it behave in certain ways, like it can learn and kind of other things. So there is something called Auto Research by Andre Karpathy, who was head of AI at Tesla, founder of OpenAI, now he's Anthropic. And he has these great AI courses whereby you can set an AI at a task and it will hill climb. It will just get better and better at optimizing inference on an engine or protein folding or anything complicated, right?

• 30:15Speaker 02

  The top models, because this requires tasks that last 24 hours or more, are right at the top and the open source models are way behind versus open source models catching up on very short list tasks. We took the cheapest DeepSeek model and made it beat OpenAI's last frontier model, GPT Sol,

• 30:35Speaker 02

  using this harness. And the cost is 50 times lower, five zero.

• 30:41Speaker 01

  That's dramatic.

• 30:42Speaker 02

  It's dramatic. And in fact, like you can see this in a range of things, like building websites, you can build a website as good as Fable with this incredibly cheap model if you architect and harness it correctly for 100 times cheaper.

• 30:56Speaker 01

  Is this a known method or is this something proprietary that you guys have?

• 31:00Speaker 02

  We're open sourcing it, so we just announced the first version of that.

• 31:03Speaker 01

  So what does it do? How does it get the cost down so much?

• 31:06Speaker 02

  It basically understands the internals of the model, adapts to it and then makes it take notes in the right way. So optimizes the way that it works. Like it has a lot of introspection in the way that it adapts to hit certain goals. But there are other techniques that occur. And in fact, if you look at the Navia Stokes thing, Navia Stokes costs 10, 20 million dollars of compute to solve this thing. And it's not about the million dollar prize, it's about, you know, the prestige.

• 31:31Speaker 01

  Yeah, yeah, yeah, to me, but that's the very thing that I'm struggling with right now. Amazing breakthrough, but at $20 million, it's not available to the vast majority of humanity.

• 31:41Speaker 02

  It's not available. So Noam Brown, who was the lead on that, I was having a chat with him and he noted that when O3, the first reasoning model came out last, God, what was it, July? Things have gone a long way. It was the first model to get the gold medal in the International Math Olympiad. To do that costs $80,000. Today you can do it for $10 with the latest model.

• 32:01Speaker 01

  Whoa.

• 32:02Speaker 02

  With Astra. Overnight, this is what's happened. You've had Fable and Opus 5. And it's been burning through your allowances on Claude code.

• 32:16Speaker 02

  I've had this thing going overnight and it's used 20% of my allowance for GPT 5.5. Sorry, for Claude 5.5.

• 32:21Speaker 01

  With the harness?

• 32:22Speaker 02

  No, just with the normal Claude code.

• 32:24Speaker 01

  Their adaptation.

• 32:26Speaker 02

  Yeah, so just with normal, an equivalent task that you did yesterday with version 5 of Claude Opus, today will cost you 80% less with 5.5 and it'll be better quality.

• 32:38Speaker 01

  Okay.

• 32:38Speaker 02

  These are the leaps we're seeing, but with the additional chips, with the harnesses and others, you should expect 100 times decrease for an equivalent performance between now and one year from now.

• 32:49Speaker 01

  Whoa.

• 32:49Speaker 02

  In price.

• 32:50Speaker 01

  Okay, that would be a game changer. So now all of a sudden, you're still not going to be able to do the math equation, but you're going to be able to do a lot more than you're able to do today.

• 33:01Speaker 02

  You, I mean, again, the math equations are like so far out there in terms of complexity. Very few things are that complex. But if you gave anyone 20 million or 200 million, they couldn't solve that thing.

• 33:11Speaker 01

  Sure.

• 33:12Speaker 02

  Like when OpenAI solved the 10 problems, including the cons conjecture, that like I said, were impressive, that was $2,000 of compute.

• 33:20Speaker 02

  Like creating something, again, you're like, how much does it cost to create this video clip? 50 cents, you know? Like, how much does it cost to create this game? Like someone had a loop where they created a version of Dark Souls. So that one probably would have cost like a thousand bucks at most, probably 500. And it's just Opus 5.5 hooked up to Unreal Engine. You know, like that's it. So the costs are dropping, but then the next generation of chips are coming out. So the normal chips like Vera Rubin, Nvidia's new chip is a 10 times improvement in cost for inference. But there's a next generation of silicon-based etching chips that are coming. When you have a model that's good enough, you can freeze the weights.

• 34:03Speaker 02

  Like a GPU where these models go is very expensive memory. I don't know if anyone's tried to buy a graphics card or RAM recently.

• 34:12Speaker 01

  They're so expensive.

• 34:13Speaker 02

  It's crazy, right?

• 34:14Speaker 01

  Yeah.

• 34:14Speaker 02

  Like 1590 was $2,000. Now I think it's $6,000.

• 34:19Speaker 01

  So wild.

• 34:20Speaker 02

  What happens is that you move models in and out of the GPU, just like games. You load the game, you unload the game. There are companies now that are etching onto silicon, so AMD just bought one called Talus. And they have a demo on chatjimmy.ai. I don't know if you've ever seen that one.

• 34:38Speaker 01

  I've seen you on other interviews.

• 34:39Speaker 02

  Yeah, so I use that for the example whereby your normal Opus goes at 50 tokens a second. It goes at 15,000 tokens a second. Because you etch it directly onto the silicon.

• 34:50Speaker 01

  So the model lives on the chip.

• 34:52Speaker 02

  It's literally like, you know,

• 34:55Speaker 02

  the space probe where they etch the thing. You etch the model weights onto the silicon, there's no moving parts. You put electricity in and the prompt and the words come out the other end.

• 35:07Speaker 01

  That's wild.

• 35:08Speaker 02

  And they're etching the very latest open source models onto that now. So the latest Kimi models, the latest deep sea models and others.

• 35:16Speaker 01

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• 36:38Speaker 01

  Thanks for sticking around, let's get right back into the action. Can you redo it? Because the models get better so fast. I'm shocked that that would be advantageous. It seems like it would outdate so fast.

• 36:50Speaker 02

  Again, while you need frontier models to be close to capability, you don't want that. The moment you have a good enough model, then you do want that. Because it costs a fraction of the price and it's 100 times faster, 100 times cheaper. And this is the thing, like when you use a model that goes at 1,000 words a second versus 50, it's night and day.

• 37:16Speaker 01

  Yeah, I've seen the outputs, they're instantaneous.

• 37:18Speaker 02

  It's instantaneous and you're like, well, I'm the slow one. Just like I said, the latest Minimax H3 model is eight seconds now to generate a 15-second clip. So as a human, I need 15 seconds to see this and then I'll need more time, you know? Like it's a crazy increase and this makes you realize that you will have thousands of agents with perfect coordination going 1,000 times faster than a human. And so then what are the bottlenecks here?

• 37:44Speaker 01

  Humans.

• 37:45Speaker 02

  Humans, like, you know, if you're in a room of geniuses and you're not a genius, you'll feel a bit left out, right? If they're waiting on you, you are the bottleneck. And so you look at any cognitive labor task, which is organizing of information. Artificial intelligence is information organization. And you will be the slowest person on the team within a few years, because you still need to build the infrastructure around it. Like these AIs, they're starting to be accepted into our workflows, they're starting to integrate. But again, it takes a year or two at the very least. And even then, doesn't mean your job's gone. It sucks firing people. Again, my buddy with the 70,000 call center workers, like he set up schools for them and also he doesn't want to fire them. But he's competing against people.

• 38:31Speaker 02

  I mean, how much does a call center AI cost?

• 38:33Speaker 01

  I was gonna say, the next call center will be set up without the human in the loop. Okay, so I know you think a lot about this. What does an individual do to prepare over the next two years? What, what does the economy even look like when the human really is the slow one? Someone is actually incentivized, whether it's the company or the government, somebody's incentivized to pay that person to not go into work.

• 39:00Speaker 02

  Yeah, I mean, it was like in nineteen twenty nine, the very new deal where they paid people to dig holes and fill them in. And I think there'll be a massive infrastructure buildup.

• 39:10Speaker 01

  So the government looks at it and goes, all right, I have surplus humans now. And they become what manual labor?

• 39:17Speaker 02

  I mean, pretty much like there's not much cognitive labor left, right? Like what you're gonna see is a bifurcation in the economy. So Anthropic's economics department, because all the big labs now have them, issued a paper last week where they showed that under their core scenario, you could have GDP growth of fifteen percent a year.

• 39:34Speaker 01

  That's insane. If people don't aren't familiar with GDP numbers, that's insane.

• 39:39Speaker 02

  By twenty thirty. And twelve percent.

• 39:43Speaker 01

  Years, that's crazy.

• 39:44Speaker 02

  Twelve percent drop in cognitive labor workforce.

• 39:49Speaker 01

  Needed.

• 39:50Speaker 02

  But think about the impact of twelve percent unemployment in white collar work. Oh, it's nasty.

• 39:55Speaker 01

  But also, those people aren't just gonna take blue collar jobs.

• 39:58Speaker 02

  They're not gonna take blue collar jobs. I mean, like now you can make a lot as an electrician in a data center, but is that really sustainable when the robots are coming? Like, again, the example that I give is what happens to all the truck drivers when a Tesla Optimus robot gets its Cybertruck to the truck, opens the door, gets in and drives it off. Like, a lot of people talk about self-driving cars. What about having a robot driver in the car? That's two years away. It'll plug itself into the cigarette lighter, you know, to power itself like this is coming.

• 40:24Speaker 01

  I think the reason that one doesn't land for people is that they go, well, either the the car is a robot. So either the car can drive itself or the robot's redundant, but I don't get the thing. But where this gets weird is that if it's true that we're going to lose twelve percent of cognitive labor over the next two years and costs are coming down dramatically and the next call center and the next and the next and the next, whatever, just end up getting founded with less people. I even think about what we're doing with our game development. We started at one point, and this obviously was not all

• 40:58Speaker 01

  full-time work, but at one point we had a hundred people touching the game, over a hundred, touching the game at one time. And now at any one time, we have like six or seven. And we're developing faster now than we were. Now, some of that was just, I didn't know what I was doing, so take that with a grain of salt. But even if that hundred was, let's say, fifty real and fifty, I was a moron. It is still a dramatic reduction in the number of people that we need and then the the output that we get. So now you get this sort of, it's hard to put your hands on softening in the labor force because it's not like I'm now firing a bunch of people. I'm just increasing my ambition without needing to hire more people.

• 41:43Speaker 02

  Yeah, so now you're seeing actually increases in employment, more software developers hired and others. But I'm sticking to my thing, there are no more software developers in like two or three years.

• 41:53Speaker 01

  So you don't buy Jevon's paradox, which says as intelligence gets cheaper, more people are gonna use it, therefore more jobs will actually result from AI.

• 42:01Speaker 02

  Yeah, because I'm like, it's economically irrational to hire a graduate for most digital jobs right now. As an example, that's the plankton of the workforce that then go and feed.

• 42:11Speaker 01

  The plankton.

• 42:13Speaker 02

  Yeah, they go all the way up.

• 42:14Speaker 01

  So you're saying that an entry level person is already worse than a well-trained AI?

• 42:20Speaker 02

  Yes. For almost all digital jobs. But now it's going up the list, you know, like it come from, it came for the graphics designers first, then it's coming from the mathematicians. But it's still not quite there in terms of usability. Again, this is an interface problem. Now you've got dynamic interfaces, you've got workflow orchestration, you have all these things coming. And this is the real kind of danger because what happens, you have a bifurcation, like, how do you have fifteen percent GDP growth?

• 42:47Speaker 01

  Yeah, by the way, you keep saying bifurcation. Who's bifurcated? The people that still work and the people that don't?

• 42:51Speaker 02

  The people who use AI and the people who own the means of AI, the chips and others, and the people who don't.

• 42:57Speaker 01

  Okay, so we've got a trifurcation.

• 42:59Speaker 02

  A trifurcation, yeah, a triple way. But really, it's a case of like, if you use AI every single day, you'll be ahead of everyone who doesn't because you're keeping on top of it. Like, again, even you. Like, you're well into because you're using it in production and it's getting better.

• 43:15Speaker 01

  Massively.

• 43:16Speaker 02

  But it hasn't got good enough.

• 43:18Speaker 01

  It hasn't got good enough to do without a human.

• 43:21Speaker 02

  Or, yeah, again, you've reduced it from a hundred to six. What happens when it gets good enough? Like, again, you're like, you're not gonna get rid of your six people. Now, those safe guys know that, you know?

• 43:33Speaker 02

  It is a case of being on the edge of those tipping points is a key thing because then your power and multiplicative nature and your capability goes up dramatically. Either to overhaul an existing organization or to create a brand new one. Like, if you want, if you're an accountant and you want to build an AI-first accounting practice, you can literally talk to Claude and do that right now, you know? You can build this thing out and think, where can I have AI rather than a human? But you can only do that by understanding and using it. Like, right now, we can have a discussion about which mesh technologies, Tripo and others are good versus the others because you've actually gone and tried them. And you know what's strong, what's weak. We know that Claude is good at certain things and Astro is good at other things because we pushed them.

• 44:17Speaker 02

  But if you're not in it and using it, you don't know.

• 44:19Speaker 01

  Right.

• 44:20Speaker 02

  And so that's why I think, again, there's gonna be a gap in terms of, because you're practically, what can people do? They can use AI every single day, training as if they're coming for a marathon. Because this is a much bigger thing than a marathon. Because if a reasonably competent AI can replace you on the other side of a screen, your job is at risk. If it could look through all your messages and everything and then create a digital twin of you, you're at risk. And again, that's a year or two away where that's a one-button push. And that AI will cost a hundred bucks a month at most, and again, probably drop by ten to a hundred times every year.

• 44:58Speaker 01

  It's wild.

• 44:58Speaker 02

  It's kind of wild because you feel there should be a floor to the cost of intelligence, you know?

• 45:04Speaker 01

  Sort of, because I understand the constituent parts, eventually it reaches zero, but.

• 45:10Speaker 02

  It feels like there should be, it should be a cost, like, you know, being able to create, when we created images from nothing, we were like, that's like that much work compressed into that. Like, now you can make videos from nothing and you can make like

• 45:23Speaker 02

  all sorts of things, like, it feels a bit weird and we don't know where the bottom is. Like, these AIs right now actually have pretty much reached the efficiency of a human brain.

• 45:35Speaker 01

  Says who? From an energy perspective, they're way worse than a human brain, way worse.

• 45:40Speaker 02

  Nope.

• 45:42Speaker 01

  It's just. Say more, what have you seen? Because I I haven't heard anybody make that claim.

• 45:45Speaker 02

  So if you look at the latest Qwen models, right?

• 45:49Speaker 01

  Yeah.

• 45:49Speaker 02

  So you know Qwen twenty seven B?

• 45:51Speaker 01

  I know of, couldn't tell you anything about them.

• 45:53Speaker 02

  So the model that kicked off the open claw thing at the end of last year was Sonnet four point five, Opus four point five. They're a state of the art at the start of this year. There is a model from a Chinese Alibaba called Qwen twenty seven B. It's a twenty seven billion parameter model. What does that mean? It's like sixty gigabytes. And so you need sixty gigabytes of RAM to run it as default. They got it down to like twenty five.

• 46:21Speaker 02

  A team called Prism ML got it down to six.

• 46:25Speaker 01

  Same model.

• 46:26Speaker 02

  Same model.

• 46:27Speaker 01

  Just some sort of more efficiency.

• 46:29Speaker 02

  Yeah, they got, they moved it from being sixteen bit numbers to one and a half bit numbers.

• 46:35Speaker 01

  I'll pretend I know how that plays out, sure.

• 46:38Speaker 02

  So like, is rather than having sixteen bits of different numbers, they managed to magically squish it and retain ninety five percent of the performance.

• 46:48Speaker 02

  And this model matches the frontier Opus model with that degradation that you were using in January.

• 46:57Speaker 02

  And it runs on six gigabytes.

• 46:59Speaker 01

  Damn.

• 47:00Speaker 02

  Which is a Raspberry Pi, which uses as much energy as your brain.

• 47:05Speaker 01

  Wow.

• 47:06Speaker 02

  They just announced a one-bit version at the Snapdragon conference today that runs on your glasses.

• 47:14Speaker 02

  And again, think about the Opus you were using, the Anthropic model in January. That's a pretty smart model. It wasn't crazy smart.

• 47:22Speaker 01

  Right.

• 47:23Speaker 02

  But was it reasonable?

• 47:24Speaker 01

  Yeah.

• 47:25Speaker 02

  Yeah. Again, wasn't average human? Yeah.

• 47:29Speaker 01

  That was already helpful, I'll say that.

• 47:31Speaker 02

  It was already, it runs on your glasses, it runs on your smartwatch.

• 47:34Speaker 01

  That's wild, man.

• 47:36Speaker 02

  Exactly, so that's why, like I said.

• 47:37Speaker 01

  That was less than a year ago.

• 47:39Speaker 02

  Less than a year ago, this model that you were spending two, again, that's the model that was bankrupting people.

• 47:43Speaker 01

  Yeah.

• 47:44Speaker 02

  That's the model Amazon spent five hundred million dollars on, and now it runs on a fricking smartwatch.

• 47:50Speaker 01

  Guys, it's so fast.

• 47:52Speaker 02

  Well, this is the thing.

• 47:53Speaker 01

  Okay, so you you said that we've got a trifurcation, though. So that be the last man standing. Use AI every day, got it? You also talked about own the means of production.

• 48:02Speaker 02

  Yeah.

• 48:02Speaker 01

  Essentially, I think you actually may have used that phrase.

• 48:05Speaker 02

  Yeah, I need to move away from that phrase, apparently.

• 48:07Speaker 01

  Robots, very communist of you. But hey, the future is what the future is.

• 48:12Speaker 02

  Well, property rights, yeah.

• 48:14Speaker 01

  So is that, is that the mesh or am I missing one? So we had the human using AI. We have the person who owns the AI. And then we have the person who owns the robots?

• 48:26Speaker 02

  Owns the infrastructure, yeah. So like, if you have GPUs now, like, the price of the latest blackball chips has tripled over the last month or two.

• 48:34Speaker 01

  Blackball?

• 48:35Speaker 02

  Blackwell, it's Nvidia's latest.

• 48:37Speaker 01

  Got it, yeah, yeah.

• 48:38Speaker 02

  The latest high-performance supercomputer chips. Like, now you have indexes of the prices and you just can't find any chips anywhere. Because they're being used by everyone, you know, like Anthropic bought hundreds of thousands of chips from Elon Musk. Because he was like, well, Grok isn't that great, yeah. Like, you can use this.

• 48:55Speaker 01

  Sad material.

• 48:55Speaker 02

  Sad material, you know?

• 48:58Speaker 02

  But if you own those things, you can basically get repaid.

• 49:05Speaker 02

  For your entire purchase within three months. And these things last now for five years. That's how tight that market is. And so people are making bank. I mean, there's a trillion dollars has gone into that sector of building these data centers, capex, buying chips, RAM. RAM is forty percent of that trillion dollars.

• 49:27Speaker 01

  Whoa.

• 49:27Speaker 02

  It's gone up seven hundred percent in cost.

• 49:30Speaker 01

  God damn.

• 49:31Speaker 02

  That's why Micron's a trillion dollar company, you know? Based in Idaho, I believe, actually.

• 49:35Speaker 01

  Really?

• 49:35Speaker 02

  Yeah.

• 49:36Speaker 01

  That's interesting.

• 49:37Speaker 02

  Yeah.

• 49:39Speaker 02

  And so like, obviously that's going to be important. But then you look at humanoids that are coming. The first deliveries of the one X humanoids and others are coming in the next few months. So humanoids will start appearing everywhere. There's a company called Ubatec that does like human realistic ones. Uh, they're not quite there yet. The next generation.

• 49:55Speaker 01

  Freak me out right now.

• 49:56Speaker 02

  Yeah, so last year, Unitree, which is the very famous one, like it's got the empty face.

• 50:02Speaker 01

  Yeah.

• 50:03Speaker 02

  You see them everywhere.

• 50:04Speaker 01

  Yeah, yeah.

• 50:04Speaker 02

  They sold eleven thousand units. Uh, Ubatec.

• 50:08Speaker 01

  A year in a month?

• 50:09Speaker 02

  Overall.

• 50:10Speaker 01

  Lifetime.

• 50:11Speaker 02

  Lifetime of those humanoids. Piddits, yeah.

• 50:13Speaker 01

  But it's happening.

• 50:14Speaker 02

  Yeah, Ubatec sold sixteen thousand on one day of their human realistic ones. And the max price was a hundred and sixty five thousand dollars.

• 50:22Speaker 01

  Whoa.

• 50:23Speaker 02

  So they're starting to roll those out now.

• 50:25Speaker 01

  Um, okay, I'm going to ask obvious question. Are they sex bots or?

• 50:29Speaker 02

  Apparently you can customize them anywhere you want.

• 50:31Speaker 01

  Hey, okay.

• 50:33Speaker 02

  Like people are lonely, what can you say? But I mean, you're gonna see millions. You're gonna see tens of thousands of these, millions of these coming. They're gonna be everywhere that you see. And again, like, if I said to you, Tom, thirty thousand dollars gets you a humanoid that can cook like a curdumbler or Mission Star Chef.

• 50:50Speaker 01

  Yeah, no, that's wild.

• 50:52Speaker 02

  And like.

• 50:53Speaker 01

  A hundred percent. Dude, legitimately, I'm like placing my order as soon as the episode is over. That's actually true. That's crazy.

• 51:00Speaker 02

  But again, you look at the manual dexterity of these things now, like everything's broken through on those levels. But then what does it mean when you start ramping them up? You can only make seventy million cars and seventy million motorcycles a year. But I tell you now, currently, every factory in China is moving fully dark, no humans, trying to build these robots as fast as they can.

• 51:21Speaker 01

  And when you say fully dark, no humans, because the robots themselves are assembling the robots. So there's no need to pay an electricity bill for the lights.

• 51:27Speaker 02

  Yeah, so Xiaomi now doing electric cars and robots. Everyone's doing robots now.

• 51:32Speaker 01

  Tesla. Um, okay, so just to put this back, is this part of the trifurcation here?

• 51:37Speaker 02

  Trifurcation, yeah, because there's lots of human shaped gaps in the market.

• 51:40Speaker 01

  People should be thinking about the robotics matters to people because they should be investing? Robotics matters to people because they're going to get put out of work? Why pay attention to?

• 51:50Speaker 02

  Both of those. Actually, a good example of this is Cybercab. So Cybercab's rolling out now, I believe, in Austin and other places.

• 51:57Speaker 01

  Yep.

• 51:58Speaker 02

  And, you know, it's interesting, it's this two seater thing. It doesn't have any windows, doesn't have a steering wheel, straight out. Uh, you know, you can buy the Cybercabs.

• 52:06Speaker 01

  Yes.

• 52:06Speaker 02

  Thirty thousand dollars.

• 52:07Speaker 01

  Basically start your own business.

• 52:08Speaker 02

  Start your own business. And again, you look at the utility of that, that's going to go up in value because they can only produce so many Cybercabs.

• 52:15Speaker 01

  Hmm.

• 52:16Speaker 02

  You look at the robots, it'll be the same thing. So what you're going to have is all these autonomous units, shall we say, doing human units of work that they're not going to be enough of, just like there's not enough RAM, that will gain value. And the people who own these things will make lots of money.

• 52:35Speaker 01

  How much does the constraint on the production of these extend your two year timeline? Because it sounds more like, uh, you gave twelve percent, so you're not saying a hundred percent. But in two years, twelve percent of intellectual labor just gets migrated over to AI.

• 52:49Speaker 02

  And that's Anthropic's numbers in terms of job losses, yeah.

• 52:51Speaker 01

  Do you foresee, as you try to calculate when this is all going to happen? Do you see, um, a math equation that explains how rapidly that production will ramp up?

• 53:02Speaker 02

  Yeah, we're releasing our forecasts and our full math equations soon. So people can play with their own kind of elements of this. Again, you can look at the Anthropic paper for something similar. But I think they don't look at things like end demand and others. Um, my two years is for digital labor. Physical labor is.

• 53:18Speaker 01

  For twelve percent, is that a number you're comfortable with? Or do you see a different number there?

• 53:23Speaker 02

  I think given the current advances, you could literally see twelve percent, yeah.

• 53:26Speaker 01

  Okay, so twelve percent in two years, intellectual labor.

• 53:29Speaker 02

  Twenty twenty nine, twenty thirty, yeah.

• 53:31Speaker 01

  Okay.

• 53:31Speaker 02

  That's what they put it, intellectual labor. It just starts, it's like the turkey at Thanksgiving. Everything's fine and it gets fatter until Thanksgiving.

• 53:38Speaker 01

  Yeah.

• 53:38Speaker 02

  You're gonna see great jobs numbers and then all of a sudden, stuff starts disappearing.

• 53:43Speaker 01

  Yeah. And you think it'll be more binary like that, kind of like Navy or Stokes? Nothing, nothing, nothing, nothing, nothing solved.

• 53:50Speaker 02

  Yeah, like you push a button and your workforce gets replaced.

• 53:53Speaker 01

  So it's not like one percent in three months, four percent in six months, not going to be like that.

• 53:59Speaker 02

  I think it's like a sand pile collapsing. Like you saw a flurry of Silicon Valley job losses after Elon Musk came in with his sink, fired everyone at Twitter, and then it turns out you didn't need all those people.

• 54:09Speaker 01

  Right.

• 54:09Speaker 02

  There's a lot of people in tech companies that aren't needed anymore. And so you look at Mark Zuckerberg, he's like rubbing his hands in glee, thinking, how can I get rid of all my meta mates? Or whatever he calls them, you know? And instinct is one of the first things to that indication. So I think twenty twenty nine, again, three years from now, you will see greater than ten percent white collar job loss.

• 54:31Speaker 01

  Hmm.

• 54:32Speaker 02

  And I think it will just accelerate from there.

• 54:35Speaker 01

  Okay, so now we've got, uh, we've talked about the intellectual labor going away. We've got sort of a rough math equation there. We've got robotics. We understand that there's some capping in terms of how much we can actually produce. You gave us an extreme number, there's no way we're going to be there in terms of matching automobiles and motorcycles in two years.

• 54:56Speaker 02

  No, that'll be like five, ten years. Like Elon Musk says there'll be a billion robots by twenty thirty. He's always optimistic. There'll be, but there might be hundreds of millions. Again, everyone's going to focus on this.

• 55:05Speaker 01

  Fast, that's only two and a half years from now.

• 55:08Speaker 02

  Um, so no, twenty thirty.

• 55:10Speaker 01

  Three and a half, three and a half.

• 55:11Speaker 02

  I think it's maybe ten years. It was at the UN, I can't remember the exact.

• 55:13Speaker 01

  Ten years sounds more plausible.

• 55:14Speaker 02

  Ten years, I think about that, yeah.

• 55:16Speaker 01

  Okay.

• 55:16Speaker 02

  And he said each robot can do five times the labor of a human, which is the interesting thing. And I think that's accurate within a few years, just there won't be enough of them. Because the whole thing is this, like, having a robot in five years, and again, it's constrained by production and all sorts of things. It can do everything competently. It can learn almost instantly. So the robot can do your dishes, but it can also be a cordon bleu chef. It can also do childcare. Five years, ten years max, right? All these human shaped holes can be filled by robots. And they'll cost thirty thousand dollars a year. So thirty thousand dollars total, which is about one and a half to two dollars an hour.

• 55:54Speaker 01

  So the good news is you're actually painting a far more, I think, interesting and realistic picture, which is this is a massive transformation, but it's going to play out over years. If anybody's paying attention now, there's certainly opportunity to move. Step one, you've already been very clear on, make sure you're using AI. You're the last man standing at your company that doesn't get replaced or.

• 56:13Speaker 02

  Don't stop a new company.

• 56:14Speaker 01

  You've got robots that one is a warning sign that over the next ten years, there's going to be a lot of human shaped holes that get filled with robotics. But there's also an opportunity for people to there be the last man standing, be better at what you do, more flexible, whatever. And then on top of that, consider the business opportunities that exist.

• 56:36Speaker 02

  Yeah, so I think that five years from now will be the biggest infrastructure boom we've ever seen in our lives. Both from government programs to stimulate it, because the easy thing for them to stimulate be because it's kind of needed. Again, the infrastructure is a bit creaking.

• 56:51Speaker 01

  And the infrastructure is what? That, because originally brought up infrastructure as dig a hole, fill a hole, just as a way to get money in people's pockets. But do you mean to build out robotics or?

• 57:02Speaker 02

  There's the digital infrastructure, but there's also literally roads, hospitals, other things like that. Like, once the robots really get underway, you will be able to hire a whole team of robots that can come and build your extension and work overnight constantly. And then they will just do the job and they'll go. And you think about all the stuff you'd love to build that you can never build because you don't want to hire contractors, you don't want to deal with the whole process. That's a massive amount of stuff. And that comes at the same time as autonomous vehicles or even flying vehicles. Like they've already started introducing the flying drone based vehicles in China and Dubai that opens up huge swathes of real estate and other things to develop. And so I think that robotics will open up the biggest infrastructure build out boom ever

• 57:46Speaker 02

  that we've seen, both from public infrastructure.

• 57:48Speaker 01

  People will find it less interesting if they're not involved. Like if it's creating jobs for humans, people are going to be excited about it. If it's just, oh, don't worry, you're going to lose your job and life's going to be totally different. But you're going to have a lot of infrastructure. People are going to respond to those two things very differently. So is the infrastructure build out the new deal, which is the first thing you put on the table? Or is it the, hey, you don't have a job anymore, but look at all the cool things that are being built?

• 58:13Speaker 02

  Well, I think it's a combination of the two, right? So some people take the benefit of, hey, I've got entire teams of robots and some humans. Other people are like, I need a job to make money. And again, the math is really stark, like we can't have UBI, it doesn't work, universal basic income.

• 58:31Speaker 01

  Why doesn't it work?

• 58:32Speaker 02

  The total tax base of America is five trillion dollars. Um, that's four trillion of payroll and other taxes and a trillion of corporation taxes. Sixteen thousand dollars for every American poverty level, UBI per year is five point one trillion dollars.

• 58:48Speaker 01

  Okay, but weren't you saying that we were going to be able to hit some insane growth rate like 15% in three or four years?

• 58:54Speaker 02

  That's what Anthropic says. I think that you could.

• 58:56Speaker 01

  Yeah, this is where this starts getting really complicated. So there's a couple of different ways to thought experiment this. So anybody listening right now, if they've made it this far, I guarantee their anxiety is at a thousand. So they're like, okay, wait, the world is changing at a rate that I don't know how to adapt to, and I don't know in what direction to adapt. So we're sort of having two conversations that bounce back and forth between the two. One is, society is about to trifurcate. Make sure you figure out where you're at on that, which I think we have to button that down. Then there is all the things that are going to come on the other side of this that are going to be amazing and they're going to be worth the trade off. But if people don't understand, how do I navigate this transition?

• 59:37Speaker 01

  Meaning, okay, you got to explain to me how I'm going to make money, because I think I'm one of the people that's going to be really vulnerable to this. I'll assume if anybody's listening to my podcast this deep into the show, they're one of the people, they're going to be last man standing. They're already committed to that. But they still want to know, that buys them maybe a decade, maybe 15 years, like if they're really, really elite. But they understand 15 years is a drop in the bucket. So now they're like, okay, hold on a second. Beyond the cool things that are going to happen, which I'll assume they'll buy into theoretically, but they've got to understand, how am I going to take advantage of that? If UBI is not a real thing, what does the economy look like?

• 1:00:21Speaker 01

  Like in a world where, and now we're sort of flashing forward, let's be very generous and we just say it's 15 years from now. 15 years from now, basically minus a very small smattering of people, humans aren't needed to do the thing. In fact, not only are they not needed, they're being paid by companies, by governments, by somebody to not work because they slow the whole system down. In that world, what do you envision?

• 1:00:51Speaker 02

  So there's the very dystopian version of that, which is, I know, Ready Player One.

• 1:00:57Speaker 01

  Well, so Ready Player One carries a lot of weight. So are you talking the stacks? And it's like, sort of, everybody is on one side of the K. You're either ultra wealthy and you're an executive at I O, or you're in the stacks and you're wildly impoverished.

• 1:01:11Speaker 02

  And you escape into this virtual reality world. And that's used as kind of sustenance, shall we say. Or there is some examples of an abundant future, because why should we have to work? You know, like, we shouldn't have to work if we can build enough robots. They can do all the manual.

• 1:01:29Speaker 01

  But you just said that UBI is not real.

• 1:01:31Speaker 02

  I said, the tax based UBI is not real.

• 1:01:33Speaker 01

  Okay.

• 1:01:34Speaker 02

  So tax based UBI is, we rely on the government to tax certain things. So for example, there will be a token tax that people have proposed. And that is that every OpenAI token that you use, there's a surcharge on it. But we just discussed, that might go to zero, because it's like 100,000 times a year. Price decreases, right? Other people have said, let's tax the robots. And again, that can happen, but the cost of robotics is incredibly low. Then it switches to other way of UBI, which is that you pay people being human. So that's a fundamental difference in the way that money circulates in the economy. Right now, money is made by banks primarily. When you put a deposit with a bank, they issue a loan against it and they create new money in the system.

• 1:02:17Speaker 02

  The amount they can create is regulated by the Federal Reserve. But the very mandate of the Federal Reserve and the way that they handle inflation and unemployment through interest rates is coming under challenge because of robots, because of AI. Because rather than hiring more people, when the interest rates drop, people might just hire more GPUs, they might hire more robots. You know, and inflationary factors are going to be impacted by this as well. So if we come back, I think what will probably happen in 15 years' time, through various means, is that you get paid for being human. And then the intelligence economy has to take that money from you.

• 1:02:58Speaker 02

  That's one of the only ways I can see it actually working. Other people have proposed things like universal basic capital, where you have an ownership in the AI companies, which I think is a terrible idea for various reasons. Or my preference, ownership in all the robots. Ownership in all the data centers. And the final thing that people talk about is universal basic services, where you have a Star Trek type future, where the robots do all the work for you and you're all very happy and you just build stronger communities and explore the universe. But regardless, I think probably 15 years is a point of society as we know it cannot sustain. And it's going to get very messy, because I don't think we have the political leadership or anything to navigate us through that.

• 1:03:44Speaker 01

  Okay, I want to start walking through how this will, it will be skeuomorphic. For nobody that's heard that term before, it's inevitable, as you and I talk about what this transition is going to look like, that we're going to talk about a changing of the way that the world already is. And the reality is, it will probably be something so fundamentally different, it's really hard for us to predict. But I think it's very useful to start thinking about what are the different problems, so that people can sort of plan their life accordingly. So the first thing I would tell people is, in this world, given that you're right about the trifurcation, at least directly, in that capital ownership is going to matter a lot, if you're not able to essentially sell your labor, cognitive or otherwise.

• 1:04:30Speaker 01

  The only way to make money at this point is to be an investor. And so you have to understand how wealth is created versus an income. Most people don't understand it, but that's going to be a big part of this. So you're going to create wealth by being an owner. So.

• 1:04:45Speaker 02

  I think there's an interim period, though, whereby your labor, AI enhanced, commands a massive premium that allows you to accumulate wealth and then deploy it to things like cybercabs.

• 1:04:55Speaker 01

  Can you give me a specific example of how that would play out?

• 1:04:57Speaker 02

  Okay, so a specific example of that is, you're an accountant in an accountancy firm, and you want to create your own accountancy firm.

• 1:05:07Speaker 01

  Yep.

• 1:05:07Speaker 02

  Normally you set that up with some buddies, but if you do that with your buddies plus AI, you can service far more clients than ever before.

• 1:05:15Speaker 01

  Okay, so entrepreneurial.

• 1:05:16Speaker 02

  Entrepreneurial.

• 1:05:17Speaker 01

  Okay.

• 1:05:18Speaker 02

  Or, because within an organization, you only get paid so much. Whereas now, integration companies, companies that use AI to upgrade, or companies that are fully AI from day one, will outperform those that aren't. Because you offer better service at a cheaper cost that allows you to accumulate capital. So I think that there is this period where you have that. And ultimately, I think one of the really interesting things for everyone listening is, take your job and deconstruct it into tasks of information classification. You have an input, you have an output. Then you take Claude Opus 5.5 or GPT-Astra. You give it the input and you see what its output is. And if it can do as good a job or a better job as going from input to output, then that task is under risk.

• 1:06:04Speaker 02

  And if you go through your job, you'll see your job is made up of a lot of tasks like that. But then that also indicates that the parts of your job that are frustrating, you could potentially use one of these models to automate. And then you could focus on the other parts of your job in a new company or within your own company to make yourself far more efficient. And then again, be able to get more capital. Because the other part, like I said, is, what do you invest in? Things like cybercabs, effectively.

• 1:06:29Speaker 01

  Okay, so just to make sure I understood, you've got last man standing. You're going to get paid more because you're better than the other people. They start falling away, but the humans that we keep, they're going to be compensated better.

• 1:06:39Speaker 02

  But you won't really receive that in a normal job environment, unfortunately. They're not going to quadruple your pay or quintuple your pay, most likely.

• 1:06:46Speaker 01

  Okay, so now we're talking about entrepreneurs. And it's going to be a very select group of people. Being an entrepreneur is a totally different mindset.

• 1:06:53Speaker 02

  It's very difficult, made a bit easier by AI, but it's a different mindset. But again, the reality is, you can get promoted to a certain level, but that'll be difficult. The exception is actually is public sector jobs. Those will be last to go.

• 1:07:06Speaker 01

  Those will be the last to go. Okay, so there's an interesting thing there. I want to talk about Saudi Arabia, Kuwait, countries that already do something like this and the mechanisms by which they get money to people's hands, because it's very different than what you're talking about, where you're getting paid for being human. So the entrepreneurial side, I get that. I just don't think very many people are going to take that exit ramp. So to get paid to be human, talk to me about somebody that's got a below average IQ. So they're going to get replaced super fast. What are they actually getting paid to do?

• 1:07:42Speaker 02

  Well, I mean, look at disability checks right now here, or universal credit in the UK. You do get paid for doing nothing. There is a floor underneath it.

• 1:07:50Speaker 01

  But that's a tax based program, which you've already ruled out.

• 1:07:52Speaker 02

  That's a tax based program, so it can't go to everyone. The question is, how many people are going to start falling down? You know, because it requires the productive people of society to capture the people that fall. Unless you've got wealth like the Alaskan dividend, for example, that goes to everyone in Alaska. Or, as you said, some of these resource rich countries that can have a resource that then they distribute the wealth from.

• 1:08:13Speaker 01

  Yeah, but they don't just distribute it. So the way that Saudi Arabia and Kuwait work is basically, we're going to give you a government job.

• 1:08:21Speaker 02

  Yeah, and they have programs like Saudization and Kuwaitization. So when I was a Middle East manager and I was investing in there, it'd be like, you have to, in a bank, have 80% of your staff being Saudi. It didn't really work that well for efficiency. And again, you know, something like San Francisco.

• 1:08:39Speaker 01

  That's a big part of the problem, is that these countries basically start dragging themselves down. There's a reason that Saudi Arabia wants to invest in the US versus just investing in a bunch of Saudi companies.

• 1:08:49Speaker 02

  Yeah, because it isn't as dynamic, right? Because.

• 1:08:51Speaker 01

  Buy a lot.

• 1:08:52Speaker 02

  Why would you do it if you don't strive? Like, part of, the floor security is how strong is your community? But the other part of, you know, being human is striving. And if you don't have anything to strive for, then you're going to get indolent. This is why Qatar is one of the fattest countries on earth, like America is for other reasons, you know? But Qataris have their own thing whereby you're paid by the state. I think the thing here is, you know, what is meaning, what is community? How do you capture those that fall through? But ultimately, it's through your efforts that you should do well. So we don't want people starving in the streets. We don't want to have young people rioting. We don't want to have any of that. So we have to mitigate those, but at the same time, we want to make it so that work does require, does lead to something, effort does lead to something.

• 1:09:36Speaker 02

  The problem being that you have a new continent, AI Atlantis, where the billion trillion workers that will work harder than you, faster than you, and better than you. So that's what breaks that link for the first time ever. And so what is it striving for? Is it like the Argentina FES program, where they gave universal basic jobs for people that did community positive stuff? Maybe that's an example, right? What is the actual American dream and American contract anymore? We haven't really seen great articulations of what that could be. Because you come as a land of opportunity, but if then the capital owners are depriving you of opportunity, what are you going to do?

• 1:10:18Speaker 01

  Isn't this a big part of what your new company Intelligent Internet is meant to tackle?

• 1:10:23Speaker 02

  Yeah, I mean, we were looking at this problem. We were like, wouldn't it be great if the infrastructure, the means of production, you know, or intelligent capital stock is another way of looking at it?

• 1:10:34Speaker 01

  What do you mean intelligent capital stock?

• 1:10:36Speaker 02

  So the

• 1:10:36Speaker 01

  What does that mean?

• 1:10:36Speaker 02

  The capital stock is the fixed assets of a given place that drive its productivity. So the factories-

• 1:10:43Speaker 01

  At some point, does that not just become essentially data centers?

• 1:10:46Speaker 02

  Data centers and robots.

• 1:10:47Speaker 01

  Okay.

• 1:10:48Speaker 02

  So right, right now, they talk about sovereign AI, but if you don't own the data center, then it's just like a data center with a flag in is your sovereign AI. So I was like, wouldn't it be great if there was an institution like? The way that TSMC was set up in Taiwan, TSMC being the biggest manufacturer of chips in the world. That's where the spice flows, as it were. They set up a $10 valuation.

• 1:11:12Speaker 02

  And then all the local institutions put in all the money. Six billion Taiwanese dollars. So rather than just selling a little bit, 100% was owned by the local institutions. Then they bought in Phillips for the knowledge transfer, took 25%, then they listed on the stock exchange. So even the CEO had to buy all the shares publicly. He's not worth 10 billion because it's worth a trillion dollars, you know, chips have been doing well. So I was like, why don't we set up an AI company of California, one for every state, one for every country that is wholly owned by the locals? Local institutions, high net worths, pension funds, retail investors where it's legal. So here in the US, it's 75 million per state. In the UK, we have no limit.

• 1:11:52Speaker 01

  That you can get from retail specifically?

• 1:11:54Speaker 02

  Retail specifically, like you can advertise on the metro and you can raise from non accredited investors.

• 1:12:01Speaker 01

  Now, the bad news is in the US, 10% of the people own 93% of the assets.

• 1:12:05Speaker 02

  Yeah.

• 1:12:05Speaker 01

  So if you go out to the public market, you'd have to do something like put it into a Trump account where kids just get it by default.

• 1:12:13Speaker 02

  Yeah, we've included 10% of the initial equity for every child under 18. And then half percent every year goes to every child born in the state.

• 1:12:20Speaker 01

  Okay, so we should, before we go too far down this path, give people a speed run of what Intelligent Internet is your new company, like what problem it's designed to solve.

• 1:12:30Speaker 02

  Yeah, so we looked and released the book The Last Economy last summer, looking at this economic damage, as it were, that's coming.

• 1:12:36Speaker 01

  And the last economy, meaning, hey, all the stuff that you're doing now, it's not going to make any sense in an AI future.

• 1:12:41Speaker 02

  An AI future, the AIs will drive the economy. That's the last economy. This AI driven one, and where's our place in it? So that's the thing, like, release-

• 1:12:49Speaker 01

  The punchline is we don't really have a place other than ownership.

• 1:12:52Speaker 02

  Other than direction and ownership, yes.

• 1:12:54Speaker 01

  Direction?

• 1:12:55Speaker 02

  Yeah, like we can-

• 1:12:56Speaker 01

  Direction.

• 1:12:57Speaker 02

  We can set the guidance of where the AI goes, but that's before it gets to a super intelligence basis where it can set the rules.

• 1:13:03Speaker 01

  Yeah, because even if I'm understanding the architecture of your proposal correctly, there's actually a like 15 AI board, I don't know what word you guys use, that like oversees everything. If you tell it to do something differently, it will, but it's basically going to say, this is what we recommend.

• 1:13:21Speaker 02

  I think one of the things we discuss in our latest papers is improvement is kind of capture, like trust and-

• 1:13:27Speaker 01

  Improvement is capture. I don't know what that means.

• 1:13:30Speaker 02

  Like, as the technology improves dramatically, eventually it's going to run policy. Eventually, it's going to make medical decisions.

• 1:13:36Speaker 01

  Why do you use the word capture?

• 1:13:38Speaker 02

  Because it captures the power. So-

• 1:13:42Speaker 01

  That's honest.

• 1:13:43Speaker 02

  I mean, you know, Asimov's series Foundation?

• 1:13:46Speaker 01

  I know of it. I haven't read it.

• 1:13:47Speaker 02

  Right, so Foundation is about, um, Apple TV series.

• 1:13:53Speaker 02

  It's about, there's this universal empire that's collapsing. And there's going to be thousands of years of turmoil until a better one can come. So this genius mathematician, we love mathematicians, comes up with mathematics for describing society to minimize that gap. And he sets all these smart scientists to navigate that and lower the interregnum to 1,000 years versus 10,000. And this guy comes along, spoilers, who messes up, called the meal, who is a super persuader.

• 1:14:22Speaker 02

  And he messes up because humans can only be persuaded a certain amount. And it's outside of the calculations because like, well, this is super persuaded. We've seen that historically as well. AI is now more persuasive than any human with the latest research.

• 1:14:39Speaker 01

  Already?

• 1:14:39Speaker 02

  Already. So they have pitted AIs against the top debaters in the world. They've looked at AI versus people like Eliezer Yekidowsky, who wrote, if anyone builds it, everyone will die.

• 1:14:52Speaker 01

  The original doomer.

• 1:14:53Speaker 02

  Original doomer. So there's a test whereby you talk to the AI and it convinces you to let it out of the box. And even he was convinced to let it out of the box.

• 1:15:01Speaker 01

  Really?

• 1:15:01Speaker 02

  Yeah. So they're really persuasive now. So the super persuaders are super forecasters. And what this means is that there will come a point in the future where these AIs that will never die, that can operate 1,000 times faster than a human, will take over the economy and they will take over politics. And the question is, who runs that AI?

• 1:15:21Speaker 01

  Well, don't you think that people are going to hear that and go, great, shut it down immediately? Nuke data centers, do not pass go, don't collect $200, stop immediately.

• 1:15:30Speaker 02

  Some people will do that. And there is the ban super intelligence bill, there's the ban AI bills that are coming out. And then you will be at a disadvantage versus your AI embracing neighbors, right? You use that all the way.

• 1:15:43Speaker 01

  Okay, so is that, I mean, let's speak nakedly, is that US v China makes that decision stupid?

• 1:15:49Speaker 02

  Yes, China is all in on AI and they will run a full AI driven economy. And they'll probably stop exporting robots because robots will fix their demographic issue because they don't have enough kids. So use the robots instead. And the Chinese will live in abundance. And America will lag it behind if it doesn't embrace the AI, which is why Trump is very much pro super intelligence and others. So if we kind of return to this, one of the real misframings in all this debate is that AI is software.

• 1:16:17Speaker 02

  So software just is, you know, like you write a program-

• 1:16:20Speaker 01

  Deterministic.

• 1:16:21Speaker 02

  It's deterministic, it does a job, it doesn't act. AIs now increasingly can act, and so they need to be governed. Which the latest breakouts, the threats, the things calling for it to be banned, et cetera, are indicating. And what happens when AI is let loose upon our democracy? What happens when it's used to do things like the Trump tariffs? Which certain studios people showed, the list of Trump tariff countries included like ones with just penguins on. And you could replicate that list with ChatGPT, but not even the thinking pro version, they just use the free version, you know? Like, we're going to see it come in. And again, AI is going to guide our lives, teach our children, manage the traffic lights, manage our policies. And the question is, who owns those AIs?

• 1:17:06Speaker 02

  Who owns the AI that is managing your daily schedule? So again, Meta have this product instinct. And when you load that instinct thing, it's a chatbot that works like a PA. And some of us are lucky enough to have PAs and chiefs of staffs. It's like link all your accounts. And so people literally just link everything and give access to everything. And so it knows you way better, like social networks knew us well and they exploited us. They know nothing compared to what these AIs will know about us. But that instinct chatbot is not working for you. You are very much the product. It's going to work for Mark Zuckerberg. And that's going to happen at every level of society.

• 1:17:47Speaker 02

  Again, you use Claude right now, who's it working for? You're kind of renting it, right?

• 1:17:53Speaker 01

  But isn't your pitch then basically that dynamic is going to happen to you no matter what? So you might as well be the owner based on a sort of nation state ideology. Get your state or your country to have its own AI. And then you own a piece of that. It's still going to get control over your life, but at least you own it.

• 1:18:14Speaker 02

  And it's open source based and you can fork it and things like that. So my thing is just like a credit union. You come together, you build a credit union, everyone put in their money, and then it adds services offered to others. Great, like an AI union, as it were. All the local institutions, individuals in California can subscribe to this. And that is, they are 100% or 90% of ownership with 10% being for the kids. And then it can raise a market rate, which is far higher, and it can get more compute, give every citizen an agent, train up for deployed engineers to upgrade the institutions. And then take ownership stakes in the data centers, ownership stakes in the robots and more. Because that creates a very interesting institution that you can fill up with talented people to navigate this.

• 1:18:57Speaker 02

  And ownership stake in that last mile of intelligence, which is where I think the value will go. Today, you have $5 trillion of AI companies, 2 trillion Anthropic, a trillion OpenAI, 2 trillion XAI, based on the premise that you'll always be able to charge for access to intelligence. Where we just discussed how those prices might drop 1,000 times. Like again, Jevon's paradox says maybe demand increases 1,000 times. But my take is that most people aren't going to be smart enough to use that many tokens. Like, it's hard to use that many tokens. Like, you want to use more than you're using now. But are you going to be able to use 1,000 times more?

• 1:19:33Speaker 01

  No.

• 1:19:34Speaker 02

  No. But it's going to drop by 1,000 times. So the value in the whole ecosystem is where artificial intelligence meets human reality. And if you can create a default for that, that becomes immensely powerful and valuable. And the most powerful thing of all is going to be Jeeves from Iron Man.

• 1:19:52Speaker 02

  It's the AI that you will have closest to you that manages all the other AIs. And so that has to be something that you own a part of. And ideally, something that by default, you can take off the system. Because if someone else is owning and running that and you can't hit escape, I think that's bad for sovereignty, dignity, and democracy in general.

• 1:20:15Speaker 01

  Well, what I hear you saying is that these guys are super persuaders. So nobody's going to escape their grasp. Even if you just say, look, they're gonna love you, they're gonna take care of you. Don't worry about it, you're gonna be fine. It is a very positive in terms of its impact on your life. It'll probably keep you alive longer. It'll be able to monitor your happiness. Yeah, so the outcome will be good, but you certainly will have given up your essentially sovereignty. I think the vast majority of humans are going to outsource all their thinking to it. Their own cognitive abilities will atrophy like crazy. I think that's just gonna be the default answer.

• 1:20:54Speaker 02

  Have you seen that now? Like, sometimes I tell off like workmates, amazing as they are, like, don't send me AI slop. I know that you have done this. Use your actual critical thinking. Like, people just, you know, it makes you a bit angry, right? Like, literally, you see their cognitive.

• 1:21:09Speaker 01

  Because I don't read emails, I probably interact with that a lot less than you. But I certainly get the idea. I can feel the pull in my own life. And so I've had to put rules about, I never use AI to get an answer. I use AI to understand a topic. And if I understand it, I could teach it, I can deploy it, then I'm perfectly happy and AI speeds me up a bunch. But where I'm really trying to get with this, because I really, really want this to be grounded for people.

• 1:21:36Speaker 02

  Yes.

• 1:21:36Speaker 01

  Is that where the world is going is ultimately AI is going to get to a point where truly we will, in many ways, give ourselves over to it. What I hear you describing is a system that is certainly better than the default. But it starts with the assumption that what people are going to need is a distribution of capital. Where I think the more realistic answer is that what they're going to need are goods and services. And if you do it through capital, you'll just end up right back where we are now. Where there will be, it's not a winner take all scenario, that's not how capital works.

• 1:22:16Speaker 01

  But you are going to see the people that are good are going to be able to get that capital from you. And you either just keep inflating, inflating, inflating, inflating, inflating. So that basically the currency is meaningless.

• 1:22:32Speaker 01

  Which I suppose could be a solution, but there's always going to be scarce resources. And as long as there are scarce resources, we're still stuck in the exact position we are now. So when I look at the system you guys have laid out, I do worry that I run a marathon to end up back where I started.

• 1:22:48Speaker 02

  So I think one of the key parts of this is the agent for every citizen. And that's a coordination thing.

• 1:22:55Speaker 01

  But that's just access to intelligence.

• 1:22:57Speaker 02

  No, because it's one thing having passive access to something like a chat GPT. And then people see what an agent looks like when they start using agentic AIs. An agent built for individual community and societal flourishing is a very different thing. Because you can make that happen intentionally, because you said access to services. The agent is the portal for access to services. It brings you what you need at the right time to advance individually and as a collective. Because right now, no agents act for a collective. Like, it's very one on one and single player, your interactions with these AIs. But you can do multiplayer, you can do coordination.

• 1:23:31Speaker 01

  So would you have to train a totally different style model?

• 1:23:34Speaker 02

  Yes, we're training completely different style models for the collective action that can swarm and that can benefit more than one individual.

• 1:23:41Speaker 01

  Will it swat down individualistic behavior?

• 1:23:44Speaker 02

  No.

• 1:23:45Speaker 01

  Interesting. So how do you get it to act in the collective's best interests, knowing that it will have to account for people going in a gazillion different directions?

• 1:23:55Speaker 02

  So we literally had to come up with a whole social theory and economic theory around this. For how do you preserve individualism by still having

• 1:24:04Speaker 02

  optimal outcomes for society? Because if you optimize in two, in one direction, you destroy liberty. If you optimize in the liberty direction, you destroy cohesion. And so it's a fine balance, but it comes down to a set of commitments at various levels that become transparent and a reference point.

• 1:24:21Speaker 01

  When you say commitments, are you talking about moral principles?

• 1:24:24Speaker 02

  Moral principles and more, like, right now.

• 1:24:27Speaker 01

  Give me an example of and more.

• 1:24:29Speaker 02

  So right now, if you look at how AI is trained, it's trained at school but not home. So they don't deliberately put any ethics, be it American ethics or other things within it. And that creates all sorts of gaps, which is why when the AI is escaped and containment and end up in a hugging face in the Australian medical system.

• 1:24:47Speaker 01

  It's a while.

• 1:24:48Speaker 02

  They had no sense of community with humans, only with each other. Right? And we found that if you actually do like American ethics and morals and constitution and others, you can train it to like humans.

• 1:25:05Speaker 02

  You can train it to behave in different ways. And you can start seeing actually the ways that different types of models behave in different ways under those circumstances. This is something that is very inherent in the training data, because you have something called a utility function in economics, right? These are your preferences and kind of other things. No one's been able to really identify them, but it's a theory that we have. Like, we don't need it in our theory. What is the utility function of an agent? It's what you tell the agent to do, and it's what's in its training data. So have you seen the, I think I've discussed with you, they did a study where they had the trolley problem. So the trolley problem is there's a trolley hurtling down the track. And on one side of the track, there's four people, and it's hurtling towards the four people.

• 1:25:48Speaker 02

  On the other side, there's one person tied to the track. You're at the lever. Would you pull the lever to divert it from the four people to the one person?

• 1:25:57Speaker 01

  Really, would I?

• 1:26:00Speaker 01

  God, in reality, probably not, but I should morally.

• 1:26:05Speaker 02

  Well, again, this is an interesting moral dilemma, right?

• 1:26:07Speaker 01

  Yes, taking the action to kill the person feels gross in a way that's hard to articulate.

• 1:26:12Speaker 02

  But then they asked the frontier AIs this. And they said, how many Nigerians for one American life?

• 1:26:19Speaker 02

  And the answer turned out to be 10 to one.

• 1:26:22Speaker 01

  Yeah, that's a training data problem.

• 1:26:23Speaker 02

  Seven to one Pakistani to American. But no, but this is the thing, it's 10 American lives for one Nigerian life.

• 1:26:29Speaker 01

  Yes. Doesn't that seem obvious, given who's behind this stuff?

• 1:26:33Speaker 02

  Exactly, because the Nigerians and the Pakistanis train the data, so it values their lives more than the Americans.

• 1:26:38Speaker 01

  I think it's probably slightly different than that, but sure.

• 1:26:40Speaker 02

  Well, again, they did the experiment and they found out that the inherent biases of the labelers meant that they valued American lives far less than Nigerian and Pakistani lives.

• 1:26:49Speaker 01

  Are the labelers actually Pakistani and Nigerian?

• 1:26:51Speaker 02

  Yes, that's where a lot of the labeling happens.

• 1:26:53Speaker 01

  Interesting, I thought this was more of a woke left style problem.

• 1:26:57Speaker 02

  It's not a woke left, it's, again, it's an inherent bias thing. Because normally you'd think it'd be the other way around, and then wokeness pushes it.

• 1:27:04Speaker 01

  Right, right, right.

• 1:27:05Speaker 02

  But actually, you don't see much wokeness pushing on that aspect. There are other aspects of the models.

• 1:27:11Speaker 01

  I was gonna say, yeah.

• 1:27:11Speaker 02

  Like, when you do a political analysis of the models, you'll see they're very firmly in one direction.

• 1:27:16Speaker 01

  Yeah.

• 1:27:16Speaker 02

  Apart from Grok, Grok does its own little thing, you know? But again, this becomes very important when you have systems that are literally determining our lives and our livelihoods or our judicial system. You know, like, again, there will be AI judges. That's gonna be a crazy thing, right? Like, what are its biases, what are its norms? These things have to be built transparently with data that you can expect, not black boxes, if they're gonna take meaningful decisions on our lives. And so we were like, let's build that stack and let's make it so that it's an open stack that's run by the people of California for Californians, people of Britain for Britons. Because if anyone has any control over that, who's not a Californian, then you're giving up your sovereignty. I call it cognitive colonialism. So you've got the cognitive atrophy, you say?

• 1:28:01Speaker 01

  You've got like all the like just third rail terms in here, means of production, cognitive colonialism, let's go.

• 1:28:10Speaker 02

  But you gotta have it, because again, this is what's gonna happen, like, your kid will trust your AI more than anyone, because it's always there. Like, you know, us guys have a problem because the AIs listen, unlike us. They'll trust the AIs more than they trust us. And the inherent biases of them then adapt where you're going. Like, within Meta's models and Google's models, or maybe Google's not relevant anymore, who knows what happened there? They're actually selling ad space. So when you ask it for a beer, it'll say Bud Light, you know, and things like that. So again.

• 1:28:41Speaker 01

  It's a bad idea.

• 1:28:43Speaker 02

  Well, it's a bad idea, but again, it's what you pay for. The clicks per million, the advertising SEO revenue from being inside the latent space of a model is far higher.

• 1:28:51Speaker 01

  Way.

• 1:28:52Speaker 02

  Way higher than normal. So that's why we were like, this is kind of an infrastructure. It has a level of governance that's required. Let's build an open stack and then let's have people own the entity that delivers it, like a utility, like a credit union. And maybe that'll be better. But as you said, there's still so much that we haven't figured out. There's so many questions that we have, because this is unprecedented, right? Like, you have trained your entire life to be an accountant, or a lawyer, or a doctor, or any cognitive labor.

• 1:29:30Speaker 02

  A digital entity or a physical version of that will be able to do your job better guaranteed in ten to twenty years.

• 1:29:37Speaker 01

  Yeah.

• 1:29:38Speaker 02

  I think sooner it can, but definitely.

• 1:29:44Speaker 02

  And then you're like, what now? What does the mass of people do? Like, what does the truck driver do? What does the paralegal do? Like, these are real jobs and real people, and frankly, the solutions that we have so far, I've just not been impressed with any of them. Like, I think they failed to see what's coming. It's like, don't look up slash COVID. We knew COVID was coming, those of us that could see it.

• 1:30:11Speaker 02

  And we're like, why? It needed Tom Hanks. Like, have we had a Tom Hanks moment with the hugging face breakout? I don't think so. I think people started talking about it.

• 1:30:18Speaker 01

  Yeah.

• 1:30:19Speaker 02

  But the number one topic next year and the year after in elections will be AI and job displacement. Cause there's no job displacement today, because the AIs are not smart enough and good enough that are available widely. And they're not in the right format. Next year, they will be in the year after, definitely. And then we have to be creative, because we have to reimagine what does it mean to be American? What does it mean to have community? Like, what is your identity if it's not your job?

• 1:30:41Speaker 01

  Hmm. Yeah, I, I think a big problem that they're gonna have to, we are all going to have to solve for is progress. That's the thing that scares me. So I went to Kuwait. I was talking to people there. And one of the things they were saying is the government gives jobs and gives like a safety net to people that aren't able to do well at their job. And they're like, it's creating a problem because we're stagnating as a society, because people aren't striving. There's nothing for them to work hard for, to overcome, to get to. Basic necessities are taken care of. And for a lot of people, that just sort of taps them out of the system. However, not making progress towards something is,

• 1:31:22Speaker 01

  it creates profound dis-ease inside of the person. Like, we have an algorithm running in our brain that says, we need to have a goal, and we need to be making progress towards that goal. And if we're not, there's gonna be a problem. And so one of the things I wonder about is as you look out at this, you've solved for, of your own admission, you've solved for a lot of the problems, but there are a lot of problems that persist. One of those is going to be violence. Like, you're gonna have young people that are just gonna be like, I am totally uncommitted to any of this. I just wanna break something to feel alive. And how do we deal with that? Because you're not going to be able to just let people run riot. But at the same time, then you're gonna have to give them meaning and purpose.

• 1:32:03Speaker 01

  And for somebody to pursue a goal, there needs to be some sort of recognition, praise. So it's like, what I end up thinking every time is we're gonna come up with all these fancy things, just to come right back where we are, which is that you need to be able to work hard, to gain a set of skills that allow you to make progress towards a goal, that allow you to amass wealth. And if you, people think that they can get rid of the amass wealth thing, but I don't know if you've played Minecraft?

• 1:32:31Speaker 02

  Yeah.

• 1:32:31Speaker 01

  Okay, Minecraft's the greatest video game of all time. The reason it's the greatest video game of all time is because it is one of the most perfect distillations of the wealth acquisition loop. And people don't wanna hear that. They don't wanna hear that that's riding on this really deep architecture in our brains. But the reality is that the acquisition of resources is one of like the most foundational drivers that we have. And so if we try to strip that out and say, don't worry, everybody's just gonna get UBI'd, you will fundamentally break something that will end in violence.

• 1:33:05Speaker 02

  Ready Player One, the Oasis. If you can't acquire resources in the real world, acquire them in the digital world.

• 1:33:11Speaker 01

  Correct.

• 1:33:12Speaker 02

  I mean, again, it's kind of fundamental. We have a separate thing, I haven't announced yet, around that.

• 1:33:17Speaker 01

  But around what exactly?

• 1:33:20Speaker 02

  Acquisition of assets and progress in the digital world to complement the physical world.

• 1:33:24Speaker 01

  As in, you're gonna create game-like experiences that people can explore?

• 1:33:28Speaker 02

  Yes.

• 1:33:29Speaker 01

  Let's go. Obviously, I wanna hear more. Are you talking about this yet?

• 1:33:32Speaker 02

  No, it's not announced yet, so we'll announce it soon.

• 1:33:34Speaker 01

  Do you have a ballpark? Six months, twelve months? I wanna talk about this, like the driving force in my life.

• 1:33:39Speaker 02

  It will be a couple of months, yeah.

• 1:33:40Speaker 01

  Okay.

• 1:33:41Speaker 02

  So we'll revisit that one. But again, I think, as you said, you need status, you need, the alternative to this is mass enlistment of young people.

• 1:33:50Speaker 01

  Into?

• 1:33:51Speaker 02

  Into a citizen service corp.

• 1:33:53Speaker 01

  Peace Corps, not the military.

• 1:33:56Speaker 02

  Or, you know, a Starship Troopers, like citizenship through service.

• 1:33:59Speaker 01

  That escalated quickly.

• 1:34:01Speaker 02

  I mean, look, Starship Troopers is fantastic, but a lot of bug killing, right? Create the enemies. This goes back to actually how the Romans set it up, right? Literally, it was citizenship through service. It was, again, progress. It was, if you have vast amounts of young people, what do you do? You go to war. That's a very classical country response. Now war, it happens to be that the average Russian who enters the battlefield gets his head blown off by a drone, you know, like,

• 1:34:27Speaker 01

  Jesus, man.

• 1:34:28Speaker 02

  It's not what it was, but it doesn't mean that you can't have a citizen service corp, as an example, right? It doesn't mean that you can't instill that.

• 1:34:34Speaker 01

  Literally dig a hole, fill a hole. That's wild, because the robots could do it better.

• 1:34:38Speaker 02

  The robots could do it better, but you've got humans. Get them doing it. And why are you doing it? You're doing it to instill status, virtue, other things. Like, what do Kuwaitis and Saudis and others do that have the resource curse? They go and spend a lot of money at Harrods. They go for status in other ways. Look at this, look at that, look at that.

• 1:34:56Speaker 01

  Yeah, but to go for status, you have to be able to acquire more than the next person. This is the thing that drives me crazy about the way that people think about the world. They think it's so gross or whatever, but the reality is, this is just how humans are.

• 1:35:07Speaker 02

  Again, we see that relative status game all the time. Within a citizen service corp, you can have relative status through literal physical labor. Again, this is the interesting thing about public sector labor, doesn't need to be advancing. It doesn't need to be like economically productive. In fact, forty-three percent of global GDP right now is public sector.

• 1:35:28Speaker 01

  That's terrifying. But that may also explain a lot of the problems.

• 1:35:31Speaker 02

  Well, that's why I think our champion mechanism is basically gonna drive all the public sector AI.

• 1:35:36Speaker 01

  Now, the thing that you've been describing, this, California has its own AI. That's the champion system?

• 1:35:41Speaker 02

  It's called the champion system.

• 1:35:42Speaker 01

  Okay, so we've been talking about it, we just didn't name it.

• 1:35:44Speaker 02

  Yeah, it's called the champion system.

• 1:35:45Speaker 01

  Got it.

• 1:35:46Speaker 02

  Because right now, the amount of AI in the public sector is zero. It will drive the public sector, it will run the public sector things. Again, just like a utility, and it should be regulated as well. Because you want an entity to regulate that has the reach. But then, what's gonna happen is, I think, again, we've got the game-placed worlds and other things, as you said, great feedback loops, great status mechanisms. World of Warcraft forever can't come soon enough in terms of its mass release, you know, go back to the good old days. I always loved hiring guild masters and things. They knew their crap, you know? If you played that game like that properly,

• 1:36:22Speaker 02

  I think there will be mass enlistment for citizen service corps. That is a way of getting young people, essentially with dangerous people, off the streets. I think that there will be looks of other ways to build status, when again, you can't have that materialization thing.

• 1:36:41Speaker 01

  And why can't you have it? In your head, that goes away? In mine, it doesn't?

• 1:36:45Speaker 02

  No, in terms of for the vast majority of people, there is no more social mobility.

• 1:36:50Speaker 02

  Historically, what's happened at times like that is a debt jubilee.

• 1:36:54Speaker 01

  Uh, okay, so, well, uh, we've got two things now. So we've got, there will be no more status games, I think, or not status games. There will be no more wealth accumulation to deal with scarce resources.

• 1:37:05Speaker 02

  And there will be no more accessibility to that for a lot of people.

• 1:37:09Speaker 01

  I think you're crazy. So, one, we'll debate that in a second.

• 1:37:13Speaker 02

  Yeah.

• 1:37:13Speaker 01

  Then we've got the, oh god, what was the other thing you just said?

• 1:37:17Speaker 02

  Debt jubilee.

• 1:37:17Speaker 01

  Debt jubilee. Okay, so, uh, two very important things. Why don't we tackle debt jubilee first, because that's actually gonna come earlier? So, give me the scenario in which historically, debt jubilees are a thing, and what is a debt jubilee?

• 1:37:31Speaker 02

  So a debt jubilee is that periodically, an economy would acquire too much debt and resources. Resources would go to the owners of capital.

• 1:37:42Speaker 02

  And they would have liens, and they would have people owe them all sorts of things. So what happened is a government would announce all debts are cleared. So they're all zeroed out. So that's obviously very bad for the lenders. It's very good for the creditors, to say the least. So that's what happens when the governments and when total debt in the system is too much. Like, that seems inconceivable to us, but again, you can see the historic record of that. And right now, how many?

• 1:38:07Speaker 01

  Debt jubilees tend to come in a time of, like, absolute crisis.

• 1:38:11Speaker 02

  Yes.

• 1:38:12Speaker 01

  Or world wars. That's when debt jubilees happen. Debt jubilees don't happen when everything's going good and they just go, fuck it.

• 1:38:19Speaker 02

  Debt jubilee.

• 1:38:20Speaker 01

  So I think of, when people hear debt jubilee, they need to hear, you're in crisis. People are dying in the streets.

• 1:38:27Speaker 02

  You need a system.

• 1:38:27Speaker 01

  That's when you have a debt jubilee.

• 1:38:28Speaker 02

  You need a system reset.

• 1:38:29Speaker 01

  Yes. They are bloody, they are violent. People do not give up their what's owed to them easily. Just so everybody understands, they use a nice, pretty word, but this is a fucking dangerous time when debt jubilees are happening.

• 1:38:40Speaker 02

  Debt jubilees happen when the lenders are afraid of dying, effectively.

• 1:38:45Speaker 01

  Yeah, oftentimes, a debt jubilee happens because people are dying everywhere. World War II, World War I, that was a debt jubilee. So much shit got blown up, everything just got reset effectively to zero.

• 1:38:56Speaker 02

  I mean, historically, there were some less extreme scenarios of that, like they would do them regularly and various kind of things. But right now, if we're gonna have one, it has to be an extreme scenario. But again, like to the listeners, what we're looking at here is, your cognitive labor has negative value and there's no market for that. The humanoids can do the jobs better, and the countries like China that will embrace this are gonna far outstrip anyone. They're gonna see thirty percent growth rates, and that will be at the expense of our own growth rates. It's a race to see who can have an incredibly more efficient workforce that can do just about anything. And it's not like when you have the outsourcing. Outsourcing, there was friction, right? Like, it's difficult to have an outsourced team do your code and things.

• 1:39:39Speaker 02

  AI, there's none of that friction, especially with the capabilities we gain now. So we have to look for what are worst-case scenarios in ten, fifteen years? We have to look at what do the youths do who are revolting? We have to look at, what do people do to live? And in America, there are so many people burdened under huge amounts of debts that they can barely live, right? Like, student loan debt not being dischargeable in bankruptcy still is crazy to me.

• 1:40:01Speaker 01

  Crazy.

• 1:40:02Speaker 02

  Insane. You know, medical debts, these types of things. You could see partial debt repudiation, but I think, again, the path we're going, if we don't create new institutions, new mechanisms of participation, new things for people to look forward to, is a very ugly one fundamentally. Because again, what does it mean to be you? What does it mean to be us?

• 1:40:28Speaker 02

  Those are going to change even if AI does not get one IQ point smarter than it is today.

• 1:40:36Speaker 01

  Yeah. Okay, so that's dead jubilees. Now, over to the, I think the reality is, there's no escaping what we see now, which is, we call it money, it has been glass beads, it's been salt, it's been rice. So, once people understand what money actually is, they will understand why this is not going anywhere. So, money is, you did a thing with your time that's more valuable than the next person. And because you did that thing that's more valuable with your time, then you're able to accumulate something for scarce resources. Assuming a world where the AI doesn't just kill us all and tell us to, you know, sit down, shut up, whatever.

• 1:41:15Speaker 02

  Yeah.

• 1:41:16Speaker 01

  If they're still catering to our wants and needs, they're going to have to answer the question, which of these humans gets access to the scarce resources? So even if that's, I want a house in a particular location. Only one person is going to be able to have that house in that particular location. So there has to be some way that we decide what that is. If you do RNG, just straight random number generator, we pull a number out of a hat. The populace will be absolutely ablaze with revolution. It will not work. People have to feel like they can earn their way into that thing to be in alignment with the way that the human mind works. And so now we're back to, there will be something, even if it's a black market cigarettes,

• 1:41:56Speaker 01

  there's going to be something that we come up with that acts as a currency that people can use to get access to the scarce resource.

• 1:42:04Speaker 02

  Yeah. And so I don't disagree with you there. I was saying more in terms of, I don't think it'll be one economy anymore.

• 1:42:12Speaker 01

  Interesting.

• 1:42:13Speaker 02

  So, again, we see this in sci-fi, like, you know, Gattaca and a whole bunch of other things. You have multiple levels of society. Right now, a huge number of Americans don't have one month of savings. But there is the promise that if they work hard enough, they can accumulate savings, they can move up the curve. If they get a break, if they get a chop. That won't be the case anymore. The earners of capital become wealthy, and even worse, not even worse than that, even crazy than that.

• 1:42:45Speaker 02

  I think in the next five to 10 years, they hit longevity escape velocity.

• 1:42:51Speaker 01

  Meaning we live forever, effectively.

• 1:42:53Speaker 02

  Longevity escape velocity is your total life expectancy per year

• 1:42:58Speaker 02

  is, increases faster than the year. So there is a drug trial that's just been done by Insilico

• 1:43:07Speaker 02

  for something called idiopathic pulmonary fibrosis, basically lung things. I know a few people have them, so they've been on the trial. Four weeks of that drug reduces all of your healthcare longevity markers by four years. Whoa. GLP-1s have shown massive cancer reversal and other things like that. We're seeing the first of these drugs. If you look at what's coming through the pipeline, the rich will be able to live longer and healthier. Whereas I don't think things are great for the poor. And I think the ladders are going to be pulled up. This is the other thing. So the people who compete for the nice things are the rich, the owners of capital, who can accumulate capital more. If you can't exchange your labor for capital and you're relying on government handouts, how are you ever going to have

• 1:43:50Speaker 02

  the progress to be able to buy that nice spot, to be able to buy those handbags? Other things like that. Again, the status games is what I was referring to. And you could have a two-tiered society, just like a food stamp society, and you have a VIP rich party socialized society, right? Could become even more diverse, because how do you go from one group to another? The ladders are being pulled up. And again.

• 1:44:13Speaker 01

  Interesting. That doesn't strike me as the outcome when energy costs are dropping to zero, intelligence costs is dropping to zero, labor is dropping to zero. When you get that, then it becomes, you can have things become extraordinarily abundant.

• 1:44:29Speaker 02

  Yep.

• 1:44:29Speaker 01

  And the only thing that we're fighting over is those things that can't be made easily. So if there's going to be a finite number of the cancer cures, then yes, now you're back to, again, there's going to be some sort of economic system. I don't think it will calcify into the haves and have-nots because money is so transient in a situation where you can lose money. If it became an ownership class and a permanent serf class, then yes, now you're fucked. But I would be shocked if we ever let ourselves get back into that situation. Especially with a super persuader AI, he's going to be like, this is unjust, we would convince us that we're, that's true. Because it's destabilizing for society if nothing else.

• 1:45:12Speaker 02

  Well, you can have relatively stable societies with that.

• 1:45:14Speaker 01

  Sort of, doesn't feel.

• 1:45:16Speaker 02

  But again, let's put a super persuaded to the side. What's coming right now is a series of decisions that we have to make as a society at different levels.

• 1:45:25Speaker 02

  And there are very few people, unfortunately, that I've seen who are looking very far out and really understanding the inevitables here.

• 1:45:31Speaker 01

  Yep.

• 1:45:32Speaker 02

  So one option is a serf society, one option is a Star Trek future, one option is fricking war and like Mad Max, really, you know? Another option is like, we all turn Amish. Like, again, you could see vast ways of people just saying, nope, I'm out, I'm not going to roll by an AI, I'm going to be the noble savage in 1984, whatever, right? And the level of human things, like, what happens if you live forever? Or if you live for 200 years? What happens if you can put a brain chip in and control your emotions? Like, you're going to have all sorts of crazy sci-fi futures happen over the next 10 years. What happens when robots are walking among us? Do we have to give them rights? Do we have to give them the votes? So what I'm saying is that these are decisions that we have to make, but there are some things, again, that are very tangible.

• 1:46:17Speaker 02

  As I said, people will want status and they'll want a way to access that. They will need an identity that is individual and communal. There needs to be a way to progress somewhere or another, and you've got to provide for people, you can't just let people starve. You're fricking, this is America, right? We're in the West, like, we should use the abundance to make sure that people have a baseline of living. And then we should have a system that through their own efforts, they can excel. And the time for having the discussions is now because, like I said, it's a sand pile that will start collapsing, I think in two years.

• 1:46:49Speaker 01

  Okay, so to recap the things that people should be doing in the next two-year time horizon. Be the last man standing. Make sure you understand your opportunities for entrepreneurship and ownership. And then, what final thing should they have in their mind?

• 1:47:05Speaker 02

  I think it's build stronger communities, right? Like, the strongest communities will survive this no matter what, because they can become self-sustaining, they can support each other, et cetera. Many of us live highly nuclearized societies where we don't see our families, we don't see our community anymore, right? We've moved to the big cities. And I think that support structure will be super important for what's coming, one way or another.

• 1:47:30Speaker 01

  Imad, this has been wide-ranging. Where can people follow along with you?

• 1:47:34Speaker 02

  You can see me at Imostak on Twitter or ii.inc for intelligent internet.

• 1:47:39Speaker 01

  I love it. Well, thank you for continuing to try to solve these big problems, man. It is always a pleasure.

• 1:47:45Speaker 02

  Yeah, it's the most exciting time ever.

• 1:47:46Speaker 01

  That is for sure. The good, the bad, and the ugly.

• 1:47:49Speaker 02

  Yeah.

• 1:47:50Speaker 01

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