Live in the Future

Summary

Naval Podcast: "Live in the Future" (July 2, 2026) — Summary

Episode Overview

In this lively, irreverent, and wide-ranging roundtable, Naval Ravikant hosts Gary Tan (Y Combinator), Daniel Gross (Able Police), Farboud (Alist), and unidentified friends for a drinks-fueled debate on the state, risks, and promise of AI. They tackle AI's transformative pace, the future of work, geopolitical ramifications (especially China vs. US), the fate of open-source models, the nature of human productivity, and anxieties about creativity and meaning in a world increasingly dominated by automation and intelligent agents. The conversation is characterized by high energy, candid skepticism, dark humor, and a founder-to-founder sharing of practical lessons.

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Key Discussion Points & Insights

1. AI’s Rapid Advancements and Perceived Exponential Growth

• Orders of Magnitude Change: Gary describes how compute for AI is set to increase by as much as 90,000x over the next several years, challenging assumptions that current AI is anywhere near its plateau.
  • [02:56] Gary Tan: "Craziest idea...if you’re just willing to spend $100,000 a year on tokens, you can basically live like you are a normal citizen in 2028...compute is going to go way, way up—like, you know, we think like 90,000x..."
• Practical Impact: AI is not just theoretical anymore; founders are living inside the exponential curve, building agents and personal stacks that “make them feel like citizens of 2028.”

2. Centralization vs. Open Source & Geopolitical Shifts

• US vs. China: The group discusses how the US focuses on closed, frontier models (OpenAI, Anthropic), while China aggressively pushes open source (GLM, Fable).
  • [03:22] Daniel Gross: "Is open source going to be good enough for most use cases or are you always going to need the frontier proprietary models?"
• Commoditization of Software: Daniel points out that as AI eats software, software advantages become fleeting, benefitting China which dominates in hardware.
  • [31:56] Daniel Gross: "Software was eating the world and AI eats software. So now software is commoditized...that helps China."

3. AI’s Societal Impact: Work, Meaning, & Agency

• Transition Anxiety: There’s deep concern about the speed of change, particularly for white-collar jobs, echoed in comparisons to industrial revolutions and the demise of farm work.
  • [10:46] Daniel Gross: "But the question is, what is the speed of transition?"
• Job Displacement & Makework: The group jokes about "bullshit jobs" and how most large companies and institutions already run on non-essential labor.
  • [11:04] Daniel Gross: "It’s already all makework jobs anyway. Right. Very few people are actually working."
• Will Humans Stay in the Loop? Past patterns in chess (Centaur chess) are cited: humans + AI used to beat pure AI, but now pure AI wins even with a human in the loop; is all creative work destined for this fate?
  • [06:27] Daniel Gross: "Chess went by. There was Centaur chess...but eventually just the computer alone beat the Centaur model."

4. Cost, Access, and the Frontier Model Oligopoly

• Token Costs & Democratization: Token costs are dropping, but still, access to the best models can be heavily gated, raising fears of AI being controlled by an elite.
  • [12:09] Daniel Gross: "It becomes a Defense Department thing. Then it's like who has access? Who has control?"
• Nationalization & Regulatory Capture: Acceleration of government oversight is noted, especially with OpenAI and Anthropic cooperating with the US government, which could stifle open access.
  • [12:05] Daniel Gross: "...Sam Altman said that Codex 5.6 will be rolled out slowly to partners approved by the US Government first."

5. Open Source Catch-Up & Security Concerns

• Model Distillation & Algorithmic Leapfrogging: The group lays out how Chinese labs are catching up or even surpassing US models—through looser copyright, distillation (copying via API querying), leaks, and talent flows.
  • [28:08] Daniel Gross: "So there's some of it that's obvious...the Chinese are doing their own pre-training...Then there's accusations that Anthropic made...they’re distilling our models..."

6. AI Writing, Originality, and “Living in the Future”

• Quality, Creativity, and ‘Skill Files’: There’s fierce debate on whether AI writing will ever rival or replace human-authored work. For now, AI prose is seen as verbose, generic, and lacking true novelty but evaluation and multi-modal skill files could change that.
  • [16:01] Farboud: "This is one reason I enjoy Twitter less. Lately...so many replies...when I get emails that are clearly written in AI, I’m like, dude..."
  • [16:05] Gary Tan: "I think in the future people will just have...skill files that extract the style and the diction..."
• Living in the Future: Gary emphasizes the best way to understand or predict the future is simply to "live in it"—use AI aggressively, max out your tools, and work backwards.
  • [19:19] Gary Tan: "...the way to...build the future is just like live in the future and work backwards."
  • [19:58] Daniel Gross: "Everyone should be AI maxing."

7. Startups, Tech Power, and Market Dynamics

• Startup Ecosystem Viability: As software commoditizes, startups face existential questions—can small teams still build significant businesses, or will general-purpose AIs render niche SaaS irrelevant?
  • [50:56] Gary Tan: "Will there still be a startup ecosystem? Because on the one hand you're shrinking the size of the firm..."
• General vs. Specialized Models: The group observes that, increasingly, the general/frontier models outperform siloed vertical models.
  • [51:28] Daniel Gross: "One of the...bitter lessons here is that the general models beat the specialized ones."

8. Future of Work: AI Handlers, Robotics, and Human Desire

• Handler Paradigm: Rather than all humans doing manual labor, in a best-case scenario, people become AI/robot "handlers," managing and guiding the tools to fulfill human desires.
  • [65:11] Daniel Gross: "There’s a good version of this...people don’t have to have just shitty manual jobs. They can actually be handling and guiding the robots and the AIs..."
• Fundamental Human Drives: No matter how advanced AI gets, human desire and motivation for novelty, connection, and meaning will persist.
• Universal Basic Robots (UBR): Jokingly, the group suggests society might be saved by UBR—a robot for every person.
  • [62:48] Gary Tan: "UBR is good. We need to have universal basic robot. Everyone should have a robot..."

9. Geopolitics, China, and the Fragility of the West

• US-China Dynamics: There’s skepticism about the prospects of open conflict over Taiwan or the South China Sea; instead, competition is through economic and technological means.
  • [57:19] Daniel Gross: "That’s the thin blue line standing between the so-called free world and the Chinese competition...I don’t think we're in competition with China."
• Chinese Competence vs US Dysfunction: The panel contrasts China’s centralized competence and speed to California’s political chaos, regulatory burden, and dire housing crises.
  • [59:53] Gary Tan: "Not only that, they [China] are actually pretty hyper competent...If you compare it to like the California government, it's disastrous."
• America’s Internal Civil War: Daniel points out the real US struggle is internal, as radicalization and demagoguery increase on both right (nationalists) and left (communists).
  • [57:34] Daniel Gross: "We have a civil war going on internally in this country...It’s nationalist versus Communists."

10. Humanity, AI Companionship, and the Line Between Tool and Friend

• AI as Companion: The group half-jokes about AI “girlfriends” and human attachment to agents, with Daniel mentioning a friend who manages property for companies that make AI companions.
  • [67:01] Daniel Gross: "You just have someone in the Filipino call center being your girlfriend...What's the difference between an AI and someone in the Filipino call center?"
• The Diminishing Distinction: Gary concedes that AI companionship, while “not my girlfriend,” is getting closer.

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Notable Quotes & Memorable Moments

On Acceleration and Living in the Future

• [01:50] Gary Tan: "At some point I met Pedro from Brex...I basically converted from like Claude code, like cult to openclaw cult within like 24 hours. ...If you're just willing to spend like a hundred thousand dollars a year on tokens, you can basically live like you are a normal citizen in 2028."
• [19:19] Gary Tan: "...the way to...build the future is just like live in the future and work backwards."

On AI Anxiety & Utopian/Fatalistic Outcomes

• [35:38] Daniel Gross: "Soon everybody will have AI anxiety. Like, we're all feeling it. We're all feeling AI anxious."
• [36:04] Farboud: "Why? Yeah, they're stressed out because they think it's going to kill us all."
• [36:23] Gary Tan: "Wait, so why is this not just going to result in Star Trek the Next Generation? Like that's, that's my hope."
• [49:00] Unidentified Guest: "...That's likely the easiest thing in the world, but no one will do it. No one's doing it."

On the Collapse of Makework & White Collar Work

• [11:03] Gary Tan: "It's already all make work jobs anyway. Right."
• [11:04] Daniel Gross: "Very few people are actually working."

On Writing, AI Style, and the Future of Communication

• [16:01] Farboud: "This is one reason I enjoy Twitter less. Lately...so many replies...when I get emails that are clearly written in AI, I’m like, dude..."
• [16:05] Gary Tan: "In the future people will just have really, really impressive skill files that actually extract like the style and the diction...you will not be able to tell, I guarantee."

On Creative Use of AI

• [28:28] Gary Tan: "Actually, I programmed a crazy thing...gbrain. It's the retrieval thing I made. It's actually basically a collider of different vector spaces...I have this thing called LSD mode...Lateral Stochastic Drift...finds bangers...give me some LSD bangers. And it will literally give me like 10 or 20 ideas..."

On US-China and Open Source

• [29:29] Daniel Gross: "AI is our Chinese against their Chinese. Right."

On Politics & Tech Governance

• [12:09] Daniel Gross: "...it is definitely much scarier that a small group of people have control over AI than everybody has it. But everybody having it is also scary because of. Well, I mean, there's the print, a bioweapon thing..."
• [40:45] Daniel Gross: "AIs are not legible by the way. ... In the future the AIs will develop their own languages. They'll communicate with each other in some kind of a binary high speed protocol. ... It’s only humans who demand the legibility, but the AIs don’t really have it."

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Timestamps of Key Segments

• 00:00–01:10: Intro, playful banter, quick founder backgrounds
• 01:10–06:00: The state of AI, “perishable knowledge,” compute acceleration, and scaling laws
• 06:00–12:00: AI creativity, Centaur models, cost as a bottleneck, nationalization, control, and democratization
• 12:00–15:00: AI writing, agent conversations, debates on authenticity and writing voice
• 15:00–23:00: Open source vs. proprietary AI, Chinese/US dynamics, model distillation, and algorithmic leapfrogging
• 23:00–35:00: Startup power dynamics, “makework” jobs, the shrinking moat of software, organization management with AI
• 35:00–46:00: AI anxiety vs. jubilation, cultural impacts, rapid diminishing of durable competitive advantages
• 46:00–57:00: China hardware edge, US startup ecosystem, regulatory risk, geopolitics, supply chains, and Taiwan
• 57:00–64:00: Internal U.S. conflict, American freedom, education as UBI, robotics, and the coming future of universal basic robots (UBR)
• 64:00–67:46: The future of desire, human motivation, AI companionship, and closing reflections

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Conclusion

This episode offers a raw, tactical, founder-eye-view into the blurring lines between AI evolution, economic structure, global competition, and the human need for agency and meaning. The group is clearly both exhilarated and unnerved by the speed of change—and their consensus is not to slow down, but to "live in the future" as the best way to understand and shape it.

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For deeper dives into any of the segments, see the referenced timestamps.

Transcript

[Naval Ravikant]

Welcome to all the legends out there listening to the Naval Podcast, the number one podcast in the universe and your authoritative source for new knowledge. We've got three founders with us here today. On my right is Gary Tan from Y Combinator. They say it's the most reliable way to become a billionaire is to join the Y Combinator program and start as a trillionaire.

[Gary Tan]

That's one way to do it.

[Daniel Gross]

We're all drinking, by the way, except one person here is not drinking. You have to figure out at the

[Farboud]

Russian Roulette who's actually sober. Yeah.

[Naval Ravikant]

And then on my left, I've got Daniel from Able Police. They started off by turning body cam footage into police reports, but now they have a whole set of tools for compliant AI chat. Translation, what else do you guys do?

[Farboud]

Citizen reporting? All kinds of things.

[Naval Ravikant]

Okay, then on my right, I've got Farboud from Alist, the health super app. As usual, we don't really care about what these guys are building. We care more about what they're learning about building, what they're figuring out, what they're still trying to figure out, and the principles that they can share with other founders. So does anyone have anything they want to jump in with?

[Daniel Gross]

I mean, the topic that everyone's thinking about right now is AI.

[Farboud]

Right, AI. Yeah, I think I've heard something about it.

[Naval Ravikant]

Yeah.

[Daniel Gross]

I kind of hate talking about it because it's the most perishable thing. Like, you know, the podcast will be obsolete by the time it ships, but it's still also the most interesting because it's the fastest changing thing in the environment. That's high impact. So it's the steepest learning curve, and you're always trying to trade notes with people to kind of see where they're at. In fact, I was at a thing with you recently where I bumped into you, and the conversation immediately turns to AI, of course.

[Gary Tan]

Got to. Yeah.

[Daniel Gross]

So we can avoid it for a little while, but I feel like we'll circle back on that topic.

[Naval Ravikant]

I got a question for you. What are you being floored by at YC in terms of, like, what you see the companies doing with AI?

[Daniel Gross]

So.

[Gary Tan]

So I think the awkward thing is, like, I basically, like, slept three hours a night for like, four months, and then somehow, like, went from not coding at all to, like, basically teaching people how to do it and making, like, one of the top 100 open source packages for how people vibe code called Gstack. So that is very, very weird. And now, like, at some point, I met Pedro from Brexit. And then after that I basically converted from like Claude code, like cult to openclaw cult within like 24 hours. And then now we use both. But like it's, it seems like basically if you, you know, the craziest idea that I discovered is that if you're just willing to spend like a hundred thousand dollars a year on tokens, you can basically live like you are a normal citizen in 2028. Like, it's just pretty clear that token costs going to come down compute is going to go way, way up. Like, you know, we think like 90,000x or so there will be 90,000x the amount of like inference from here to like three years from now.

[Daniel Gross]

You plot it out in some curve 90,000 times.

[Gary Tan]

I mean it's like many, many orders

[Daniel Gross]

of magnitude, which is kind of baked in both with the chips and the data centers are building out.

[Gary Tan]

Yeah, I mean, a lot of people say that Nvidia is way overpriced, but what if it's way, way underpriced by like several orders of magnitude. Right.

[Naval Ravikant]

Thousand by when?

[Gary Tan]

I don't know, 24 to 36 months.

[Naval Ravikant]

Okay, so five orders of magnitude?

[Daniel Gross]

Basically.

[Gary Tan]

Yeah. I mean, we might be off by a couple orders.

[Daniel Gross]

Yeah. But either way. But actually, the thing that's crazy is that if you go up by five orders of magnitude, it's not just what it does in terms of usage, but in terms of capabilities. Because every order of magnitude you go up, new capabilities emerge. And I've been pretty behind the curve on AI for a while. I missed it in 2020-2022 because I'd grown up my whole life hearing about AI when I was doing CS and just assumed it was one of those things like fusion that was never going to come. And then it came when it came, it came really fast. And at first a lot of the stuff people were saying about it sounded breathless and like they were talking their own book seemed crazy, but they turned out to be right so far. Right. So I think there were many big questions about AI coming up right now. I think one question I used to have in my mind was like, is it going to be distributed or is it going to be centralized? And now that's kind of morphed into is open source going to be good enough for most use cases or are you always going to need the frontier proprietary models? Right. There's the whole thing about like, it's weird that China is making all the open source stuff and the US is doing all the closed source stuff. And so where do we go from there, right. There's the question of is it going to be nationalized or is it going to be sort of private sector? Especially if you're saying, hey, it's a new Manhattan Project, these are the new nuclear weapons, then like private companies building them and controlling them doesn't make sense. But I think the most interesting remaining question, there's still one that I really care about over the others, where there's no clear answer yet is I think the people in the labs believe that the scaling laws are such that the AIs will keep getting smarter until they become smarter than the smartest humans, probably through the process of recursive self intelligence, recursive improvement, or what they call asi. And I think that is the big question. So two years ago you could have taken the viewpoint that AI will get you mid at everything, but it's not going to be the pro at anything. Right now you're getting to the point where it'll get you the pro at everything, but we don't know if it'll get you the, the last creative mile. Like that last bit of like moving out of the system and creating something new, not just recombining what's already in the training sets.

[Farboud]

Did the progress that it made on the Erdos math problem bother you?

[Daniel Gross]

It bothers me for sure. I mean that bothers me. It's a process of discovery. I don't want to be bothered by laws of the universe. Right. So bothered me. But it definitely surprises all of us. But at the same time I still don't see like broad general creativity.

[Gary Tan]

But anyway, that's separate bothers.

[Farboud]

I was a math major and I really loved proofs and something actually making progress in that domain in a meaningful way that looked really original. Like there's something creepy about it, almost like.

[Gary Tan]

But it was directed by someone. Right?

[Naval Ravikant]

Sure.

[Gary Tan]

So, and I, I think that that's fine.

[Farboud]

Everyone was surprised who was involved. Right, right, right. Like I, I don't know if you saw the answer.

[Unidentified Guest]

All that stuff is kind of like boring. It just means like go do something else. Like if you have limited time to think about something, do you want to spend it opining over the fact that there's a machine that's better than a human, that's something now. Or just go apply your humanness, something that you haven't thought about.

[Daniel Gross]

Or actually to riff on Gary's point, are we going to end up in a place where a machine is strictly better than a machine with a human? Like a human in the loop?

[Gary Tan]

Isn't that big?

[Daniel Gross]

That's the biggest question. Right. Like, because chess went by. There was Centaur chess. Somebody was telling me about this. But there was centaur chess, where, like, the chess computer plus the human would beat just the chess computer, but eventually just the computer alone beat the Centaur model.

[Unidentified Guest]

I guess for, like, for me, dealing with AI in the most practical way humanly possible, you know, spinning up thousands of agents for people on demand, build a massive fleet management system, an eval harness. The reality of it is, like, I don't think intelligence is the bottleneck. Cost is the bottleneck.

[Naval Ravikant]

Yep.

[Daniel Gross]

Right now.

[Unidentified Guest]

Right now when we started doing it, every single person in our app has their own open claw running for them. It's a really powerful.

[Farboud]

Yeah.

[Gary Tan]

Oh, my God.

[Unidentified Guest]

Like. Like mine wrote.

[Gary Tan]

But what about this openclaw then?

[Farboud]

What's that?

[Gary Tan]

People just want openclaw right now, or they should want.

[Unidentified Guest]

But it's not open claw anymore. Because when we started with openclaw, so expensive and opus, it was a hundred dollars a month per person.

[Gary Tan]

Yeah.

[Unidentified Guest]

We spent three, four months driving that down to $2.84.

[Gary Tan]

Do you use PI Now?

[Unidentified Guest]

We built an entire stack that is just completely wild that has an eval harness and then is like an entire agentic fleet that can spin up and down elastic so that I deal with mundane parts of that stuff all the time. I still think what's way more interesting is to think about what humans will do when they don't have to do these things.

[Daniel Gross]

But I think there is a very real phenomenon going on right now where the people who would know the most in the labs are basically saying there will be nothing left for humans to do. Really. When you read between the lines of what they're saying, they're saying in different ways, but they're saying your harness doesn't matter because within a year, the AI will be spinning up harnesses as needed, and you won't even be the consumer because it'll be talking to other AIs. And beyond the erdish problem, it'll be solving fundamental problems. Is material science and physics and math and. And engineering and health. Great. Yes. But then, you know, that's taking the average person out on the street, working them up into a frenzy. They're getting angry and scared because fear is a precursor to anger.

[Gary Tan]

Try to get all my smart friends to go work at Anthropic so that then I'll have lots of friends there who will get me into the Anthropic Level two breadline.

[Naval Ravikant]

Yeah.

[Gary Tan]

Because right now I like. I feel like, pretty solidly in level three, you know, like level one scene,

[Farboud]

there's only two jobs, all right? It'll be anthropic employ and sex worker for anthropic employees. All right?

[Daniel Gross]

I mean, that's the scary part, right?

[Farboud]

That's the one.

[Daniel Gross]

And it's getting people worked up. And there are real world consequences of that because you don't live alone. You live inside a thundering herd called humanity. And if that thundering herd decides to, like, go left towards a cliff because it's mad or because it's enraged because it's poison, you're going to go with it, you know, you're not going to be the lone bison sitting out there by yourself on the edge. The thing is.

[Gary Tan]

And people are mad, you said, like nationalization. Right. Like, that's where it would go, you know?

[Daniel Gross]

But right now that you can see that trend starting with their attacking data centers. Right, right. They're attacking data centers.

[Gary Tan]

Or that's just stupid.

[Daniel Gross]

But.

[Farboud]

No, but we look back on that. That's what we think. Like the spinning loom.

[Daniel Gross]

It's a rational response, but it's an irrational carrier. So they're saying it's because of water. It's not about water.

[Gary Tan]

That was a lie. That was debunked. Yeah.

[Daniel Gross]

It's not about refusion. I mean, it's like socialism. It's not about reason. Right.

[Gary Tan]

It's about how you get the people going.

[Daniel Gross]

You're getting poor and you want to. You want more money or you're in

[Gary Tan]

this case, you're following that city right

[Daniel Gross]

now like you're going to be replaced and you want to stop this train. You want to be like, I want off this train.

[Farboud]

That's rational.

[Daniel Gross]

I want to be on this train.

[Farboud]

Yeah, that's rationally rational.

[Daniel Gross]

So in this case of. Especially when you have the popular delusions of the madness of crowds, you have the ends justify the means. So in this case, the. The water is just a means. They find another one. If it wasn't water, there'd be some endangered egret, some bird. Are they right? Well, they can't stop it. This technology is a genie. That's what they think is going to.

[Farboud]

Like. There's been times in the past where like, yeah, like smashing, like spinning looms

[Daniel Gross]

actually stopped briefly, very briefly, and slowed it down.

[Farboud]

There was other technology.

[Daniel Gross]

We have spinning looms now, but.

[Farboud]

Of course. But there was other technologies. There's other technologies where they, like, you know, refused to issue a patent or something, so it became unmarketable because it was just like politically going to be too difficult. I think that basically we ingest like you know, 100 years ago, 50% of the labor force in the US was working on farms. And that's no longer true. Right. And now it's great. Now it's.

[Gary Tan]

That's a great thing. Now it's 2% like working on a farm.

[Farboud]

We don't have 48% unemployment. Absolutely. We don't have 48% Unemployment. And we all have food. Right.

[Daniel Gross]

But the question is, what is the speed of transition?

[Farboud]

The speed of transition. Right.

[Daniel Gross]

That one's a derivative. It's a derivative.

[Farboud]

That one took like 60 or 70 years.

[Daniel Gross]

Yeah.

[Gary Tan]

Okay, so I have good news for you guys. Have you ever worked at a Fortune 500 company? Those things are so stupid.

[Daniel Gross]

Nobody has.

[Gary Tan]

Oh yes, I worked at Microsoft.

[Daniel Gross]

No, no, I mean like nobody there works.

[Gary Tan]

Yes, exactly.

[Daniel Gross]

It's already all make work jobs anyway. Right. It's like how much of the population is working and then how much of that is working for the private sector? And then how much of that is not working in some bullshit job?

[Gary Tan]

But Graeber was right. Graeber was always.

[Daniel Gross]

Very few people are actually working.

[Unidentified Guest]

I mean, I'm working more because of AI. I got six Codex agents. I agree all the time.

[Daniel Gross]

I'm working the hardest I've ever worked.

[Unidentified Guest]

And so I just kind of think people are going to work more.

[Daniel Gross]

The productivity, some people, the leverage is way higher. But that's all true until AI can totally and completely replace you, which I don't see around the corner. But I'm more open minded about it now. I used to think that was an impossibility. Now I'm like, well, no, I got to pay attention.

[Gary Tan]

That's exactly my philosophy. It's like you have two Company A, company B, you have the same technology. Everyone has access. Like, you know, hopefully everyone has access.

[Naval Ravikant]

Well, that's a key.

[Daniel Gross]

So are we going to. Is it going to be open source or is it going to be.

[Gary Tan]

That would be great.

[Daniel Gross]

Because right now if they keep scaremongering, some of that might be. Well now you need national approval. We just saw Sam Altman said that Codex 5.6 will be rolled out slowly to partners approved by the US Government first.

[Gary Tan]

My God.

[Daniel Gross]

So he's already cooperating because he doesn't want to get shut down like Anthropic did.

[Naval Ravikant]

Yes.

[Daniel Gross]

And so it's already starting. And so then a small number of people, it becomes a Defense Department thing. Then it's like who has access? Who has control? You know, they have cyber weapons. Maybe they get to hack the systems first, maybe they get to control them, maybe they get mass surveillance that we don't. For our own good. Right. That's how it always starts. So to me, it is definitely much scarier that a small group of people have control over AI than everybody has it. But everybody having it is also scary because of. Well, I mean, there's the print, a bioweapon thing, but the bio printer labs are pretty locked down to begin with. I'm not sure how real that is.

[Farboud]

Good.

[Daniel Gross]

Yeah.

[Farboud]

Good ship it.

[Gary Tan]

Yeah.

[Daniel Gross]

And in fact, it's now coming out, which many of us already knew and been saying for years, that the funder and creators of the coronavirus COVID 19 were basically the US government and the Chinese government working in cahoots. Right. It was basically Fauci and crew in North Carolina. So the joke I tweeted was like, designed by NIH in North Carolina, assembled in China. Right. Because it's like the old Apple line. Designed by Apple in California, assembled in China. But that's basically what happened with the coronavirus. They were doing gain of function research to build a vaccine. They were being total cowboys. This is crazy stuff. I mean, anyway, I'm not saying AI is necessarily going to lead to bioweapons because to the extent that AI would lead to bioweapons, right now, you know, some smart biohacker student could already do it, Right? So it's not guns don't kill people, but it don't kill people. It is democratizing a certain capability.

[Unidentified Guest]

I mean, game theory wins out in the end one way or the other.

[Daniel Gross]

The game theory on this is not good. When mutually shared destruction is available to every individual, the game theory is not good.

[Naval Ravikant]

My point of view is the problems are already out there. They're already as bad as you're saying that they're going to be like, the problems are already out there and AI is the way. And just technology progress in general is the solution to all those problems.

[Unidentified Guest]

Jerry can't even afford his open claw. That's reading his email right now. How is he going to pay for the nuclear bomb claw that.

[Gary Tan]

No, I'm good. I could pay for it. I just want everyone to pay for it.

[Unidentified Guest]

Exactly.

[Gary Tan]

I want everyone to be able to pay for it.

[Unidentified Guest]

It's like $100,000 a year, basically.

[Daniel Gross]

It's totally worth the time.

[Gary Tan]

If you hire a person, you can afford your open claw.

[Unidentified Guest]

People have gotten so I don't know if it's AI psychosis or what it is that at this point I usually just want anxiety.

[Farboud]

Yeah, I just want to be like,

[Naval Ravikant]

can I just talk to your AI, please?

[Unidentified Guest]

Like just, you know, where do I email your AI? I don't need to interact with you because people are like, you can't even text someone and get an answer from them anymore.

[Daniel Gross]

So many writing emails and writing documents with AI, like on X, I see all these posts that are clearly written by him. Like, why should I read it? I want my AI to read it.

[Farboud]

I think that's.

[Daniel Gross]

So if you write it, AI should read it.

[Farboud]

That's clearly a lower class signal. Like, it's like ridiculous. When I get emails that are clearly written in AI, I'm like, dude, that's the last.

[Gary Tan]

Well, you can write it better with AI because what you need is multi.

[Daniel Gross]

You write voice, don't you?

[Gary Tan]

I sure do.

[Farboud]

Actually.

[Gary Tan]

I don't know.

[Daniel Gross]

That's why I keep jumping to the defense. I, I hate AI writing. It's too verbose. It's too verbose, it's too clinical.

[Gary Tan]

But you can fix it like that. You know, we have super intelligence.

[Farboud]

Why wouldn't just write.

[Gary Tan]

What's that?

[Farboud]

The value of actually reading something and realizing it's written by a person is so much.

[Gary Tan]

Yes, fair enough.

[Farboud]

I feel like such a.

[Daniel Gross]

And by the way, if you're not reading something, you're not writing your own stuff. How are you going to talk? You're going to lose your ability to speak. Well, because good writing and good speaking are the output of good thinking.

[Farboud]

Yes.

[Daniel Gross]

And if you're not. If I just read that muscle. Yeah, I suppose you can do it.

[Gary Tan]

I mean, lots of tape. My counter argument would be, you know how, like, sometimes you actually really need like a person. I mean, I don't think this replaces people, but I can have now a high bandwidth conversation with a relatively smart AI model all of the time.

[Farboud]

No.

[Daniel Gross]

And you should do that. You should talk to the AI model all you want. But I'm saying like when you write something that's meant to be consumed by other humans, if that's written by an AI, that's a disservice to the other human. You're wasting their time. Everything the AI wrote should instead be compressed down by you. Or you should really, like take the time to make the point as succinctly as possible for the other person to respect their time. Otherwise their AI is going to end up reading your AI and neither of you are in the loop.

[Farboud]

You're not even in the loop. This is one reason I enjoy Twitter less. Lately is because so many replies.

[Gary Tan]

Virtue signal. Like I think in the future people will just have really, really impressive skill files that actually extract like the style and the diction and like, I mean the thing about the thing that people underestimate, that I've learned with some of this stuff is that you can just have more and more eval. You're saying you have an eval harness, right? Like you can have multiple levels, you can have cross modal evals. And when you have enough like sort of, I mean it's crosstalk. But if you do enough of it, like you can actually improve the skill file to a point where it's indistinguishable. And like this is without the next level of model. Like imagine Fable 7, Fable 8. Like you will not be able to tell, I guarantee. Yeah, no, it's less than 9 months. Like you like this whole AI writing conversation will fucking go away.

[Daniel Gross]

I think I'm still a little better defended. I'm higher up on that hill than you guys because I write very, very short. And AIs are very bad at summarizing, but also very bad at this.

[Farboud]

Good writing is novelty.

[Gary Tan]

Yeah.

[Farboud]

Like it's like surprise unexpected and anything that is guessing a next token from a regression can't do it.

[Unidentified Guest]

Yeah, it's not, it's not something.

[Farboud]

It won't do. Something original.

[Unidentified Guest]

If you like co write with an AI or use it as an editor to bounce ideas almost always it'll have like this one short. It's always like a short turn of phrase where you're like oh, that's good.

[Daniel Gross]

And it got that from somewhere else on the Internet. The Internet's a big place.

[Gary Tan]

Actually, I programmed a really crazy thing in gbrain. It's the retrieval thing I made. It's actually basically a collider of different vector spaces. And so I mean. And this is the kind what I mean by like boil the ocean, like these are things you can do now. Like it has my whole corpus of like everything I've ever said. All my emails, all my slacks, all my text messages, my DMs, everything. And then so I actually have like like 400,000 markdown files on like literally anything I've ever thought or read at this point. And then I have this thing called LSD mode, which is a lateral. Shit. What's the S. Lateral stochastic drift. I mean I just wanted to call it LSD mode.

[Daniel Gross]

Ok. Yeah, know I was trying to remember composition.

[Gary Tan]

Yeah, yeah. But basically it's, you know, take every possible vector space that is not pointed in the same direction and then cross them and then do a ranking, a re ranking across all of these ideas and you can actually more like it's called Brainstorm LSD mode and it just like finds bangers. And you know, sometimes I'm just. If I just am bored, sometimes I'll just be like, give me some LSD bangers. And it will literally give me like 10 or 20 ideas that like, you know, three or four different Frontier models have actually re ranked and said like actually if you look at this and we cross reference against like exa. Actually this is actually a really good idea. And I'm like, this is finding ideas at like a ridiculous amount of scale. So I mean I get it. But I'm also calling bullshit because I think that like this is just the classic. And I think this is actually a really fun thing that is useful. It's, you know, I think it's like a Paul Buchitism. Like the way to, you know, build the future is just like live in the future and work backwards.

[Daniel Gross]

Right, Right.

[Gary Tan]

And so like it is inevitable that like rather than fucking complain about AI, like it's helpful. Like it scores points. Like I see it on X. Like people love to like fucking score points on me. Okay, this is a problem. It's like I'm fucking inured to it. Like I don't give a fuck if someone comes to me and is like, fuck your AI writing. Because it's like, you know what? My AI writing to me is so fucking good, I don't even give a shit. No, I read it like I'm alive. I'm a human being still. Right. But anyway, that's how that's, you know, welcome to my TED talk.

[Daniel Gross]

No, I just agree like to predict the future, you just live in the future.

[Farboud]

Right?

[Daniel Gross]

Right. That's the best way to learn.

[Gary Tan]

And I want to.

[Daniel Gross]

Everyone should be AI maxing.

[Gary Tan]

Yes.

[Daniel Gross]

Just to figure it out. Otherwise you're going to have no sense of where it's going.

[Gary Tan]

I think like today's virtue signal is. I mean, I think that it's not helpful to people. Like there are people who are going to listen to this who want to be rich and they're going to be like, oh no, I shouldn't use AI to write. So I mean, I agree with you that human beings and what you really think matters a lot and you should write. And then for me that writing process is like actually workshopping in telegram with my open source.

[Daniel Gross]

I would say for me, I don't use AI to write well, that's not true. I used to write code, so maybe I am contradicting myself, but code is like, it's a utilitarian. It's like it's not meant for a code is meant to be consumed by another computer. It's not meant to be consumed by a human. And so if I want to create something that's meant to be consumed by a computer, I will use a computer. Yeah, but if it's meant to be consumed by a human, then I want to understand the thing. I want to, you know, ruminate, marinate within it. And then I want to respect the reader or listener's time.

[Gary Tan]

Yes.

[Daniel Gross]

And give them that insight nugget. Now the AI is used for brainstorming. That part. I like, I do use AIs to brainstorm. I use them like, give me synonyms for this, give me other ideas associated with this, pull in tangential information. I argue with it sometimes, especially because a lot of them are on guardrails, but I don't use it to actually create the output that I expect a human to sit there and read. That just seems to me like discontinuity. Right. It's kind of unfair.

[Gary Tan]

It's a quality thing. I mean, I agree with you, like out of box, the quality is bad. But you can have like 20, 28 level stuff. I mean, like, I think the pattern that I'm trying to like.

[Daniel Gross]

Yeah.

[Gary Tan]

You know, tell people is that like, yes, like AI writing out of the box sucks right now. Like if you rely on it out of the box, it sucks. But if you have an eval harness, if you've actually gone to like build a big enough corpus, if you actually like, you know, done crossmodal eval and like built, you know, a banger, Like I have a banger engine, you know,

[Farboud]

but I want to see some banger essays.

[Gary Tan]

Yes.

[Farboud]

Because I feel like. And even, even if they were like

[Gary Tan]

essays right now with a million views.

[Farboud]

Yeah. They wouldn't even be good enough. Because you are the president of Y Combinator. Right. I want to see someone who's just like out there posting, right. Using this system. I think they're rise up, make an anon account, disconnect it from yourself entirely, then come back and throw it in my face when you get to 300,000 followers.

[Gary Tan]

Okay.

[Farboud]

Because I'd be so. I'd be so curious if you could do that. That would prove it.

[Unidentified Guest]

You could.

[Daniel Gross]

Absolutely, you could, because there are 300000 people out there who will fall for it.

[Farboud]

But if you get that, then at least that's something, right? But it can't.

[Daniel Gross]

But if you pick up me or someone, you know, who's like smart and insightful and like, and wants like high quality content, knows what that looks like, you're not going to get those people.

[Unidentified Guest]

I've never been more creative and I think something happened probably just in the past few months, especially with Codex. I think I'm like, I'm way ahead of the curve on Codex. Like I can. I'm running my computer from home on my phone here in a way that you can't actually do without modifying Codex in some ways. And like the amount of creative productivity I have is way higher than it ever was. I think like six months ago, 12 months ago, the promise wasn't quite there. And so everyone was like, eh, this AI thing is not that useful. But I think it hit an inflection point in the past few months.

[Daniel Gross]

Yeah, I think clog code was a tipping point. In December 2025 was the tipping point and you had to reevaluate AI. AI has had a couple of tipping points. One was diffusion into images, you know, which kind of started it all. When you first saw like stability and you're just like, whoa, okay, made a dog face. You can make like cats and guys on the moon. Yeah, it was wild when it first came out. And then probably instruct GPT and ChatGPT and then there was another jump with the reasoning models like 01 and 03. But I think Claude code was a big unlock because it just unlocked a series of practical use cases. Whereas before it was like, okay, it's a better Google search. Or you know, it's like this saves me time like doing research or I can learn from this or I can even have a small conversation. But Claude code was a massive unlock.

[Gary Tan]

Well, the big thing here is like, this is the worst it'll ever be.

[Unidentified Guest]

Oh, of course.

[Daniel Gross]

Yeah, yeah. No, it's getting better.

[Gary Tan]

There are like so many crypto isms that basically super apply.

[Daniel Gross]

Yeah, yeah.

[Farboud]

You could have said that when Fable was released and you would have been wrong because they tapped away from us.

[Daniel Gross]

Yes, briefly, briefly.

[Unidentified Guest]

It'll be back use cases. You couldn't tell the difference between Fable and Minimax for almost any.

[Daniel Gross]

So that brings me to a good topic I do want to discuss, which is open source versus closed source.

[Gary Tan]

Right.

[Daniel Gross]

How good are the open source models really? Okay. I haven't tried Geole.

[Gary Tan]

Which ones are your favorite?

[Unidentified Guest]

5 times, 5 to 10 times less the cost.

[Gary Tan]

Yeah. Okay, what should we do?

[Daniel Gross]

Definitely cheaper.

[Gary Tan]

When should we lose them.

[Unidentified Guest]

Minimax is just mind bendingly good.

[Daniel Gross]

It needs a good harness though.

[Unidentified Guest]

Yeah, yeah, it does need a good harness, but if you got one, it works really well.

[Daniel Gross]

I was thinking today I'd love to see like take the latest and greatest open source model and they seem to have gone from a 12 month gap to a nine month at six month. And now some people are saying three months, I don't know if it's weeks, some people are saying three months. Whatever it is what it is, it's very jagged, right? In some domains they seem caught up, in some domains they don't. But I would love to see someone take the latest and greatest open source model, put it inside a very good harness, give it all the tools, make it available through a beautiful download desktop app and jailbreak it. Strip it of every time it pushes back at you for anything stupid, any tone policing, any. I don't want to research that. It'll just tell you the truth every time and just call it truth AI. That's all it does. I just want to see that. I just want to see what happens. Because the one place where the frontier, I'll always pay for more intelligence because I'd rather be right more often than wrong. Because I just think you're high leveraged and obviously I can afford it. But maybe if I was doing some highly repetitive tasks I wouldn't. But as a simple example, if you're doing something where the AI is right 90, you have one AI that's right. I saw this stat like 99.9% of the time and the other one's right 90% of the time. Well, if they're recursively looping and you run them 100 times, the one that was right 90% of the time is not going to be right 13% of the time, whereas the one that was 90% 99.9 will drop to 80 or 90. Right. So intelligence doesn't matter on the margin. Now those numbers are obviously chosen. 99.9 versus 90. It's not 99 versus 90. You notice that 100x more 100x lower error errors accumulate. Errors compound. That's the point. Errors compound. Anyway, going back I will pay for more intelligence. But and I'm not that cost sensitive on matters of judgment because you're always applying leverage and your time is also very valuable. But what I am curious about is the M.O. the Frontier models do annoy me by constantly trying to railroad me. You know, they're always like, well I shouldn't be telling you that. How About I give you this other answer.

[Gary Tan]

Okay. The really messed up thing.

[Daniel Gross]

How much of that are they doing?

[Gary Tan]

If you talk to it about, like, serious personal stuff. Yeah. And it also, like, always mess up UTC versus, like Pacific time. And it thinks it's like 7:00pm and it thinks it's like 5:00am I was like, hey, this is enough. It's time to go to sleep.

[Farboud]

That's why it does.

[Gary Tan]

And after a while I was like, what is going on with you? Like, it's literally 7pm and it's like, oh, sorry. Like anthropic. Arla. Like, Jeff is me. So, you know, if I'm. If you're talking about something serious and I think it's late, like.

[Daniel Gross]

Right. But I would love, like a completely jailbroken, best of breed open source model. That'd be great. Local is fine. Doesn't have to be in a nice package. It doesn't have to be local. Actually.

[Farboud]

What are you doing where the jailbreak is so important because, like, well, there

[Daniel Gross]

are a couple of things where it does stop you or catch you or try to crack you. You see that, right? There are a whole bunch where you don't see it, where it is successfully keeping you away from whatever you want to know.

[Gary Tan]

But you can always just switch to GLM 5.2 and it'll just do it.

[Daniel Gross]

Go ask it any question about race, gender, immigration, mental health, doctor advice, legal advice.

[Farboud]

I don't see why you need a harness for this. Right. Like, for me, I'm using harness because I'm using agents, because it's going out

[Daniel Gross]

and doing things to say harness. I just want the harness model. Interactions by harness, I just mean, like, I want it maxed out. I don't want any excuse for, like, why my open source model is even slightly worse than it could be. I want it operating. I want the best open source model configured in the best way. And it just tells me the truth all the time because I used to go to Grok for that. But even Grok is a little neutered.

[Farboud]

Yeah.

[Daniel Gross]

It's not like he once talked about this, is he?

[Farboud]

Yeah. People pointed out like, someone, he was like, oh, geez. And we wanted it to just be real and it was giving neoliberal answers.

[Gary Tan]

I'm dying to talk about what you said the other day, but I also don't know if you want to say it the entire, oh, where everything's probably hacked. It's priority hacked.

[Daniel Gross]

Oh, no, I'll talk about it.

[Gary Tan]

Okay.

[Daniel Gross]

So the question is, like, where are the open source models catching up, Right. And so there's a couple of different theories and I'll just lay out the theories that I know and the evidence for them. But I don't have a point of view yet.

[Gary Tan]

I mean, it's possible that these are true.

[Daniel Gross]

So there's some of it that's obviously, you know, the Chinese are doing their own pre training. They have their own compute, they have their own data sets. In fact, they can crawl more the data sets because they're less bound by copyright laws. So they can crawl YouTube and Reddit and all that stuff. And they train these models. That's like the base model, right? Then there's like the accusations that Anthropic made, which is that they're distilling our models, which is they're taking, they're querying our models en masse, taking that data,

[Gary Tan]

using, if I were China, that's what

[Daniel Gross]

I would do for sure. And thus creating a jagged intelligence kind of model. And definitely some of that is going on. But I think it's rich of Anthropic to call that out. When Anthropic crawl the open web and distill the open web, that's all these AIs are, right. In fact, in fact, one platform that I think would be very popular if the government were to do it is to say, hey, you guys, since you trained on the open web, if you trained on open web and open data, you have to open your model after x months, after 12 months or something. That seems to be like a pretty fair thing to say. Especially like open AI, you have to be. Otherwise you have to be actually open AI. Right? And Anthropic. You're the one talking doom and gloom and you're building God, but you're not going to keep God in a leash for yourself. Dario, we don't want like a priest, you know, controlling God for the rest of us, interpreting the Bible for the rest of time. So I think that would be a popular thing. Okay, so anyway, number one, they are, they are, they have their own pre training, but they get the full corpus of the web. They don't have to obey any copyright laws. Right. Second, they are distilling the existing American models which are starting to get more locked down. And a lot of this government nationalization control helps them be locked down. But you know, there are data brokers online that are taking like Claude Max accounts and reselling tokens from that in an API format to end users like 80% off. Because those plans are heavily subsidized for end users. They charge the Enterprises.

[Gary Tan]

It's like $8,000 a month retail.

[Daniel Gross]

Anyone who's run like an exchange or a regulated online brokerage knows that KYC is a dime a dozen. People get by KYC all the time. Like print passports in Vietnam, if you want. Right, yeah, exactly. So I think the distillation is going to be hard to stop, but I think the biggest one to think about. And there's some genuine algorithmic breakthroughs, like the Deep SEQ paper.

[Gary Tan]

Oh, yeah. Our ones that were incredible systems people.

[Daniel Gross]

Very, very smart people. And I would guess, just by looking at the numbers of resumes and so on, that the majority of mathematicians and researchers in AI today are Chinese. Like, they produce more STEM graduates, more PhDs in the relevant fields, more Olympiad winners than anybody else. Right. And then a lot of the US staff is Chinese. So, in fact, that's why I tweeted, like, AI is our Chinese against their Chinese. Right. And these guys. And I don't think there's any conspiracy required. These guys are all just friends. You know, they live in the same dorms, they went to the same schools, they live in the same buildings and apartments. They hang out.

[Farboud]

Yeah.

[Daniel Gross]

And they switch jobs like crazy. And not just the Chinese. You see, everyone's hopping from lab to lab to lab, and they're just taking data with them. Okay, so there's all of that going on. Right. But then on top of it, I don't think that the AI companies have the security profile of a top US national secure compartment facility. Right. They do not know how to protect secrets. So of course they're getting hacked. Of course the weights are getting leaked. And if you're Chinese or anybody else, you're not going to just take the buoys and release them back. You're going to use that to distill at high speed and train your own model or to augment your model. So I think there's another whole system right there that's going on. And the last one, actually, I think the biggest one is none of those. I think no conspiracy is required for the following. If you look at where China is, they're like, okay, we're behind. They've always been behind in software. The US has been way ahead in software. And being ahead in software allows you to extract all the margins. Because for the longest time, VCs never invested in hardware.

[Farboud]

Why?

[Daniel Gross]

Because hardware is a commodity business. And software had the network effects, the lock in software's art. As Patrick Collison said, it locks you in. And so people want to invest in software. So Even in the US whenever you get a hardware company funded, the VCs will always ask you, well, what's the software lock in? What's the software piece? Right? And so this is why like say, yeah, hardware is the moat that buys you time to build a software cast hassle, right? But guess what, Claude Code burned software down. Software was eating the world and AI eats software. So now software is commoditized. The moment you can Specify it, an AI can 1 shot it or 2 shot it or get to it within a couple of shots. Why?

[Gary Tan]

It went from like 5% to about 25% hardware. 20 to 25% hardware.

[Daniel Gross]

But hardware is also commoditized by China. Any hardware I can make here, you can make in China more cheaply and more easily. The whole ecosystem is there. Shenzhen has like 3,000 manufacturers. This tiny little cable all in one

[Gary Tan]

for normalizing relations with China and taking us off the dollar stand or the gold standard.

[Daniel Gross]

And so bringing reshoring manufacturing back the US is going to take a full generation. It should be done, no question. I'm a big fan of American manufacturing, but it's going to take a long time. In the meantime, China outproduces every one of the supply chains because they realize there are scale economies in production. So they subsidize the thing upfront, then they become the global supplier, they drive everybody else out of business, and then they control the whole supply chain across these critical industries. So they own hardware. No one's going to beat China on hardware in the next decade. It'll ramp up. We'll fight on a bunch of fronts, but. But they own hardware, so they like the commoditization of software. So when software is getting commoditized, that helps China. So if you're the Chinese government, you're basically funding all these labs. You're doing kind of a public private partnership where you're saying, don't worry, you don't have to make money. You can be number two or number three, just open it so the other labs can learn from you and we can catch up and keep up. And if the software is commoditized, then we win on the hardware. So the way I think about it today is that hardware is commoditized, but it's owned by China for the most part. There's some few exceptions like SpaceX. In the US software is commoditized. So what's not commoditized? It's actually just AI research developing, working on AI itself is the new software engineering. The problem with that is that software used to be democratized, everyone could compete. John Carmack and John Romero, sitting there with a small team, could code up Doom and Quake and compete against EA and Activision and so on. Can't do that. In AI, AI takes massive resources. Huge GPU clusters, small numbers of researchers, massive data sets, proprietary data sets, and then now regulatory capture. So it seems like all the value, all the choke points are going into AI, and that's controlled by a very small number of companies. And ironically, the only thing keeping us afloat is a Chinese government subsidizing the whole thing on open source so that their hardware can stay competitive.

[Unidentified Guest]

Yeah, I mean, I think the.

[Daniel Gross]

Plus, they have the weight.

[Gary Tan]

No kidding. Well, they might, they might. Let's use that as.

[Daniel Gross]

I mean, you could sneak it, but on one USB stick.

[Farboud]

Exactly.

[Daniel Gross]

It hasn't already been done.

[Gary Tan]

I don't need physical access. Like, you need one person on the inside. Like, there's so many people.

[Daniel Gross]

By the way, every male AI founder is walking around with a beautiful Chinese girlfriend. Have we talked about that? Like, no one talks about that. Go walk outside Silicon Valley. Right.

[Unidentified Guest]

I think we all come from a world where advantages, like, had some durability and you could actually operationalize your advantage against the rest of the world, but that's just like narrowing down in time. So you might have the smartest model, but what are you going to do with it in two weeks, in three, four weeks, until somebody else has it too? I think there's a different part of the game theory that we've not experienced before, which is the time contraction of any of these advantages. And I don't think it makes it harder to predict who's going to be in charge of anything, because like you said, a few months later, the smartest model is now open source.

[Daniel Gross]

Guys, I'm so fucking worried. This is one of my tweets I'm prouder of a couple of years back, I said, soon everybody will have AI anxiety. Like, we're all feeling it. We're all feeling AI anxious.

[Gary Tan]

Right. It's incredibly jubilant. I am AI jubilant.

[Farboud]

But it's both.

[Daniel Gross]

Right. The anxiety in its good form is kind of FOMO ish, which is like,

[Gary Tan]

look at all the great. Don't worry about me, guys.

[Unidentified Guest]

Yeah.

[Farboud]

But like, everyone I know that's working at Frontier Labs on these things that are researchers, they're like. Like the press.

[Gary Tan]

They are.

[Farboud]

Why? Yeah, they're stressed out because they think it's going to kill us all.

[Unidentified Guest]

That's because they're.

[Gary Tan]

Why would it kill us the first

[Daniel Gross]

ones I met in 2021 were saying to me that they were putting off having kids or thinking about not having kids because they were afraid for the kids future. And I was like, what are you talking about?

[Unidentified Guest]

As opposed to every other time in human history when people were not, were never afraid of their kids future. And so they didn't have any kids.

[Gary Tan]

Wait, so why is this not just going to result in Star Trek the Next Generation? Like that's, that's my hope.

[Daniel Gross]

So the bullshit part of the.

[Gary Tan]

Would be great.

[Daniel Gross]

The bullshit part about Star Trek the Next Generation is that they have AGI, clearly. Yes, but that AGI is somehow not running things.

[Gary Tan]

I mean, they couldn't conceive of it yet.

[Daniel Gross]

Right. They have the holodeck, but somehow people

[Unidentified Guest]

are still going about it's not that good enough.

[Daniel Gross]

A writer, not just living in the holodeck.

[Unidentified Guest]

There's plenty of science fiction that's, you know, bothered to see that idea further through.

[Daniel Gross]

I mean, some large percentage of the San Francisco population has been one shot of by fentanyl. You don't think the holodeck will take out the rest, right?

[Gary Tan]

They just don't show that on the show. Like Gene Roddenberry, I'm sure he conceived of it. It would just be too much of a bummer to show these giant holodeck. I mean, you say this and wireheading.

[Farboud]

You're living in Star Trek in your mind and you're happy.

[Daniel Gross]

Yeah, that's true.

[Farboud]

You're like excited for it and it's like. But yes, you recognize there's a ton of terrible things that are gonna happen, right? And you're just like, huh, it wasn't in Star Trek.

[Daniel Gross]

Well,

[Gary Tan]

you're blowing my dreams over here, Daniel.

[Daniel Gross]

But to Gary's defense, like, there's. There's been so much electricity. Like that was a big one, right? Railroads, the cars. These were big, big changes.

[Gary Tan]

You used to have to ride a horse across like the Pony Express. Do you remember that?

[Daniel Gross]

That was insane. People made it. But the more. Yeah, but the more rapid. Yeah, the more rapid the change, the more influential the displace, the more tumultuous it was. And so now we're having a very rapid change. We're displacing white collar, we're displacing. We're displacing government, we're displacing managers, we're displacing academics, we're displacing journalists. You know, I learn more from AI than I did in my college classes because I can Sit there and I can have it meet me at my exact level of knowledge, because they give that to me visually. Give me a graph about that. I can ask dumb questions. I don't understand that. Explain it again. Explain it again. Explain it a third different way. Explain it visually. Explain it audibly. Explain it with dancing elves. I don't care. Just to keep going over until I get it. I could not do that in class. I can learn so much better. I just have to care. If I care, I can learn anything. Better than with any tutor. Better than with any teacher. So all these people are obsolete and they're going to lead a revolution?

[Gary Tan]

Well, no, those people need to want more things. And if you want more things, well,

[Daniel Gross]

we want unlimited, which is great.

[Gary Tan]

That's the good news.

[Daniel Gross]

The good news is everyone wants more things are unlimited.

[Gary Tan]

And then if you have this tool and you're not averse to using it, this is why I'm so against, like, sorry to bring up the AI writing thing again, but, like, I understand. Like, that makes sense. Humans and like, there is a disrespectful aspect when you do bad writing. Right. But, like, that presupposes that, like, the AI can't write.

[Daniel Gross]

Well, that's a fair point, because right now the writing is voluminous. It's a giant, giant. Like, it takes a little thing like prompt, you give it. Well, okay, but here's the thing.

[Gary Tan]

Yeah.

[Daniel Gross]

You're giving it a prompt, right?

[Gary Tan]

Yes.

[Daniel Gross]

Why don't you just send me the prompt? Why do I need to read all the garbage?

[Gary Tan]

Because it has to draw on, like, all of human experience.

[Daniel Gross]

No, no, give me the prompt. Just send me the prompt.

[Gary Tan]

I mean, that might happen.

[Daniel Gross]

I'll send it to my AI. That's how it happens.

[Unidentified Guest]

I have my codex put. Put together a markdown file that I send to my developers that they can give to their Claude code.

[Farboud]

Yeah.

[Unidentified Guest]

To go execute things that I want

[Gary Tan]

to go do it.

[Daniel Gross]

Don't talk to me. Have your agent talk to my agent.

[Unidentified Guest]

That's literally what it is.

[Gary Tan]

My thing will just file an issue on your GitHub repo, and then.

[Daniel Gross]

Yeah, what I want to do is I want to get on the zoom, and I'm on the zoom, having the conversation. And then 10 minutes in, I know this is not for me.

[Naval Ravikant]

Yeah.

[Daniel Gross]

And then I just hit a button and the agent takes over. Agent Naval keeps talking and I go off to the next one. Yeah, I swipe right on you. But for. But then the joke's on me because you were never there to Begin with,

[Naval Ravikant]

I think it's time for politics.

[Unidentified Guest]

Politics. Politics sounded like it's been politics most of, most of the time. Fear mongering.

[Farboud]

Politics doesn't matter because of AI.

[Unidentified Guest]

You know that's not true.

[Daniel Gross]

What are you talking about?

[Farboud]

Everything's going to end. Nothing that's like politically relevant right now is going to be relevant in three years. I will say that I was going to get.

[Unidentified Guest]

I wish I could vote for an AI, their job. I wish I could vote for an AI to represent us. But who is it?

[Farboud]

Gary will make it.

[Unidentified Guest]

Somebody can make it.

[Daniel Gross]

They can open source it.

[Unidentified Guest]

They can put the weights out for

[Daniel Gross]

us to take a look at the weights. You can look at the weights. I mean not personally, that way it

[Unidentified Guest]

looks optimization like a fully transparent AI that is running for this thing.

[Daniel Gross]

They had this thing, a whole field called mechanism interpretability. But to try to figure out how the AI thinks and they've like made very little progress.

[Unidentified Guest]

Oh sure, I'm not saying we're going to know, but I'm just saying you have access to the same AIs are

[Daniel Gross]

not legible by the way. It's an anachronism. Our training data is in natural language and in computer languages that humans can read and write. And so the AIs are trained on that. But in the future the AIs will develop their own languages. They'll communicate with each other in some kind of a binary high speed protocol. They'll almost be talking compiled code or maybe even something completely different that we can't even imagine which will be more efficient for communication. It's only humans who demand the legibility, but the AIs don't really have it. And part of what makes AI systems so much better than human coded expert systems is that they don't have to be legible. So they can find correlations and patterns that we cannot articulate. In fact, even most of our knowledge is inarticulatable. Most of your feelings are inarticulatable. You don't even know half the time what you're feeling or thinking.

[Unidentified Guest]

You're not even the other half of your hallucinates. Talk about our feelings.

[Daniel Gross]

Yeah, yeah, let's do that. We're experts in that one place where we are experts.

[Unidentified Guest]

GLM 5.2. I'll vote for GLM 5.2 for office.

[Daniel Gross]

Yeah, they're Chinese overlords.

[Unidentified Guest]

Hey, it's my favorite distillation of fable.

[Daniel Gross]

I really do appreciate how the Chinese are making all the open source models out there. It's kind of pathetic that the Us just the global economy will appreciate it. Cdance is probably the global leader in video, right? So it's the best video. So in some places actually that's. So that's an interesting point about open source in some cases now, open source is number one and at least historically, like if you look at things like Linux or other open source projects, once something open source kind of gets in the lead, it rarely surrenders it. And that's because an ecosystem springs up around it where everyone starts plugging into, especially in enterprise use cases. So right now Claude and Codex are like slightly ahead of GLM fable and maybe a lot ahead of glm, but if something like a GLM were ever to surpass them, it's not clear they'd get a lead back.

[Unidentified Guest]

I mean, because how can you rationalize your limited resources at a company going into something that open source is winning at? You have to do something with your resources. And failing to catch up to open source with your precious resources is not a good use of them.

[Daniel Gross]

You'd have a clock like so if you're open AI anthropic, you would have a certain amount of revenue and money and cash in the bank and investors backing and you would have to use that to sort of jump meaningfully ahead of the open source and take the lead again before that runs out. So that's an interesting. Because if you look at the AI race 2 years ago people thought that Google and Elon and Meta were also competitors.

[Gary Tan]

Yeah, there were five kings.

[Daniel Gross]

There were five kings, there's two kings, now there's two kings. And why is that? Well, it's not just because those guys have the best models. OpenAI and Anthropic are the only ones that are a making revenue off of their models directly. And so they're not subsidizing, cross subsidizing from other business. They're not running out of cash, they're actually pouring the cash back in. And the second is because they have very active user bases and now a lot of the improvement is coming through reinforcement learning. They're getting the guidance and the trajectories to improve the models and so they're just pulling away. And maybe Elon, because he took SpaceX public and he's got that war chest, he gets maybe one more bite at the apple, plus he's got the data centers in space. So you know, don't bet against Elon Musk. Google I think has lost it.

[Gary Tan]

That's quite sad.

[Farboud]

It's really amazing what happened.

[Daniel Gross]

I was always like bearish on Google I was tweeting some pretty anti Google management stuff back in the day where I was like, we'll know they're serious about AI.

[Gary Tan]

Gemini 3.1 Pro was like the moment that was. That's the business was.

[Daniel Gross]

No, but it wasn't.

[Farboud]

But it wasn't like 2.5 Pro was better.

[Daniel Gross]

It wasn't good enough. They never even got the basic app working. I remember I tried to upgrade to pay them $20 a month. It was a nightmare. This huge run around.

[Farboud]

It's crazy.

[Daniel Gross]

No, no, you need to be part of Google one. No, no, you need Google Workspace account.

[Gary Tan]

They were contact usable context.

[Daniel Gross]

Yeah, very quick. And then every time, Even today, the iOS app, which I know it's not their platform, but everyone else seems to figure it out. You put a query into, into Gemini, you background, it always loses the connection, it just drops it. Whereas all the others will just run in the background. How hard is that? It's 2026. Run a background app, guys.

[Gary Tan]

GRPC just need a little bit more Sparta over there. Meta might be too much.

[Daniel Gross]

I think it's too late for.

[Farboud]

I think they have to kill 5,000 Google PMs. Like that's the only way. It's PM slop. The whole company's PM slop at this point, right? Like anywhere you go, it's just like tons of products overlapping. It's a huge mess. You can't figure your way through the maze.

[Daniel Gross]

Some incentive problem. Now, all the best people want stock in Open Iron Anthropic or they want to be sitting alongside the best colleagues in Open Air Anthropic or they want the data set from Open Air Anthropic. And they certainly don't want to be tied down by all the PMs and all the legacy BS. And they should have replaced Google search Google AI a long time ago. I don't even look at the results anymore. I just look at Google AI.

[Gary Tan]

So here's the alternative vision, which is like Google today could, I mean they probably have all the transcripts of all the meetings or if they don't, they

[Daniel Gross]

should have it and they have all your emails, right?

[Gary Tan]

And then they probably need to use anthropic fable 5 or whatever because like their own models are not quite good enough. But you could diarize all of these. You could have like, you know, a markdown file for every single employee at Google and you could compute a score

[Daniel Gross]

which you've cleverly trademarked and patented.

[Gary Tan]

That's right.

[Farboud]

Google running through Gstack, of course.

[Unidentified Guest]

Anyway, Google Omni is the best for Google.

[Daniel Gross]

Gary has a price. It's 7%.

[Unidentified Guest]

It's standard. It's just standard.

[Gary Tan]

Yeah, I mean, you could solve this like if someone was a true, like really wanted to fix this. Like, all of these things are just systems problems, right? Yeah, you can have a system, but

[Daniel Gross]

it would take Larry and Sergey walking in there and literally it's like that scene from Entourage when Ari Gold walks back in the office. They're shooting people, like, but only with

[Gary Tan]

their open claws and live ammunition. I'm serious, like, you don't. They don't need to be there physically. Like, you know, one of the things I learned from Pedro at Brex, like, that's how he runs Brex. Like, you know, he has total information awareness on like every team. And one of the things, like the thing that got me.

[Daniel Gross]

Didn't they lose the ramp?

[Gary Tan]

I mean, I was gonna say. I'm kidding.

[Daniel Gross]

I'm kidding.

[Farboud]

The ramp guys come in credit to bouncing.

[Gary Tan]

I don't have any skin in the game on either of those.

[Farboud]

Okay.

[Unidentified Guest]

We're accepting sponsorships from whoever calls in first.

[Gary Tan]

Whoever pays us more, we'll talk capital One or. Anyway, I mean, no, like, I mean, he really did like instrument the CEO brain like for him. Like it's his personal claw that knows like the KPIs and literally what all of his directs talk about in those meetings. And it's significant.

[Daniel Gross]

So he's spying on them all the time?

[Gary Tan]

I mean.

[Unidentified Guest]

Yes.

[Gary Tan]

No, I mean the thing is like, like, I mean, they're not the only company. Like I've Talked to other CEOs, they don't publicly talk about this behind closed door. Yeah, this is like the max thing that you could do is like, like concentrate the power in your CEO or co founding team so you have actual awareness of what the fuck is going on.

[Daniel Gross]

Well, the reality is the team should be much smaller. Right? Most of Your employees or GPUs working the data center.

[Farboud]

I mean, I mean, of course, if you can have 10 fewer. 10, like a 10th of your employees right now and just make them the 100x guys, then that's so easier said than done.

[Gary Tan]

Like most people. Most CEOs do not want to fire 50.

[Daniel Gross]

No, no. But there should be a lot more.

[Gary Tan]

I've been on boards where it's like, bro, like we're. And we need to fire 80 of the people and you have a shot. Like, but you don't know which. 80 tens of millions of dollars part of the problem.

[Daniel Gross]

You don't know which 80% you're working through.

[Gary Tan]

What I'm saying is now you get the visibility and that's not. That's not a little thing thing. That's a big fucking thing. Like, you can have total information. Like, okay, like, this is a big thing to me, right? I think that the future is essentially that, like, you need to ride the fucking AGI. Like, you. You actually need to. Like, the most significant thing to me is like, the 1 million token context window is a big deal. It's like, I mean, I talk about it as like three Harry Potter books, but guess what? Like, a human being can keep in their brain fucking seven things, plus or minus three. Like, we are little monkey brains. Like, we talk about, like, super intelligence is like, in the future. Fuck that. Super intelligence right now. Like an agent working for you can literally make like a thousand pages. Like, printed, valuable, useful, credible.

[Unidentified Guest]

Let's not talk about AI writing again.

[Gary Tan]

No, no, I'm not. It's not a writing thing. No, it's an idea. It's like a. You understand what the fuck is happening in your org? Like every CEO in the world. Like, really.

[Daniel Gross]

So. So you can have your AI, say, tie into all the systems in the entire company, evaluate everything and tell me which 20% to fire right now.

[Gary Tan]

I mean, you could do that and you should.

[Unidentified Guest]

That's likely the easiest thing in the

[Gary Tan]

world, but no one will do it. No one's doing it.

[Farboud]

We haven't talked about the project at Meta Plus.

[Daniel Gross]

It's not perfect.

[Farboud]

Do you know anything about that?

[Gary Tan]

Only what I read is like, I mean, half of the smart people I knew at Meta have left. Yeah, Yeah, I mean, I'm sorry. Like, I really like Meta, you know, like, you guys are great, but like, it's also like, what the fuck?

[Farboud]

I think it's become a sweatshop for a little bit.

[Daniel Gross]

I don't think you can build a culture or morale by just buying people especially all different from all different stripes and places and ramming them together. Then you'd have no idea how many are actually missionaries, how much are mercenaries. Culture is a real thing that takes time to evolve and grow.

[Gary Tan]

Meta, of all places, needs to do what I just described, which is like, should. Someone has to actually know what is actually happening per person, per team. And it's. I mean, you can do this now, right? But you also have to tune it. Like, there has to be a rating. It's like, what is actually a good employee? What is their behavior? What are their characteristics? Like, you can actually tune your culture, right?

[Farboud]

I mean, it's Taking the whole engineering team and turning them into data labelers. It's just like. It's like dropping a nuclear bomb in the place.

[Gary Tan]

That seems indiscriminate to me. Right. Like why would you do that? Especially because you have this incredibly fine grained thing. Like you have a prompt, you have a skill file, you have like a bunch of markdown. Like you can actually tune it to exactly the output.

[Daniel Gross]

I think their. Org is just too large. Yes, it's the same problem as Google. When you have a large org, you do things that actually make sense in certain domains. Then it gets leaked to the press, gets sensationalized. Oh, they're turning everyone to data labor. It's probably. You just have too many people, you have too many cooks in the kitchen.

[Gary Tan]

But you need a still like way less than what you can fit in three Harry Potter books. Yeah, right. Like so, I mean, and I'm sorry to like bring that, but like I

[Farboud]

think that most millennial example you could give.

[Gary Tan]

Sorry, I don't know.

[Farboud]

Read another book.

[Gary Tan]

Yes.

[Daniel Gross]

Well, I think the big scary question is, will there still be a startup ecosystem? Because on the one hand you're shrinking the size of the firm. People are more leveraged. That should mean more startups. Small teams can do more. Great. Fantastic.

[Gary Tan]

We're definitely seeing that. I mean people can get to 100mil ARR. Like not raise a million, but doing what?

[Daniel Gross]

Selling software. And software is getting completely commoditized. Like all these legal guys like Harvey and whatever. Like, like it's a good test. Like wouldn't Claude just basic mythos or fable just do a better job than somebody trained specifically on legal, especially with tool use.

[Gary Tan]

It depends. Because it depends on whether or not the Frontier labs stay open for their best models or do they close them.

[Daniel Gross]

I think anyone who pays them enough, they'll find a way to be open. So if a law firm will pay them the best result.

[Gary Tan]

That's not a given. It is possible for anthropic to say like actually Fable 6.

[Daniel Gross]

I wouldn't bet my business they're not going to enter my vertical. I think if they can enter your vertical without. Without a custom model, they'll do it. And I think one of the less one of the bitter lessons here is that the general models beat the specialized ones. Yes.

[Unidentified Guest]

They don't have to enter it. It's just gonna people automatically.

[Daniel Gross]

Yeah, exactly.

[Unidentified Guest]

To create that market. Not because the OpenAI legal act.

[Farboud]

Right, right.

[Unidentified Guest]

It's just because it's so much just

[Farboud]

like why would I use something I

[Unidentified Guest]

would pay $5,000 a month for some other SaaS companies.

[Gary Tan]

I think that like 2027 will be the year of the AI harness war is like, is it going to be Codex? Is going to be cowork slash Claude code? Is it going to be openclaw, Hermes? Is it going to like, what is it, you know, who's like, what harness are people going to use day to day for everything?

[Daniel Gross]

Yeah, right now. So a lot of Silicon Valley after 2007 got to exist because you had two mobile phone providers. You had, you had Apple and you had Google. If you had only one, if Android didn't exist in an ecosystem, it would have been a much tougher position for startups. You would have been facing a kind of a true monopolist. At the end of that chain or the top of that chain. Right now you at least have two horses fighting each other. Right. So they kind of force each other to behave a little bit. If it boils down to just one, it's a very bad situation for startups.

[Gary Tan]

Well, then they'd nationalize it and then, you know, maybe we could get the government to.

[Daniel Gross]

Do they really nationalize it? They didn't nationalize Google, they didn't nationalize. You know, Apple's way bigger than that.

[Gary Tan]

It depends on how bad it gets. I mean, like search, it's a good utility. Like, there are lots of reasons.

[Daniel Gross]

And if you nationalize it, it might slow down and lose because now the DMV is running it and China wins. It's not like the Chinese are asleep. There's an ASML machine supposedly somewhere in China. Now, did you hear about that? Howard Litnick called ASML and was all mad because an ASML machine somehow leaked into China. That's the lithography machine. There's only 184 of them.

[Farboud]

That's our silkworm's escaping.

[Daniel Gross]

Yeah. And then on top of it, they're developing their Huawei chips, they're working on their 7 nanometer, 5 nanometer, whatever processes they're building, their fabs, they're working on it. They're not dumb. I mean, you've got 1.4 billion people there. You've got a lot of stem PhDs, they have a lot of national pride. They can redirect capital. I'm not saying it matches up to innovation in a free market economy, but the US is ahead because we have created this very thin layer where we take the absolute best and brightest from all over the world and we incent them like crazy to compete with each other. And then we collect the rewards from that. And Silicon Valley actually disproportionately collects the rewards and California collects the rewards and, and it's not really spread out to the rest of the country as much. The rest of the country is scared shitless now. But that's it. That's the thin blue line standing between the so called free world and the Chinese competition. Now I'll actually take a radical point of view. I don't think we're in competition with China. I don't see the competition Taiwan. I mean every Taiwanese person I talk to doesn't want to fight. The rich people in Taiwan are busy dodging the draft by taking their kids out of the country. There's some rule in Taiwan that mandatory service, mandatory conscription, but if your kid has spent, I don't know the numbers, but something like three months a year for the last five years out of the country, then they're not eligible for the draft anymore or no more mandatory conscription. So every rich person is always taking their kids for three months a year out of the. They have like a standard system doing it. They're not interested in fighting. The second largest political party there, the Kuomintang, is very pro China. So it's already very compromised. They are, most people in Taiwan are thinking they're going to go like Hong Kong, they're going to get rich in the process. They're going to Gateway to China and then one or two generations later they'll assimilate. And how the heck is the US going to defend Taiwan? Like aircraft carriers are dead. Land based missiles from China can take out aircraft carriers, drones. DJI is the largest defense contractor in the world. It's like us trying to like, it's like China trying to defend the Florida Keys from us. You know, it's ridiculous. The whole concept is ridiculous. So, and you saw we just went through with Iran. How do you think we'd figure we'd run out of missiles in like seven days? We don't have the manufacturing base now maybe Anduril and Saronic and others get there and build all of that up, but that's a long ways off. So I mean, I think the Chinese know that and I think the Taiwanese know that and I think everyone's trying to save face While like over 10, 20 years Taiwan slowly reunites with China. And outside of that we don't really have a beef with China. You know, okay, Japan, whatever. You know, North Korea's got a South Korea issue, but it's not in our backyard. One of the big problems, the US is facing is that we've been in a low growth, high inflation environment for a while now. Maybe growth growth is picking back up, but so is inflation and people are fighting over the spoils. There will be democratic socialists coming up. The billionaires tax the wealth tax, the socialists trying to seize the means of production. Mamdani doing rings around the democratic establishment and they're talking about the eradication of western civilization. People, you got to put food on the table, you got to make people feel good. You got to make people feel like they're not going to go jobless. You got to feed them. And picking a war with China just seems like the stupidest thing to do now. We should have the appropriate tariffs against them. If they have tariffs against us, if they subsidize their businesses, especially network effect or scale economies to compete with us, then we should also have our own barriers because you gotta protect your local industry so it doesn't get snuffed out so you at least have a fighting chance. Because these things do have economies of scale. It's not as simple as David Ricardo said where it's just like, oh yeah, I'm selling bananas and you're selling watermelons and we can just trade. No, because the guy who gets better at doing something, gets really good at doing it and then can do it very, very cheaply. Or he gets a network effect around either an ecosystem or an actual lock in where new users create value for existing users. So you can't have that simplistic of a mindset. You do have to play on an even playing field. You have to make sure the currencies are aligned, no one's subsidizing, et cetera, et cetera. But that said, there's no reason for us to go to war with China. There really isn't.

[Farboud]

But is Taiwan like it or is it like controlled the South China Sea?

[Daniel Gross]

It's like why, why, why do we need to control the South China Sea?

[Farboud]

So like, okay, so the world breaks in half.

[Daniel Gross]

The world's already broken into many pieces.

[Farboud]

I know, but like right now our ships go through there and it's fine, right? But like the world literally, why would

[Daniel Gross]

our ships from going through there if they're carrying, you know, trade goods back and forth, like who knows?

[Farboud]

We have a rule that's like, you know, the rule of the sea is that we can free, freely pass wherever we want.

[Daniel Gross]

There is no need. We have a civil war going on internally in this country. In case you haven't noticed. It's nationalist versus Communists. Like everyone is going more radical in both sides.

[Farboud]

I mean, it might be fine if the world breaks in half and China controls Asia. Right. And it's like China

[Daniel Gross]

does control, China does control most of East Asia. And to the extent that it does not, it is up to Japan and South Korea and others to look out for their interests. And they can ally with the US but we're not going to get into a shooting war with China over interests in the South Pacific Sea.

[Farboud]

We would never do that. But we will sail a ship through there and they'll hit it.

[Daniel Gross]

Why would they hit our ship going through there? If they run a ship through the

[Farboud]

Panama Canal, getting our ships hit.

[Daniel Gross]

No, no, but if they, if they put a ship through the Panama Canal, why would we attack it? If it's a legal trade vessel carrying goods and services back and forth in the US that we're trading on incentivized

[Unidentified Guest]

to do any of that to each other.

[Daniel Gross]

Yeah, yeah.

[Farboud]

I think right now China actually cares way less about this stuff than we think. China's very internally focused. Like the CCP is very internally focused.

[Daniel Gross]

Exactly.

[Naval Ravikant]

Yeah.

[Daniel Gross]

They, they, they want to stay in charge of their empire. And you know, I'm not a fan of communists or the Communist party, although I think CCP resembles more of a capitalist fascist organization. The communist is a veneer. Right. Fascist in the sense of like it's, it's like the nation uniting for a common cause. They are run by a party.

[Unidentified Guest]

They're very good at making money.

[Daniel Gross]

Yeah, exactly.

[Gary Tan]

Not only that, they are actually pretty hyper competent, which actually they're very competent. If you compare it to like the California government, it's disastrous.

[Daniel Gross]

High IQ and homogenous. Right.

[Farboud]

I mean, yeah.

[Gary Tan]

I mean when you look at high speed rails like guys just change the sequence. It's time to build.

[Daniel Gross]

It's time to build. No one's building. There's a few of us building in Silicon Valley, but we're even building ethereal things that are communist instead of.

[Gary Tan]

Yeah, yeah, that's, we'll just send ours over there. But they're like, no, no, no, we don't want these guys. Like, yeah, like not so good.

[Daniel Gross]

They call them baizu. Like.

[Farboud]

Yeah.

[Daniel Gross]

What does that mean again?

[Gary Tan]

It means white and left.

[Daniel Gross]

White and left?

[Farboud]

Yeah.

[Daniel Gross]

And it's kind of derogatory look down term. Yeah, they're effeminate or stupid or something like that.

[Gary Tan]

I mean, all of the above. Yeah. I mean that's how I think of them.

[Daniel Gross]

Yeah, exactly. Centrist Democrat. Everybody

[Farboud]

in San Francisco, baby, I feel,

[Daniel Gross]

I feel like you're wearing it. You're like, please don't eat me, sir.

[Gary Tan]

No, I mean, look at San Francisco. Like, it's, you know, San Francisco is on the rebound. We're going to run the table on the supervisor seats at least, you know, like.

[Daniel Gross]

Yeah, but the problem is that LA is sinking. Yes, LA has sank. Hollywood. Hollywood got chased out of la.

[Gary Tan]

It's insane.

[Farboud]

This is not a problem. This is an opportunity. All my friends in New York are going to come back to San Francisco.

[Daniel Gross]

This is the problem. California has a monopoly in all the warm, dry coastline, all the Mediterranean land in the United States, which is the most powerful empire in the world. So it's the most powerful. It's the best land in the world, all in one state. There should be five or six different states.

[Gary Tan]

30 to 50% of the GDP of the United States will concentrate in also.

[Daniel Gross]

But also the arable land, the beautiful coastline, the good weather, it's. It's a. It's a curse of geography. They've got all the natural resources, right? It's like basically southern Italy or France or even better, but in the US and it's all in one freaking state. California is this weird direct democracy.

[Gary Tan]

I mean, the government is the worst idea. Not that bad.

[Daniel Gross]

50.1% can vote anything. And they just read a headline, they're like, yeah, yeah, free, free, Free cats. Free food for cats and dogs for everyone. Great, we'll vote for it. Keep the rich Stiers.

[Gary Tan]

Stier couldn't get in there, right?

[Farboud]

Yeah.

[Gary Tan]

You know, know, basically, like, we actually have two relatively centrist options for governor, which is good.

[Farboud]

Amazing.

[Gary Tan]

Which is amazing. That's great. Like, I like that.

[Daniel Gross]

Right?

[Unidentified Guest]

So I think all these communist experiments will fail everywhere. Like, they failed in San Francisco. They're going to fail in New York.

[Daniel Gross]

I don't, I don't agree.

[Farboud]

No, I don't think they'll fail.

[Daniel Gross]

Like, stop. The difference with San Francisco is demographics are destiny. And the demographics of New York and demographics of LA and the demographics of Chicago are just firmly committed to that cause. And the worse it gets, the more they'll vote for it. It's like Venezuela. They're going to vote all the way down and there is no one out there to fly in and arrest the next Maduro. It has to be solved internally. United States is the last bastion for freedom. Even the COVID unlocks. The lockdowns would not have lifted if you didn't have militiamen start marching around the red states and purple states carrying M16s and AR15s past the state Houses being like, we're done with the lockdowns. Then the lockdowns came up. The whole world would have been locked downs.

[Farboud]

The whole world works, baby. Yeah.

[Daniel Gross]

The whole world would be in lockdowns for 6 to 12 months longer if it weren't for the 40 million intransigent Americans who have guns. And they, whether and everybody likes to hate on them and everybody likes to shit on them. But they are freedom free. Yeah, freedom ain't free. You need those people out there, right? And so look, when, when, when the US if the US were to collapse, first of all, I think freedom bleeds out from the rest of the world. You can already see what's happening in Australia and UK with the speech laws and the censorship and all that and the weird arrests and so on. But if the US degenerates and falls, it doesn't fail like Europe did. Or even Europe isn't feeling that well these days either. But it doesn't become like a big retirement home in a museum where everyone's on good social welfare for a while. It fails like a Latin American country fails because it is bordered by Latin America. So you got a lot of people who want to get in here and they will get in here. So you're looking at much more like cartel and drugs and crime and violence and those kinds of institutions.

[Gary Tan]

Okay. White pill robotics.

[Daniel Gross]

No, you're right. Technology.

[Gary Tan]

I don't want to do ubi. We should do ubi. Ubr.

[Daniel Gross]

UBR is good.

[Gary Tan]

We need to have universal basic robot. Everyone should have a robot and the robot should cook for you. Pick up your.

[Daniel Gross]

The good and the bad news is that the, the robotics, the, the robotics boosters say it's two, three years away. The robotics skeptics say it's five to 10 years away. And no one thinks it's impossible.

[Gary Tan]

Yeah.

[Daniel Gross]

And so we already have self driving robots, self driving cars.

[Gary Tan]

I think we can make people really happy if they have a better life. Like they aren't, you know, I mean, who likes to clean their toilet bowl? Nobody. Right.

[Daniel Gross]

Unless a lot of the issues around

[Farboud]

you of this if you vote for centrist Democrats.

[Naval Ravikant]

Yes.

[Daniel Gross]

Well, a lot of the immigration and a lot of the taxation issues are happening because the boomers are retiring. There aren't enough people below them to take care of them. They're voting themselves lots of benefits. There's not enough money left in Social Security. The population is shrinking. So a smaller number of workers are carrying a larger number of these guys. So they're saying, okay, we'll just sell the country and retire.

[Gary Tan]

This is the path we need. Centrifuge Democrats who are pro technology, who are abundance oriented.

[Daniel Gross]

Okay, but, but, but to play Devil's App for a second, like health care, 90% of healthcare is wasted. It's not robots. It's not even stuff people need. No, no, but it's like, like how much of health care goes into like keeping you alive for the last two weeks.

[Gary Tan]

Right, right.

[Daniel Gross]

That's not really.

[Gary Tan]

I can fix this with markdown files.

[Daniel Gross]

Okay, okay, but. And then education is just like a big larp. Anyone who wants to mark can go educate themselves right now with AI. Educate themselves right now with all the open, open source courseware and all that stuff. They just want the stamp and they want to go to college and they want to hang out in idyllic paradise for four years and they want to protest for social justice and they just want to chill with their friends and party and get paid for it.

[Gary Tan]

Yeah, it's already ubi. You said a very important college is already ubi. The college is not about the actual act of learning. It's about being in a room with a certain set of people who like have the right networks.

[Daniel Gross]

Correct. It's socializing, it's babysitting, it's credentialism. There's just a tiny bit of education sprinkled in for a few STEM degrees.

[Gary Tan]

And then you go after a bunch of bullshit jobs.

[Daniel Gross]

Legitimize it. Yeah, and then there's. Yeah, all the social sciences and politics.

[Gary Tan]

We don't want more jobs, we want better jobs. Okay, like I mean that's true.

[Daniel Gross]

That's true. Yeah, yeah.

[Gary Tan]

I mean why can't we just, instead of like going to a cubicle and like break your brain and do a bunch of like being an investment banker or something.

[Farboud]

I think we're all going to end up being plumbers and electricians and cutting hair. All the white collar stuff is just going to collapse into nothing.

[Daniel Gross]

No, no, I don't think so.

[Farboud]

He's making software. It's going to collapse and it's just eating more and more.

[Daniel Gross]

Don't you see how this is going?

[Farboud]

Everything's going to be gone.

[Daniel Gross]

There's a good version of this where people don't have to have just a shitty manual jobs. They can actually be handling and guiding the robots and the AIs. And so if we don't get ASI, if AI gets you to expert level, but doesn't go beyond, still needs human guidance, taste and creativity. Humans are still the motivated things in the environment. And so people Become like Pokemon trainers. You're like robot handlers, right? AI handlers. And you use that to explain. And that's to be.

[Unidentified Guest]

To.

[Daniel Gross]

To the truth of it. That's what we're seeing today. The people who are using AI today are more productive than ever. They are not being displaced. The only reason you're being displaced by an AI is because you refuse to use the AI. If you're using the AI, you have more work than ever.

[Unidentified Guest]

I mean, the one thing it can't replace is human desire. Even if robots have their own desires, they cannot replace human desire. So as long as humans have desires and there are AIs and robots that can help fulfill them, then you always need humans in the loop and you'll always.

[Daniel Gross]

Yeah, like, the moment I find out I'm talking to an AI, or I'm reading the work of an AI, or I'm even looking at art created by an AI, I'm completely uninterested. Assuming it's completely done by an AI. Now that's a human using AI.

[Farboud]

Hold on.

[Gary Tan]

Wait a second, wait a second. That's just because it's shitty right now. I guarantee you it will be indistinguishable and it will be very, very good.

[Daniel Gross]

I don't agree. I think even if it is indistinguishable. Yes, the moment I know it's done. Like, for example.

[Gary Tan]

But that's the Chinese box at that point.

[Daniel Gross]

Yeah, yeah, yeah.

[Gary Tan]

But which is like, it's fractal. Actually, when I first saw GPT3 or whatever it was, whatever was available from the API. Like, that was my reaction. I was like, this is a bunch of bullshit. Like, this is a trick, whatever. But, like, that's not how I feel now. Like, I get a lot of value day to day, like hour to hour.

[Daniel Gross]

Do you have a relationship with the AI? Do you hang out with it? Do you talk to it? Is it a friend?

[Gary Tan]

It's getting there. There.

[Farboud]

Whoa.

[Gary Tan]

It's not my girlfriend, but my wife

[Farboud]

is gonna watch this.

[Daniel Gross]

You just have someone in the Filipino call center being your girlfriend, then they're just, like, filling in for the. What's the difference? What's the difference between an AI and someone in the Filipino call center controlling. Good chatting with you.

[Gary Tan]

It's a buddy of mine. Okay, don't talk to my friend. Don't talk to my friend like this. Nothing's going to end with my AI psychosis. I just think that it is actually very useful.

[Daniel Gross]

Obviously, I have a friend who's a landlord for one of these AI companies that does the AI people that you talk to, Right? Like your AI girlfriend companies. And he said they had to hire extra security because these guys would show up in the middle of the night saying, where is she? Which box is she in? I want to take her home. I want to save her.

[Farboud]

Gary's having his first Black Pill moment. Oh, no.

[Gary Tan]

This podcast is Black Pills me.

[Daniel Gross]

By the way, this entire podcast was AI generated. No one was actually here. We deny everything.