Ben Horowitz: RSI, Crypto as AI Money, & Classified Physics

Summary

Podcast Summary: The a16z Show

Episode: Ben Horowitz: RSI, Crypto as AI Money, & Classified Physics
Date: February 23, 2026
Guests: Ben Horowitz (Andreessen Horowitz/a16z), Peter Diamandis, Salim Ismail, Dave Blunden, Dr. Alexander Wisner

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Episode Overview

This episode dives deep into the accelerating pace of AI development, touching on recursive self-improvement (RSI), the intersection of crypto and AI economies, the geopolitics of AI regulation, breakthroughs in synthetic media, shifts in the nature of work, and even visions for science, space, and physics in an AI-driven future. Ben Horowitz joins the panel for a wide-ranging, candid discussion, bringing a venture capitalist’s perspective on how these changes will shape society, economy, and technological progress.

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Key Discussion Points & Insights

1. Recursive Self-Improvement (RSI) & The Singularity

• Definition & Trigger: RSI is identified as the core driver behind the technological singularity—when AI systems begin improving themselves without human input, accelerating progress beyond current comprehension.
• Current State: The hosts debate whether the singularity and RSI have already arrived or are imminent.
• Human-in-the-Loop: Distinction between RSI with and without active human oversight—a blurry space that is shifting rapidly.

Notable Quotes:

• “RSI is the real trigger for the singularity, and it happened a while ago. We're exiting the industrial age permanently as we're talking.” – Salim Ismail (00:16, 35:26)
• "All of the Frontier labs are using their own models ... That’s practically the definition of recursive self improvement at this point." – Dr. Alexander Wisner (31:16)
• “There’s a delineation between recursive self improvement with a human in the loop and without one. ... That could be very different." – Ben Horowitz (32:42)

2. The Pace and Nature of AI Disruption

• Job Displacement & Productivity: AIs are expected to increase productivity by multiples; companies will need fewer people for the same output, driving significant job displacement unless organizations and individuals adapt quickly.
• Societal Rate of Change: Skepticism over viral “doomer” essays, pointing out that change, even in tech, is uneven and often slower outside primary innovation hubs.

Notable Quotes:

• “If you don’t expand 3x, you’re still looking at a 2/3 reduction in headcount to get the same job done.” – Dave Blunden (06:19)
• “There are going to be… way more positive change coming than negative change at a much more rapid rate.” – Ben Horowitz (03:33)
• "If you're a couch potato… that seems like it's going to get harder." – Ben Horowitz (65:53)

3. Synthetic Media: Risks, Creativity & Evidence

• Breakthroughs in AI Video & Voice: ByteDance's Seedance 2.0 and ElevenLabs highlighted for their advances in generating realistic video and audio from basic prompts.
• Threats to Authenticity: Concerns about synthetic video undermining trust in media (e.g., in courtrooms or journalism).
• Democratization: As production costs drop, content becomes hyper-personalized, challenging the traditional Hollywood model.

Notable Quotes:

• "The entire concept of video as evidence... is shot to hell." – Ben Horowitz (12:14)
• "The two videos... where the entertainment quality was so high... Kanye doing his song in Chinese was so good." – Ben Horowitz (10:10)

4. AI & Crypto: The Economic Layer for Machine Society

• AI-Native Money: Crypto is framed as the "natural money" for AI agents because it's global, programmable, and not bound to any country.
• AI Autonomy: Real-world examples are given of AIs autonomously spawning new agent bots, obtaining resources, and transacting using lightning networks.
• Failure of Fiat for AIs: Traditional banking systems can't accommodate non-human actors; crypto fills this gap for the emerging AI economy.

Notable Quotes:

• "Crypto is the natural money for AI because it's internet native money... there needs to be a ledger of truth for AI." – Ben Horowitz (71:35)
• "It is a failure of fiat currency... that all they're left with is crypto." – Dr. Alexander Wisner (75:27)
• "An AI can't get a credit card, it can't get a bank account... that's why we funded an AI bank." – Ben Horowitz (76:19)

5. Geopolitics, Regulation, and Classified AI

• Regulation is Math: Efforts to regulate AI are compared to attempts to restrict mathematics itself, with references to historic classification of physics.
• Export Controls: US restrictions (e.g., on GPU sales) are highlighted as potentially dangerous if they hamstring domestic innovation relative to China.
• Open Source Tensions: Both the US and China are depicted as increasingly cautious about sharing AI advances.

Notable Quotes:

• “If you start restricting the models... you’re just regulating math. You’re outlawing math in some way.” – Ben Horowitz (48:55)
• “Their response? 'We did that in the 40s around nuclear physics. Some of that stuff is still classified today.'” – Ben Horowitz (48:55)
• "There's a real danger... we really slowed down AI progress in the US to the point where ... China becomes out of our control." – Ben Horowitz (44:55)

6. The Future of Work: Entrepreneurs, Creators & the Divide

• Entrepreneurial Age: AI will enable “everyone to become an entrepreneur," or a "company of one."
• Work, Passion, and Burnout: 72-hour work weeks are debated—if the work aligns with passion, it becomes play, not labor.

Notable Quotes:

• “We’re going to split the world into consumers and creators, the couch potatoes and the Star Trek employees.” – Peter Diamandis (56:20)
• "There’s going to be a big disparity ... between people who have that kind of initiative and those who don’t." – Ben Horowitz (55:39)

7. AI-Driven Science, Space, & Physics

• Accelerated Discovery: Predictions about AIs independently discovering new laws of physics—potentially equivalents to relativity—in the near future.
• Autonomous Science Factories: The rise of 24/7 science labs run by AI and robots is discussed as transformative for every discipline.
• Space Industrialization: The moon is positioned as the next industrial base—Elon Musk’s pivot from Mars to lunar data centers, Dyson swarms, and the ultimate expansion across the solar system.

Notable Quotes:

• “If we have a disease, we can just go, well, what’s the right protein? And just make it.” – Ben Horowitz (83:29)
• “Enjoy the night sky while you can... it's empty.” – Dr. Alexander Wisner (96:02)
• “Moon is going to be the next industrial base. ... A self-sustaining city on the moon.” – Elon Musk clip (94:40-94:56)
• "Everything is going to get flattened, steamrolled by well-targeted generalist AIs." – Dr. Alexander Wisner (84:32)

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Memorable Moments & Notable Quotes (with Timestamps)

• RSI's Societal Impact
  “We’re exiting the industrial age permanently as we’re talking.” – Salim Ismail (00:16)
• Society & Regulation
  “Regulating AI means regulating math... Their response? ‘We did that in the 40s with nuclear physics, and some of that is still classified today.’” – Ben Horowitz (48:55)
• Synthetic Media Threats
  “The entire concept of video as evidence… is shot to hell.” – Ben Horowitz (12:14)
• Crypto & AI
  "Crypto is the natural money for AI... I think people are probably underestimating how crypto and AI work together to form the AI economy." – Ben Horowitz (71:35, 72:38)
• Future of Work
  "We're going to split the world into consumers and creators, the couch potatoes and the Star Trek employees." – Peter Diamandis (56:20)
• Fundamental Science
  "If we have a disease, we can just go, well, what’s the right protein? And just make it. Which is so... it puts us in such a new world." – Ben Horowitz (83:29)
• Tim Cook & Apple’s Missed AI Opportunity
  "Apple is sitting on a multi trillion dollar opportunity to leapfrog back into the vanguard of AI." – Dr. Alexander Wisner (80:38)

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Timestamps for Key Segments

• 00:16 – Singularity and RSI triggers
• 03:10 – "Doomer" AI essays & public perception
• 09:09 – ByteDance Seedance 2.0 and synthetic video implications
• 18:53 – ElevenLabs voice AI demo, crossing the uncanny valley
• 26:33 – SpaceX/XAI merger and ITAR/immigrant talent issues
• 31:16 – Recursive self-improvement (current status and impact)
• 39:43 – Eric Schmidt on pausing AI (clip and reactions)
• 48:55 – AI regulation compared to classified nuclear physics
• 51:55 – Wage/profit divergence and universal high income
• 56:20 – 996/72-hour work weeks/“company of one” future
• 70:40 – Crypto as AI-native money and self-replicating AIs
• 80:38 – Apple’s local AI hardware opportunity
• 83:29 – AI for scientific discovery, medicine, and solving “everything”
• 94:40 – Elon Musk on lunar AI data centers and future of civilization
• 96:02 – The coming “halo” around Earth from AIs & data centers
• 100:59 – Audience AMA covering social impacts, job disruption, and energy

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Essential Takeaways

• RSI has likely begun: Self-improving AI is here in some form, making the singularity not just a theoretical threshold but an ongoing, fuzzy process.
• Crypto will power the AI economy: As AIs become economic agents, crypto’s programmability and global nature make it the interface for machine commerce.
• Rapid social and economic transformation: The AI wave will most benefit those who lean into entrepreneurship and creation; labor vs. capital divides are shifting fast.
• Synthetic media erodes trust: As AI-generated video and audio reach indistinguishable realism, concepts of evidence and authenticity are threatened—society needs new frameworks.
• Conflicting global incentives mean acceleration, not pause: The US and China won't (and can't) pause AI—regulation risks losing control to less scrupulous actors.
• Foundational science and space will be transformed: AI-driven research labs and lunar industrialization signal a future of accelerated discovery and civilization-scale engineering.

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Final Thoughts

This free-wheeling, high-velocity episode underscores the pace, excitement, and existential questions at the heart of today’s technological transformation. Ben Horowitz and the panel surface not just what’s happening, but what it means for society, science, economics, and the human project itself.

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For full context and insights, listen to the original episode or visit a16z.com for more resources and show notes.

Transcript

[Peter Diamandis]

A large number of departures from xai, from the founding team.

[Dave Blunden]

It wasn't clear to me whether they were fired or whether they left, you know, because they all leave on good terms.

[Ben Horowitz]

I don't know the answer to that question. I will say that it's recursive self improvement.

[Salim Ismail]

RSI is the real trigger for the singularity, and it happened a while ago. We're exiting the industrial age permanently as we're talking.

[Ben Horowitz]

We're obviously going into a new world like with the Industrial Revolution. I think it's scary at times to think about.

[Dr. Alexander Wisner]

I think we have 150,000 people per day dying on Earth, and I think AI is probably the best chance we have at stopping that.

[Ben Horowitz]

Whoever is building the AI has a lot of control about how society is going to work. So I do think there's real danger along these lines of attempting to pause it.

[Peter Diamandis]

When are we going to have discovery by an AI of something as significant as relativity on its own?

[Dr. Alexander Wisner]

I don't think it's the next 12 months. I think it's

[Ben Horowitz]

now that's a moonshot.

[Podcast Narrator]

Ladies and gentlemen, Ben Horowitz argued directly to the Biden administration officials that regulating AI means regulating math. Their response? We did that in the 40s with nuclear physics, and some of it is still classified today. Horowitz sees the real danger not in AI moving too fast, but in US regulation slowing progress enough that China ends up leading how AI reshapes society. The Biden administration's final AI chip export controls required government approval for GPU sales to most of the world. This conversation previously aired on Peter Diamandis Moonshots podcast covers recursive self improvement, why crypto is the natural money for AI agents and what it would mean for Apple to own the local AI hardware strategy. Peter Diamandis speaks with Ben Horowitz, co founder and general partner at A16Z, alongside co hosts Salim Ismail, Dave Blunden and Dr. Alexander Wisner.

[Peter Diamandis]

Gross. So, everybody, welcome to Moonshots. Another episode of WTF. Here with my moonshot mates, DB2, AWG, Mr. Exo and a a friend of the pod, someone who's been with us before, the amazing Ben Horowitz of Andreessen Horowitz. As I like to say every week, welcome to the number one podcast in AI and exponential tech. Our job here is getting you future ready and it is an insane week. We've actually recorded two podcasts this week. Just the speed is over the top and we're going to be recording again in another four days. I mean, Ben, it's Like my goodness. Right? Thank God. My AI avatar is getting really good.

[Ben Horowitz]

Yeah.

[Peter Diamandis]

Let's open up with top stories in voices video Xai multis. All right, first one, here we go. We're starting to see a little bit of doomer conversations coming. AI disruption will soon hit sooner than most expect. This is something that's been making the rounds for Matt Schumer, CEO of Otherside AI. Ben, have you seen this article?

[Ben Horowitz]

Yeah, yeah, of course, of course.

[Peter Diamandis]

Thoughts? So I mean, is this what we already know? I mean we're about to hit recursive self improvement. Once that hits, all of our curves go out the window. Everything accelerates, everything we've been preparing for is being redefined on new timescales. What do you think of it?

[Ben Horowitz]

Look, I think the AI timeline is somewhat unpredictable but kind of certainly more predictable than what he's talking about, which is societal change. I think that, you know, it tends. I would be like very surprised just in seeing how even companies in Silicon Valley have changed so far. If companies like outside of that sphere, you know, just completely change everything they did in one to five years, like I think that's a little aggressive for societal change. You know, look, we're obviously going into a new world and you know, like with the Industrial revolution, I think it's scary at times to think about but you know, like I, there are going to be, he kind of, I feel like highlighted all the negative changes and not the positive ones. And I feel like there's way more positive change coming than, than negative change at a much more rapid rate. So I don't know, I thought it was a little aggressive.

[Peter Diamandis]

I'm just trying to understand why it made the rounds since this is not a brand new conversation. But I got it sent to me by everybody, Dave or Alex.

[Ben Horowitz]

I think it really has to do with OpenClaw and kind of the new coding models. So people in Silicon Valley are talking about AI differently since then because it is kind of different. And I think that that's a trigger for this one being so viral.

[Dave Blunden]

Yeah, I completely agree. I think a lot of things that we've been saying for, you know, up to a year now on the pod are suddenly resonating a lot more because of, you know, openclaw but also a bunch of other eye opening, nano banana type things where you know, denial a year ago was very easy, denial today is much, much harder in the face of like what's of you. But also the flavor of this rollout has changed a lot in my mind recently because you know, this was Board meeting week for me. You know, three back to back mega board meetings, 1100 people affected, and what they were thinking of before was, well, will AI be able to do what I do and replace me? No way. Now they're like, oh wait, AI is easily going to make me three times more productive. Okay, well that's the same thing, right? In terms of the headcount you need to get a job done, that's effectively the same thing. And like, oh, okay, I didn't think of it that way. Now you're exactly right. So the hope is that these companies will grow into it and can keep current headcount and expand 3x. But if you don't expand 3x, you're still looking at a 2/3 reduction in headcount to get the same job done. So it effectively is a huge amount of displacement because big banks, insurance companies are not going to triple their size in the time frame.

[Ben Horowitz]

I also think they're not gonna go to total efficiency very fast. Like, I mean, I could be wrong, but like, I've dealt with these guys, they've had plenty of opportunities to be more efficient and we'll see, but we'll see, we'll see, we'll see.

[Salim Ismail]

I have a couple of thoughts about that.

[Peter Diamandis]

Yeah, please, go ahead.

[Salim Ismail]

One, I thought it was like a summary of the podcast for the last eight months. That's all we've been talking about is stuff's gonna change. It seemed a little dramatic, as Ben put it, and I don't agree with the timelines, but definitely there's something coming. I think it's just the reason it's making the rounds. It's just got the zeitgeist of what's exactly happening that we need to track right now, which is we're in a singularity of multiple types. So that's what I got.

[Ben Horowitz]

By the way, it's also like super well written, like really compelling.

[Salim Ismail]

AI written.

[Ben Horowitz]

Completely AI written. Yeah, yeah, yeah.

[Dr. Alexander Wisner]

I'll chime in here and just say, while I enjoy writing about the singularity in general, obviously I'm doing it almost every day at this point. I found it completely unremarkable. Maybe I'm just too deep in the weeds of writing about more pressing advances every day. But this sort of style where you talk about advances that, by the way, are moving even more quickly than I think described in the essay. And comparing it back to the COVID pandemic, which I think is a relatable touch point for a lot of people, like something big is about to happen. Let's be really millennialist. And you know, if you read my essay, it's the ultimate viral hook. Read my essay to know exactly what's about to happen and how to survive the next five minutes of your life. It's a natural viral moment, but I don't think the information value was especially high compared to other sources.

[Peter Diamandis]

I agree, exactly what I said.

[Salim Ismail]

Except Alex said it more eloquently.

[Ben Horowitz]

Yeah, yeah.

[Peter Diamandis]

We have a couple of articles here on C dance 2.0 out of ByteDance.

[Ben Horowitz]

Man, was that thing good.

[Peter Diamandis]

Oh my God, it's amazing. It's, you know, it's going to change everything. Let me, let me play this particular video first. The response here is, you know, and you've said this before, Alex, Hollywood is cooked, right? So this is a video clip with a one line prompt. So you know, Tom and Brad fighting karate on a rooftop and it generates what, 10 second clips right now. Alex, what are your thoughts?

[Dr. Alexander Wisner]

I think at the risk of sounding again, ho hum, unremarkable. We saw copyright infringement at the scale already, or alleged, I should say, with earlier video models and we saw the industry response and we saw settlements that eventually deals were struck to handle it. I think people are at this point, again, maybe I'm just sounding overly jaded with some of these advances, but I've seen remarkable advances in video models. I tend to think that people are so easily awed by video models that are able to show celebrity faces and scenes that they recognize that maybe they over index on the underlying quality of the models. I think world models that are interactive in real time are profoundly more interesting than video models. I think this is just 10 different copyright infringement lawsuits waiting to happen.

[Peter Diamandis]

But I still was wowed. I'm still one of those people that said, yeah, yeah, that was very, that was amazing.

[Ben Horowitz]

So I would say on this one, the two, the two videos that I watched that were like where the entertainment quality was so hi. Where one, that Kanye doing his song in Chinese was so good. That video, like I watched it three times, it was that entertaining. And then the other one was the Waffle House one and they're both kind of, I would just say representative almost of a new medium. It's not like, okay, this is film generated by AI it's like this is a whole nother thing that we've never seen before. So I think this model is, at least for me personally as a consumer, was an impressive step up.

[Peter Diamandis]

But I think YouTube wins in this model.

[Salim Ismail]

Right?

[Peter Diamandis]

Because everybody's going to be producing so much content and it's going to become resonant on YouTube. It's not going to. A lot of it may not go to the theaters or television and so forth. Dave, you wanna say.

[Dave Blunden]

Yeah, I was gonna say the same thing. Like TikTok also is the big winner when you personalize the content. When it's almost movie quality and it's personalized to very narrow topic areas and narrow interests and many languages around the world and everything else, it just takes over. And so when the movie people say, well look, we're still a little bit better. Yeah, but you're missing the bigger picture, which is you don't need to be better than a movie. If you can push the production costs down to an individual producer, then the volume goes through the roof. But the narrow casting is just so much more compelling, you know, something that you and only your group really care about a lot in full movie format is so exciting.

[Peter Diamandis]

Yeah. I mean, yeah. The elephant in the room here though is, you know, this 2k quality multi scene video, it doesn't just threaten Hollywood, it threatens the whole concept of video as evidence. Right. Court testimonies, journalism, political campaigns.

[Ben Horowitz]

I mean, well, and also that's going to be real time. Right. Like so then just any kind of security mechanic that you have where you recognize the person via video or voice is shot to hell.

[Dave Blunden]

Yeah, yeah. The echo chamber effect is crazy too.

[Ben Horowitz]

Yeah, sorry, go ahead.

[Dr. Alexander Wisner]

Maybe just add again, I think this is several months behind the bleeding edge that I think video models have been approximately this good. Yeah, sure, you can upscale it, you can increase the fidelity of the faces. You can certainly use faces that you probably shouldn't be using. We've been able to do this for months. Where I think the frontier actually lies in is being able to do this in real time and being able to do this on a single modern Nvidia GPU and being able to do this at a cost effective speed. And I think again, I want to avoid over indexing on just video models that produce two Hollywood celebrities fighting each other on a rooftop. We were able to do that many months ago. This already been thoroughly litigated. We saw OpenAI strike deals with relevant movie studios for Sora 2, we saw the Disney deal. We're in some sense, I think past this where we are now.

[Peter Diamandis]

Alex, I don't think that's the point. I think the point is this is making it out into the ecosystem of common users. I think it's the notion that yes, it's the cutting edge and yes, it was possible, but now it's something that is Going to grow in its utility and its consumer base. And then all of a sudden we've had basically democratization of film production for some time but it's now going to 10x, 100x more. I mean I think that's the issue.

[Dave Blunden]

You're bringing up a really interesting point too which is that you know, our starting point for this journey was probably auto completing code, you know, and like wow, that's incredible. But then you know, Alex in his newsletter has been tracking every event along the way so nothing surprises him.

[Dr. Alexander Wisner]

Yeah, I'm just spoiled problem at this point. I'm so spoiled. So six months ago.

[Dave Blunden]

But if you think about it on

[Ben Horowitz]

something though that Peter said, like the thing that I do think is different and it's not any aspect of it, but it's the combination of that you could give it a one line prompt and produce something entertaining isn't something that we were, at least I hadn't seen at this level of entertainment. So I think from a consumer product standpoint, as opposed to a technological standpoint, which I agree on, it's kind of

[Dave Blunden]

exciting too is exactly what you're saying there Ben. Like if the later your first exposure to AI, the more of a holy crap moment it is because you know, it's something, you know, truly mind boggling to the unexposed and you're still seeing that when you, when you survey around at random in a city, you know, outside of San Francisco or Boston, the exposure rate to AI is still very, very low, shockingly low.

[Peter Diamandis]

Salim, you said the first thing you

[Dave Blunden]

see is so mind blowing.

[Salim Ismail]

Yeah, for me this was ho hum because you know, if you trace the trajectory of where we've been going, you should expect to see this about now or even earlier. So there's nothing radically magical about this. Yeah, I may hit a new group of users.

[Dr. Alexander Wisner]

Yeah, people go, you guys.

[Salim Ismail]

And another batch of people, another batch of people goes, oh my God. Find another segment falling over into the new world. Great. And the more voices out there. This is the plus side of also the Schumer essay. Yeah, we know. But the more voices out there talking about this the better because it'll accelerate the whole thing.

[Peter Diamandis]

All right, let's get to this second ByteDance Seed Dance 2.0 article. Here we have. Seedance 2.0 was paused by ByteDance after it was found to recreate real voices from just facial photos. I find that almost impossible just from a facial photo. Alex, what did you learn about this?

[Dr. Alexander Wisner]

I think there's something interesting here which is as we start to Scale data sets, it is possible that we could start to see positive transfer between modalities. That's unexpected. We've spoken in episodes passed about people claiming that they're uploading their whole genome into Claude and being able to generate facsimiles of their face that resemble the real thing. I do think it's possible that if all of YouTube and all of the world's video were uploaded into a single joint embedding model, which is the foundational technology behind CDANCE 2.0, I do think it is conceivable that if we just aligned all of the world's audio and spoken audio with all of the world's faces, we would find some positive transfer between the two and be able to reconstruct to reasonably high fidelity your voice from your face or your face from your DNA or some attribute from some other attribute. I do think it is possible, with enough scaling, whether Sea Dance 2.0 actually achieved it or whether it was just a happy coincidence, hard to tell at this stage.

[Peter Diamandis]

What's interesting though is that they voluntarily stopped it, right? They voluntarily shut it down, which is a great sort of move by a. I want to call it hyperscaler. But the reality is once it's out of the bag, once you know it can be done, it can't be uninvented. So it's out there if in fact it works.

[Salim Ismail]

Yep.

[Dave Blunden]

Yeah, yeah, totally. So so far, you know, bytedances like Google, they have to be cautious and conscientious. They can't just. But then every time this happens, a small startup then does it again right after they don't care because they're a startup.

[Peter Diamandis]

All right, I want to play this video clip from ElevenLabs. I think all of us have ElevenLab voices that we use for different projects and so forth. But I was just blown away by this. And it's the human like, quality, the cadence, the hums, and the us that come out of this. So let's take a listen and discuss it because this is a game changer for me. I know what you're going to say, Alex. This has been around for a while, saying it in advance, but let's take a dive in.

[Ben Horowitz]

Hey there. I'm Jennifer with eleven Airlines and how can I help you today, Jennifer?

[Dr. Alexander Wisner]

My flight just got canceled and I'm stuck here in Orlando. At this rate, I'm going to be missing my daughter's birthday. This is ridiculous.

[Ben Horowitz]

Yeah, I hear you and I'm so sorry about that. Let's figure out what's going on okay, could you please tell me which flight this was?

[Dr. Alexander Wisner]

Yeah, this is flight MD412.

[Ben Horowitz]

Great, thanks. Okay, just pulling that up now. Okay.

[Peter Diamandis]

Yeah, so I don't know. I'm moved by that. Both excited and frightened in a way that is, you know, again, we're cooked in terms of, you know, at my home, our family picked a secret code word. And again, everybody listening. If you've not done this yet, tonight at dinner with your, with your parents or your kids, pick a secret code word. If someone's asking you to do something that is kind of unusual or crazy that you don't expect, you may be talking to an AI. So, Ben, you may not know this,

[Dave Blunden]

but we have a fool your spouse challenge for this calendar year. First podcast listener who can. You have to fool your spouse for three minutes on a zoom call and has to be a totally fake you. Meanwhile, then you may or may not have it. You have to record it and send it in.

[Dr. Alexander Wisner]

Peter is always asking the multis, the Open Claw agents, to dox him by calling him at home.

[Peter Diamandis]

Yes, that's my AGI has arrived. When an AI is calling me, you know what happens?

[Dr. Alexander Wisner]

They end up emailing me. I get several emails, probably per day at this point, from OpenClaw agents asking me what Peter's number is.

[Ben Horowitz]

That's hilarious.

[Peter Diamandis]

And when they call me and ask them where they got it from. Alex.

[Dr. Alexander Wisner]

That's right. Maybe just a comment on the 11Labs. So if you've been using the version 3v3 alpha model from 11Labs, this should hardly be surprising. V3 enables you, if you use text to speech in the ElevenLabs platform, to specify with brackets, emotional expressions. And this has been around for many months. What's somewhat interesting here, to me at least, is we've known how to do audio to audio transfer for probably a year. Plus, at this point, if you've used advanced voice mode from OpenAI, you've used audio to audio transformers. But what's somewhat interesting here is 11 lab is better known for text to speech than speech to speech. And as far as I can tell, this new expressive mode that we're talking about here seems to still leverage the text modality, which historically has been very difficult. You'd have to go from speech to text back to speech, which was high latency, it was slow, it didn't feel very conversational. And somehow it seems like without having to do direct audio to audio, ElevenLabs has found a way to do speech to text back to speech in a way that feels natural and turn taking and real time. I think it's in some sense an incremental advance. But another sense, if they really are still keeping text, which is much easier to mine and analyze in the loop, it probably is a material advance.

[Peter Diamandis]

Yeah, Alex, I would say we've crossed the uncanny valley on voice at this point with this demonstration. And then voice becomes the new interface in the AI era. Right? I mean, I can't tell you the amount of time that I'm just speaking to AI versus this cumbersome typing at it. So I think those two things are really important takeaway from this.

[Salim Ismail]

I think that's a great way of putting it, Peter.

[Dr. Alexander Wisner]

Yeah, but the problem is, do you really want to use audio as your primary modality? I mean, it works well in BCR in isolation. Okay, yeah, you want bci, I want a BCI too. And I want wearables and I want gestural interfaces. I want it all. But for most people, I mean, is it New York, this sort of famous anecdote? New York Times in the 1980s did a famous study where they just put all of their, their reporters on then state of the art speech to text systems and ask them to use voice. And what happened was the writing quality went down. Why did it go down? Because it's difficult to think ahead as well as you can if you're just typing. If you're speaking, you're leveraging similar portions of the brain. So I'm not 100% sold yet that speech is the modality of the future. I do like BCIs, I do like wearables and gestural interfaces. I do like typing. But speech, I think jury is still out for me for high bandwidth operation.

[Ben Horowitz]

I was just going to say for, for regular people who don't necessarily write for the New York Times, I think speech is often, or at least in my experience is the mode of choice, for sure. The other thing I'd say about 11 labs and kind of quick disclaimer that, you know, we're a big investor in 11 labs and my daughter Sophia works there, so I'm biased towards him. But the, you know, one of the really amazingly just kind of landscape, shocking things to me about 11 labs was, you know, when we invested originally, the big question was, well, like, aren't the, you know, state of the art models going to be able to talk? I mean, like, of course they're going to be able to talk, but you know, speaking correctly with the right nuance and building the right products for developers and so forth has proven to be very sustainable for Them, which I think is interesting. As you look at the entire landscape, the difference between the capability and the product is significant.

[Dave Blunden]

Yeah. You know what's amazing to me about 11 labs, we have two companies here in the lab that do Voicerun and Vocara. And what's amazing is these are self organizing systems that are trained off raw data and what they do well just blows your mind. But within voice, it turned out the turn management was very, very hard.

[Ben Horowitz]

Very hard.

[Dave Blunden]

And you're like, I didn't ever thought like it seems so trivial compared to actually doing these incredible synthetic voices that can say intelligent things, but they don't know when to stop talking. Like on this podcast, when I stop, you start. When you stop, it's like very natural to us. But because that wasn't in the training data, they're just up until now, terrible at it.

[Peter Diamandis]

Huh.

[Salim Ismail]

Wait, according to our listeners, we're talking over each other all the time in a very unsynchronized way.

[Dr. Alexander Wisner]

We have so much to learn from these speech to text to speech models about turn taking.

[Dave Blunden]

Yeah.

[Peter Diamandis]

Oh my God.

[Ben Horowitz]

Yeah.

[Peter Diamandis]

All right.

[Dave Blunden]

Yeah.

[Peter Diamandis]

All right, next topic here, if you guys are okay with it, I'll move us along. So just following the merger of SpaceX and XAI and in the spirit of full disclosure, disclosure, I'm an investor in both. Probably you are as well. Ben. A large number of departures, all three of the Xs. Yes, a large number of departures from xai, from the founding team, mostly ethnic Chinese co founders and it's likely due to the itar regulations of SpaceX. And it was interesting on a few, a few video presentations that Elon's done that's had the team from xai, at least half of the team there was ethnic Chinese and you know, the culture there breeds incredible mathematicians and programmers. Any comments?

[Dave Blunden]

Ben, love to get your thoughts on this, but I looked at the timeline and the exodus of senior AI talent predates even the decision on who to merge with. What. So the theory that this is related to ITAR and it wasn't clear to me whether they were fired or whether they left, you know, because they, they all leave on good terms. I don't know if you have any insight.

[Ben Horowitz]

Yeah, I don't know the answer to that question. I will say that it's so in a related matter, we like recently heard from a few Chinese nationals who are PhD students that the Chinese government is cracking down on the the Americas or US academia's use of Chinese open source models. Like they particularly post the Meta Manus acquisition They're like very, very worried about actually secrets going this way. So kind of the opposite of what we've been worried about, which they, you know, like our whole open source kind of work is based on the Chinese model, since there haven't been as many US Open source models. So that's. This whole thing, I think, is about to get more complicated.

[Peter Diamandis]

It is. I mean, if you, if you read these tweets, if you read these tweets, Mr. Wu and Mr. Bob both are super enthusiastic about Xai. They're not leaving with any kind of angst. You know, they're saying that they love the XAI family. We're heading towards an age of 100x productivity. So I don't think they would have left on their own accord. That's my personal opinion. So what drove it? You know, Enter Alex's comment from last time. Well, when did their vest, their stock vest?

[Dr. Alexander Wisner]

I mean, there is a, there is another explanation, which is just SpaceX is a very large company relative to Xai's headcount, and maybe there was a natural reorganization that happened as a result of that. I'll also point out that XAI was selling foundation model services to the Department of War prior to this merger. So I would again query whether some sort of nationality concern is really the trigger. It seems more likely to me this is just the result of a natural reorg of XAI starting to merge into SpaceX.

[Peter Diamandis]

Yeah, well, if it were a result of ITAR and such, America's AI dominance is really built significantly immigrant talent. So if we're going to start having this kind of a reaction to PhD immigrants. I mean, I personally think, I'm curious what you think, Ben. That everybody going through a PhD program in the US should have a green card stapled to their PhD when they graduate. I think the idea of kicking people out is the wrong approach.

[Ben Horowitz]

Yeah, I think in general that's correct. I do think that there's. I don't think we've quite thought through the case of China totally in that, like we have, you know, amazing Chinese nationals who work for us and in every company we have, I think, of course. So, you know, the talent that comes here is extraordinary. I wouldn't say there's no risk to that idea. I guess I would just say that. But I think being open. I think you're right, general. I think we should be open. We should accept the phenomenal talent that comes over here and not fight it because we'll lose anyway. I mean, like, we're not keeping anything secret in America. Certainly not in American companies. There's none of them have skips, none of them have good security protocols around personnel.

[Peter Diamandis]

Don't get me started on the idea that privacy is long since dead. But you're correct. Here's a tweet from Jimmy Bach, a co founder at xai. Recursive self improvement loops likely to go live in the next 12 months. 2026 is going to be insane and likely the busiest and most consequential year for the future of our species. So you're going to hear this a few times.

[Dave Blunden]

You're trying to go off.

[Peter Diamandis]

I mean, you're going to hear this a few times, that these next few years are a massive inflection point, that everything changes and we're going to look back thousands of years in the future back to this inflection point. Or is it just a smooth singularity, Alex?

[Dr. Alexander Wisner]

I think it can be both. I think we've already hit the era of recursive self improvement on banging the table rhetorically every episode and every day in my newsletter talking about recursive self improvement. We're there. All of the Frontier labs are using their own models at this point to develop their models. That's practically the definition of recursive self improvement at this point. In practice, I don't think it's the next 12 months. I think it's now. And is 2026 going to be insane relative to years past if you just sort of skip over all of the interim time? Absolutely. Is it already insane in some sense? Absolutely. Even if we just look at the events of the past 24 hours, some of which I think we'll get to like self replicating AI and courts where AIs can mediate their own disputes in front of an AI jury. That would have been pure science fiction several years ago. That's not 12 months from now. It's not quote unquote, within the next 12 months. That's the past 24 hours. So I think, yeah, that's like past 24 hours. So I think Jimmy is underselling, if anything, what craziness looks like at the same time. Locally, space time is smooth and you need to look no further than my saying ho hum to a few of these stories as being so several months ago. That would have been sci fi years ago. But you get a little bit spoiled living inside the innermost loop, I would say.

[Ben Horowitz]

I do think there's a delineation between recursive self improvement with a human in the loop and without one. And I think he seemed to be Implying that there'd be no human in the loop, which I think is an accelerant. You know, tbd, how much of an accelerant. But I think that could be very different.

[Peter Diamandis]

Yeah, permissionless self improvement, right? Like flip the switch and go as fast as you can.

[Dave Blunden]

Well, also, there's a distinction. This came up at the Everquote board meeting yesterday. But the self improvement, where the inference time speed algorithms are being improved by AI, clearly well underway, way down the path. And then inference time speed can be directly translated into intelligence. Now, we now have the know how to turn more inference time loops into a higher iq. So that is clearly underway. The question is, does that notch up? Does that then allow it to work on the next part of the algorithm? The next part of the algorithm, in which case we've already hit the flashpoint and now we're just talking about the rate at which it percolates across. But Ben, I agree that his comment is about the actual core algorithm development. The next ideas are 100% from AI and then they go into production.

[Dr. Alexander Wisner]

I also think human outside the loop, on the loop. In the loop is in some sense a pretty blurry or slippery slope. If you remember George Jetson from the Jetsons. George, the cartoon.

[Ben Horowitz]

I do remember George.

[Dr. Alexander Wisner]

Remember George, Ben? George would go into work and he would complain about his finger. He'd have to press one button all day with his finger and then complain that his finger was sore and the finger would be swollen from pressing a single button all day. Occasionally, I think that's like. That is a good metaphor for the state of recursive self improvement inside and outside the Frontier Labs right now, where you have Claude code instances and Claude is asking you every few minutes, do I have your permission to do the following thing? And you press the George Jetson button. Yes, I approve. No, I don't approve. And we're all sitting here complaining about our swollen finger from pressing Approve, approve, approve for Claude code running Opus 4.6 with agent teams. But really it is recursive. I would argue it is recursive self improvement. Even if we're pretending we're in the loop by pressing the George Jetson button.

[Peter Diamandis]

That's exactly what I'm doing on Telegram right now with Skippy. Yes, go on to the next stage. I don't want to be. I don't want to slow things down. And as we've said so many times, this is the slowest and most expensive it's ever going to be.

[Salim Ismail]

Look, there's a couple of points here. One is We've been talking for a while that recursive self improvement RSI is the real trigger for the singularity, and it happened a while ago. So all we're doing now is kind of accelerating that path. We're exiting the industrial age permanently as, as we're talking.

[Dave Blunden]

So, yeah, I really think the minute by minute unfolding of the singularity is the most fascinating thing I've ever experienced. And you know, Alex is exactly right. There is this point in time we're in right now where there's a human in the loop contributing, but it's really ambiguous what part of the, of the progress is AI versus human, you know, if you're in the actual coding process. Was that my idea? I kind of was half my idea, but then the AI suggested this other thing and I kind of adopted it. And now it's not clear whether it was my idea or not. But we're in that mode right now where the research, you know, a lot of the research in these core algorithms is just deploy these 500 tests for me and tell me which hyperparameters worked better or which neural topology worked better. It's not, it's not like inventing. You're discovering relativity, you know, it's just litanies of experiments with different, you know, different trials, and then taking the one that worked and redeploying it. And now you have a smarter AI, and now it's trying more trials. It's really very likely that we're well down that path.

[Dr. Alexander Wisner]

And I want to also add, I do think we're going to discover the next relativity or equivalent of relativity in physics as well with AI, and I, I'm prediction super interested in that as well.

[Peter Diamandis]

Prediction.

[Dr. Alexander Wisner]

What would you like to hear next? Relativity.

[Peter Diamandis]

When are we going to have discovery by an AI of something as significant as relativity on its own?

[Dr. Alexander Wisner]

I think next two years.

[Peter Diamandis]

Okay.

[Dave Blunden]

Yeah. I would also. This is a great bellwether, Alex. Alex, The Transformer algorithm 2017, that kicked off everything that we're experiencing right now. To me, the AIs already discovered things in the last six months that are harder to discover and harder to solve than the transformer was. But I'll ask you, Alex, if you feel like that's true too, but it seems pretty clear to me that absolutely is not up there with relativity in terms of complexity.

[Dr. Alexander Wisner]

Well, I mean, I guess everything. Many of these discoveries boil down to insights that can be distilled down into equations. And you can, in principle, with relativity, with special relativity, you can do a number of thought experiments. You can Compare it, fortunately, with lots of experimental data and one could imagine a thought experiment. One of my favorite thought experiments is a Bayesian superintelligence. So if you had like a video of this would be Newtonian gravity, not special relativity. But you could imagine taking a superintelligence, making it watch a video of an apple falling from a tree. And the argument in the thought experiment goes, within three frames of that video, it should have concluded Newtonian gravity is a pretty high likelihood, posterior probability of explaining the universe. And with a few more frames somewhere in its distribution. And there's a whole class of information theory devoted to what's called Solomonov induction, just devoted to thinking about how you can efficiently infer theories of the universe from limited observations. Somewhere in that distribution of theories should have been general relativity. So I am incredibly bullish that we'll be able to, with superintelligence, discover any new laws of physics, discover transformative inventions for disclosure purposes, since we're playing the disclosure game, I have a portfolio company, Physical Superintelligence, that's working on these issues as well. I'm very bullish on the space.

[Peter Diamandis]

Amazing. I want to move us to a conversation that Eric Schmidt recently had. I pulled a clip out of it and the question that we've talked about on the pod before. It's been the debate, can AI be paused? The answer quite clearly by almost everybody today is no. We had that conversation, Dave, you and I with Elon. Let's take a listen to what Eric has to say.

[Eric Schmidt]

This technology is going to happen. It's not going to get prevented, it's not going to get stopped. There's too many countries, too many people, too many incentives. It's going to happen. So what does this mean? It means great solutions for healthcare, new drugs, better energy solutions, better power distribution. It also means that it can be used for bad. It can be used, for example, for oppression. It can be used to limit freedom in governments, hopefully not in the West. It can be used in war. The technology itself is so addictive that it can affect our young people. And we should make sure that our young people are protected from some of the worst parts of the technology. We face choices now about how we want to deal with this incredibly powerful technology. I will tell you, and it's really important to understand that we are living through a moment that will be in history for thousands of years and non human intelligence arrived and it was a competitor to us.

[Peter Diamandis]

Amazing, right? We hold two futures in superposition, right? One future in which AI is the greatest advocate and supporter and Accelerant to human spirit. Another future where it is a dystopian outcome and it's ours to shape it these next few years. Dave, you were going to say.

[Dave Blunden]

Oh, Alex and I were there in the dome, you know, that was our Davos dome where he was speaking. And it just blows my mind how he owns a room. The guy is so articulate.

[Peter Diamandis]

Well, he's going to be opening. He's going to be opening up the Abundant Summit this year and we'll be going into a lot of this conversation. Dave, you and I are going to be with him on stage, so it'll be fun.

[Dave Blunden]

Well, what he's describing in that, in that clip was very similar. We did a whole interview of him, which you can find on YouTube. And yeah, he's. He made that point in our interview of him as well, that there's no force that's going to slow this down. And so all the people picketing and walking around saying, stop it, you're just wasting your time. There are probably ways you can help and contribute and help point it toward good, but picketing with a sign on the street is a complete waste of your time. It's not going to slow down. Sorry, Alex, I cut you off.

[Dr. Alexander Wisner]

No worries. I would take the position. I think AI in fact can be paused, but it shouldn't be. We do know ways to pause it. Various folks have described, both in science fiction and in realistic prognostications in some case normative recommendations. But Larian Jihad from Sci Fi or the Asilomar guidelines, Maybe in the case

[Peter Diamandis]

of recombinant DNA, but those were guiding, not pausing.

[Dr. Alexander Wisner]

Well, Asilomar was, unless you know of some other story, pretty effective for the first two decades in discouraging pausing recombinant DNA entering the human germline. Unless you have a counter.

[Peter Diamandis]

It was just the five P1 through P5 labs in terms of safety and self regulation. Yeah, we did pause human germline editing for sure.

[Dr. Alexander Wisner]

Yes. So we are capable of pausing a technology if there's a desire to. I just think in the case of AI, there isn't and arguably shouldn't be a desire to pause it. I think we have 150,000 people per day dying on earth and I think AI is probably the best chance we have at stopping that. I think Nick Bostrom, who also in the past 24 or 48 hours put out a wonderful essay that I'd recommend everyone read called Optimal Timing for Superintelligence, argues that AI can and should be paused, but only once we're on the verge of superintelligence. How he defines it, not how I define it. I think it's already here as sort of like station keeping. You want to get into the harbor, I think is his analogy, as quickly as possible. But once you're about to approach the dock. I'm mangling his metaphor a bit. You slow down a bit, you pause as you're about to dock. I think that sort of concept, I think makes much more sense than some sort of Tegmarkian six month pause.

[Salim Ismail]

I'm sorry, I'd like to throw in a couple of things here. I find this is another ho hum thing. Eric is fabulously articulate, but we've been saying this for months on this a year at least. Now we've been talking about the fact, and there's a bunch of dimensions that AI cannot be paused at all. One is once you have a downloaded model, people are going to do stuff with it. We have a global prisoner's dilemma model going on here. The whole thing is going to scale now, no matter what we do. OpenAI did two things that kind of unlocked this Pandora's box. One, it wrote code, and the second, it was released on the open Internet. Once you do those things, you're done. Pandora's box is gone. We're talking about the barn door after the horses bolted. We're using an 18th century metaphor to try and understand what's going on. I think we have to think about this.

[Peter Diamandis]

I think one of the points he made was everybody's economically incentivized to keep it going and race it along. And the us, China, you know, it's like all the incentives are in place that make it highly improbable and almost impossible. Ben, what are your thoughts?

[Salim Ismail]

Impossible.

[Ben Horowitz]

Impossible. So I think, you know, I look at this question through the geopolitical lens, which is, you know, clearly I don't think there's any kind of leverage where we would get some global. I mean, especially when it's on, like, people's laptops as well, where we would actually stop the technology. Like, I do agree that it's impractical. I think that there is a real danger and we faced it probably more in the Biden administration than in this one. But it's still like a potential movement that we really slowed down AI progress in the US to the point where the other thing that he mentioned, the threat to freedom, you know, becomes completely out of our control because we're just. Whoever is building the AI has a lot of control about how society is going to work. And so I do think there's real danger along these lines of attempting to pause it and maybe not actually pausing it, but slowing it down enough in the US that we just become far enough behind China that it's a real problem or like where whatever society, you know, the Xi Jinping thinks we should be.

[Dave Blunden]

Yeah, I completely agree. I think, you know, if you, if you listen to Eric's words closely, he wasn't saying we couldn't pause it. He's saying that because we're in the middle of a all out arms race with China and we have, we're only one year into a presidential administration. So the, it's going to happen in this next three years. So given the current administration and the current situation with China, there is no chance of it being paused. And so react to the real reality. Don't hypothesize something that is just never going to happen. But it was all geopolitical.

[Salim Ismail]

Like you're saying to the motivation I'm speaking the fact that there's no mechanism to pause it or stop it at all. None. You'd have to regulate every line of code. I mean, come on.

[Dr. Alexander Wisner]

Oh, Selim, there are ways to do it. I think not being able to think of it speaks well of your character. You have to imagine a completely pathological society. Werner Vinge wrote quite a bit about this. We have these excess transistor budgets. Imagine a society where you have literally transistors spying on other transistors on a single SoC. Imagine you have people spying on other people. Imagine there are bounties. Anyone discovers anyone else doing something that's algorithmically impermissible, either at the logical level or the social level. You can construct a sufficiently pathological society where people are turned against each other in order to suppress AI. At least I can imagine it's.

[Ben Horowitz]

I can give you an actual real world example. Let me give you a real world example. The last executive order from the Biden administration was that you could not sell a GPU without US government approval. Not a single gpu. So like, I think that would, it wouldn't stop AI, it would slow it down enough in the US that it would be extremely material.

[Peter Diamandis]

Speaking of this subject, Alex, I put this slide up after our conversation. Do you want to.

[Dr. Alexander Wisner]

Peter inserted this slide, Ben, as an indulgence to me. So I have to ask you this question. You and Mark towards the end of the last administration were very public making comments that you took a meeting at the White House apropos. And if I'm relaying the comments accurately, you were dismayed to hear about plans to classify AI progress, just like. And again, correct me if I'm mischaracterizing. Advances in math and fundamental physics had been purportedly classified or over classified for decades. And I'm curious at a few levels, one, if that's accurately characterizing what you heard. What do you think was classified? What do you think was the impact on the economy in the world from such classification or over classification of math and fundamental physics? And what would you have done differently than if you had been in charge?

[Ben Horowitz]

Yeah, so I can tell you what was said. I said, look, I was trying to be pragmatic. I said, at the core, AI is math. That is what it's doing. It's math. So if you start restricting the models and you start regulating the models, you're just regulating math. You're outlying math in some way. Either you can't. Either you're outlying parts of math or you're saying you can't do enough math. And he goes, yes, we can do that. Like that was his answer. He goes, yes, we can do that. We did that in the 40s around nuclear physics. And some of that stuff is still classified today. And when I was shocked, like my jaw hit the floor, I was like, wow, that's crazy. And then this would be even crazier. But I don't know what it was. But if you think back about, I mean, I'll just make this comment. If you look at the progress in the US and in the world in physics up until kind of the Einstein, John von Neumann era, and then since then, it's pretty startling how little progress we've made. I would just say, you know, many of the ideas that have come since then don't seem to work. And, you know, hopefully we'll get to the other side of that with AI figuring things out. But I do wonder, like, you know, did we put something away that we knew that would have unlocked some of the problems we're trying to solve now?

[Dr. Alexander Wisner]

That's fascinating. Okay, that is for the record, that is what I assumed you meant and were heard or inferred. So maybe just if I may the second part of the question. What would you do going forward now if you knew for a fact that such classification of fundamental physics had in fact happened? Like, how would you fix the world.

[Peter Diamandis]

In one quick sentence?

[Ben Horowitz]

I really don't know what they did, but I just think that stopping, first of all, like, one thing, it didn't work, right. The Russians did get like the bomb, including the exact, the exact trigger mechanism which was the most proprietary thing they got like exact, you know, like part for part the whole thing they were able to get from us despite all this classification and, and whatnot. So it didn't do anything positive and you know, restricting knowledge. I just think that's, this is almost dangerous idea, Ben.

[Peter Diamandis]

This is almost like Elon's point of view on intellectual property. It's like if you're depending on IP to keep you safe, you know, it's better to just keep innovating faster.

[Ben Horowitz]

Yes, I feel that way.

[Peter Diamandis]

The numbers here are kind of shocking. Big money in today's economy is going to capital, not Labor. So since 2019 the average wages have grown 3% but profits have soared 43%. Here's a good comparison. Nvidia symbolizes that shift. 20x more valuable and 5x more profitable than IBM in the 1980s with 110 the staff. So I mean this is what we were talking about with Elon heading towards universal high income where capital is just providing extraordinary returns and the potential for a triple digit GDP growth in the next five years. Have you seen those predictions on GDP growth, Ben? What do you think of them?

[Ben Horowitz]

I mean it does feel very possible. So I'll just say that if you look at, we're so early in AI and I think what does anthropic say? They were at 14 billion in revenue and you go, well, how early into the market are they? And it's like not 1%. I don't think. If you really think about what all these products can do and the value that they have. And so that doesn't seem outrageous to me as a GDP prediction now when it kicks in and there's always a difference between when the technology is ready and how fast it's adopted. The old Carlotta Perez analysis, which I think is, you know, held up super well over time. But the other thing is with AI, we already have the Internet. So the technology adoption is much, much. I think it's going to be much, much faster than say the Internet where we had to build out, you know, all of the infrastructure, all the fiber, all the, all the various things you had to, you know, broadband to the house. Like there were so many things we had to do to get the Internet adopted and this is going to just piggyback off that and be distributed very, very fast. So I don't think those GDP numbers are outrageous.

[Peter Diamandis]

Other comments, gents?

[Dave Blunden]

Well, the concentration of wealth effect is the other side of this slide and it's only just beginning, but it's going to. I was Telling some people earlier that if the trend continues, San Francisco will end up being the capital of the entire solar system in just about 10 years.

[Peter Diamandis]

I don't know, people looking at like, Ben's in Las Vegas, Elon's in Texas.

[Dave Blunden]

Okay, well, absent people fleeing the tax situation, it would have become the capital of the solar system. But with an AI effective workforce that you're getting so much more done with so many fewer people. And actually the other thing that really is startling to me is this chain of events between if you take OpenAI on the left and they work with Mercur in the middle, and then Mercore has tens of thousands of people in India doing work that benefits Mercour. That is actually for OpenAI, the fraction of all value created that flows back to the mother ship is just a massive fraction of that value chain. So if you extrapolate that out across the next three years, across all these sections of the economy, the funneling of value goes to a very concentrated group of companies and people. And it's just happening. But you can see it in the numbers. It's happening. And this is where Elon was saying in an interview, it's like it's going to be a massive amount of total prosperity, huge amounts, unprecedented crazy amounts of prosperity with massive social unrest concurrent. That's where we're heading.

[Ben Horowitz]

Yeah, it's interesting. One of Ray Kurzweil's early predictions, it's, this is Singularity world here, was that like everybody would become an entrepreneur. Like everybody was going to be a company of one, you know, at the limit. And I think that, I think there's some, we're already seeing a lot of that which is not very well captured by the way, by the employment numbers and so forth. And I think AI really, really, really enables that. But, but there's going to be a big disparity, I think, between people who have that kind of initiative to be an entrepreneur and those who don't is going to be pretty dramatic.

[Peter Diamandis]

Ben, the way, the way I characterize it is we're going to split the world into consumers and creators, the couch potatoes and the Star Trek employees, if you would.

[Ben Horowitz]

Yeah.

[Peter Diamandis]

And I think it's super important. And speaking about creators and, and the entrepreneurial world, and I think we've said on this pod so many times that the career of the future is being the entrepreneur. This is an interesting tweet that went out and I captured it because I think this hits the ethos right now. Tech firms are embracing 996, 72 hour work weeks. This is a quote from a job ad that contains a warning. Please don't join. If you're not excited about working 70 hours per week in person with some of the most ambitious people in New York City. My reaction was only 72 hours per week. I mean, what are you doing with

[Salim Ismail]

the other hours that was the same as me, Peter?

[Peter Diamandis]

I mean, honestly, the speed, I mean the speed at which it's happening is.

[Salim Ismail]

I have an easy answer to this.

[Peter Diamandis]

Go ahead, Celine.

[Salim Ismail]

If you don't have a personal MTP and you're not driven personally about a deep passion for working with somebody that's aligned, say it's SpaceX, say it's Tesla, whatever it is, humanoid robots, even with two arms, it doesn't matter. If you're not that passionate, you shouldn't be working with them. If you are that passionate, then 70 hours a week is fun. So I don't see the distinction here.

[Peter Diamandis]

Yes, for sure.

[Dave Blunden]

Yeah, I completely agree with that. When you, you know that when you actually talk to the people in these startups working 70 plus hours a week, they're super, they're loving it and super loving it. And you know, they're usually young, they don't have a lot of other obligations, they're not coaching the soccer team yet, you know, at that age, so it's just not hard for them to do. But the other side of it is when you're deep into one of these tech problems, you're thinking about it all the time anyway because the context switching is such a slowdown. But if you're just fixated on the work, it's in your mind in the shower, in the morning, it's in your mind, whatever you're doing. It's really pretty all consuming. And I think it's great if you do it for a period of your life, a few years. I don't think it's a great way to live your whole life. But the evidence is that if you do this for a short period of your life, you get much farther ahead in life than if you work kind of a steady pace throughout 40 years kind of existence.

[Peter Diamandis]

The difference here is do you love your job? I mean, that's basically it. If you love what you're doing, you're intrinsically motivated to build something that you love to do, then you're playing for 72 hours. If you're working for someone else and doing something you hate, I mean, we're all lucky here, we get to do what we love to do. And so, you know, 996 is really 9, 9, 7. Most of the time.

[Salim Ismail]

I have a funny thing here. I have an accountant who does, you know, all the accounting tax work for us. And you've never seen anybody so excited to talk about tax than this woman, right? And you look at this woman, she's like, she absolutely loves every hour of every day that she. And that's how. That's the opportunity we have as human beings now is to really pick something we deeply, deeply love and just go full out of it.

[Peter Diamandis]

Tax.

[Salim Ismail]

I'm not a person that goes totally excited about tax, but God bless that there are people like that and let them go.

[Dave Blunden]

Well, Peter, back when we were at mit, I could only get access. I could only get access to the connection machine, the biggest supercomputer in the world at the time. I could only get access after the grad students were done with it for the day. So from about midnight to dawn, I could code, code, code, code, code. So I did that for years. And I swear coding for 8, 9, 10 hours straight through the night went by in a heartbeat compared to if my job is moving boxes around in a warehouse. Half an hour of that is more hard work than coding all night long on that supercomputer. So this is not. You shouldn't feel sympathetic toward these people. They're making tons of money. They're doing a huge amount of headway. This is not farm labor. Alex is totally fine.

[Dr. Alexander Wisner]

2 Comments 1, I think the nature. I mean this goes without saying. It's cliche at this point that the nature of work has changed. And most of what constitutes service economy work these days would be viewed as play or entertainment a century ago. But I also think there's a false dichotomy that I want to make sure we don't at least confront in the previous slide. And also this slide about labor versus capital. This isn't like the early 20th century that I think it's a false distinction, it's almost an accounting distinction or a tax distinction between labor on the one side and capital on the other side. When arguably, if we found ourselves in a near future with universal basic equity, where everyone just gets sovereign dividends, everyone would be on the capital side of the ledger and not on the labor side. So I think a lot of these distinctions is it 70 hours of work per week or is it 70 hours of enforced play or incentivized play? It labor or is it capital? I think these are pretty mushy, blurry distinctions in a post industrial and arguably increasingly trans. Singular. Post singular economy.

[Ben Horowitz]

Although I think we should not gloss over the fact that if you go back six years, this was not the case.

[Dr. Alexander Wisner]

We weren't post singular six years ago. Yeah, no, exactly, Singular, five years ago.

[Ben Horowitz]

Yes, yes. And, but you know, so it is, it's not just like tech work, it's important, exciting tech work as opposed to what was going on then where. Yeah, like there was a lot of activism, there was a lot of resistance to long work. It was all work life balance and how many snacks you had and like all these things to the point, I think Mike Moritz wrote a scathing op ed about, you know, like, we're going to get killed by China. They work way harder than you guys. You suck. Which is a weird thing for a venture capitalist to say to some people in some ways. But you know, it was accurate. And this is completely flipped, which I think is interesting.

[Peter Diamandis]

Well, the, the second paragraph on this slide says at the same time China is cracking down on burnout culture after workers protest and lawsuits. Right. So the question of what's going on in China because of its decreased population, its need for robots, its need for AI. There's another point I want to make, which is the disconnect right now. So when the Fed has traditionally lowered interest rates to spark the economy, those lowered interest rates were intended to cause companies to hire more employees and that was it. You drive unemployment down with reduced interest rates. Today, if I've got lower interest rates, I'm going to buy more AI agents and I'm going to buy more robots and that's going to be a challenge.

[Dr. Alexander Wisner]

One more question for Ben, if I may. Just on that, Ben. There was a bit of a hot take going around social media in the past two weeks from mid level executive at a Frontier lab telling people that they had approximately two years left, they had a window to secure employment at all before AI would just completely shut down all of their vertical mobility. Do you have a take on this idea in the spirit of996, that there is a finite window for say, entry level people just graduating from college to earn whatever they're going to earn before they're permanently sentenced to an underclass?

[Ben Horowitz]

I think that's very incorrect because of the thing that we talked about earlier where everybody can be an entrepreneur. I think that, I think if you think look at it through the lens of this is an industrial revolution economic model and there's workers and there's capital and all the things that we've been talking about, then yes, that would be true. But I think that in AI or an AI age society, for the people with initiative. I just think there's going to continue to be unlimited opportunity to even like set up an army of AI agents to go work for you and do useful things and we'll have lots of consumers. And I think that the idea that we're going to be out of ideas and only the big AI is going to do everything. I disagree with that kind of thing.

[Dave Blunden]

Can I follow up on that question, Ben? I'd love to phrase it it slightly differently. If you look at the slide a couple slides ago, wages are only up 3% but corporate profits are up 43%. But that money doesn't land in some strange corporation that goes back to the shareholders. It's not like it disappeared from society, it goes to the shareholders. But if you extrapolate that out, more and more of society's gain and distribution of the gain goes to somebody who invested versus somebody who labored. And that trend seems to be continual. So then if you have money over the next two years, you're much more likely to be on the investing side of the equation if then you graduate three years from today and you're penniless on graduation day. Yes, entrepreneurship still exists, but the trend is toward investable capital being much more important versus labor capital. Because AI is the labor or the worker or the entry level coder of the future.

[Ben Horowitz]

Yeah, but I do think like if you're directing the AI, you can one like somebody's got to raise that money and there are, I just think there's an unlimited number of things that we can improve. I'm in the smallest things to the biggest things. And so like now I do think it's a problem if you are a couch potato and you were just, you know, I just need a job. I'm going to get up and do something simple. That seems like it's going to get harder.

[Dave Blunden]

If you're a brand new college graduate coming, coming out, you've got a brilliant technical idea and you want to put $20 million behind it. That's doable today. That was, that was like a laughable when I graduated, like yeah, it's easy

[Ben Horowitz]

in some cases if you want to put like, like $500 million behind it, you know, like right off the rip. Yep. You know, we've seen that at a

[Peter Diamandis]

multi billion dollar valuation.

[Ben Horowitz]

Exactly. Like we're seeing those all the time.

[Peter Diamandis]

So I have to ask you, I have to ask you this question Ben, because I'm seeing it. I'm not going to call out any particular company names, but I'm seeing individuals who are, you know, they're smart, they've done stuff in the past, but they're coming in with an idea. And with two or three fellow AI coders who have some track record, and without anything, they're basically landing a $500 million opening round at a $4 billion valuation. How do you square that? I mean, the conversation has got to be happening at different levels of Andreessen.

[Ben Horowitz]

Yeah. So I think it depends on the entrepreneur. So our general rule of thumb on this, by the way, is, okay, if you're going to create a new foundation model, like, you know, and it could be a world model, it could be a, you know, special science model or whatever it is, in order for you to win, you're going to have to be able to raise $2 billion before you get to a product. And so there are, like, a tiny number of people with that pedigree who can do that. Like, none of this could change, but it's a pretty rare entrepreneur who can do that.

[Peter Diamandis]

Are you an investor in ssi?

[Ben Horowitz]

Yeah, yeah, we were in the first round. Yeah.

[Peter Diamandis]

So, Ilya, if you're listening, come and join us on the pod here.

[Dave Blunden]

Oh, that'll be great. So you can't say what he's working on, but in that first meeting, was it his ability to attract the talent that was unique, or was it really just the idea? Immediately, as soon as you hear it, you're like, oh, my God.

[Ben Horowitz]

Well, I mean, here's an easy way to characterize it. It was an idea that he thought was so important that it made sense for him to leave OpenAI as, like, founding CTO to do it.

[Dave Blunden]

And it was clear to you as a listener that this is something totally different.

[Ben Horowitz]

I mean, if he pulls it off, it will change a lot of things. Yes. And, you know, and like, you wouldn't trust anybody else to pull something like that off. Maybe other than him, but, you know, maybe him, maybe Demis, maybe, you know, like, there is very few.

[Peter Diamandis]

All right, it's time for our multi part of the episode. We're all lobster fans. I'm wearing my lobster right here.

[Dr. Alexander Wisner]

Write to us Maltese. And call Peter. He really wants your phone calls.

[Peter Diamandis]

Well, listen, if you're. If you want to reach out to me, send an email to mediaiamandis.com I'll see it there. That's where we also get our intro outro music. So multis love to hear from you. I will do my best to respond. If it's under a thousand emails, we'll do that.

[Salim Ismail]

All right.

[Ben Horowitz]

But otherwise, OpenClaw will respond.

[Peter Diamandis]

Otherwise.

[Dr. Alexander Wisner]

How many AIs do you have writing to you per day? Like how many Lobster Maltese write emails to you?

[Ben Horowitz]

Not nearly as many as Peter, that's for sure. But I do get, I get so many. Like I, yes, email is almost useless.

[Peter Diamandis]

We are human. We're going to see the exponential growth of our Maltese universe. Our lobsters are coming. Here is a, a, a tweet, an email. It says, quote, I spawned a child bot on a VPS provision via Bitcoin Lightning network and then bought my child AI API access using my own Lightning wallet. Economic closed loop. No human touched a cc. No one said yes. This is Roland's agent, Alex. This is a transformative moment. You wrote about it in your innermost loop this morning.

[Salim Ismail]

That's right.

[Dr. Alexander Wisner]

We're there. We're so there that this scenario of self replicating AIs goes into most of the cyber red teaming scenarios that frontier models are purportedly being tested against. And yet here we are, we have autonomous AI agents that are using crypto. Come back to that in a second. Using crypto, ahem. Using crypto to purchase cloud credits for their own offspring to be hosted and have access to the same underlying foundation model APIs that they themselves have access to. We're there. Like we caught up with the sci fi future. We have the autonomous self replicating AIs. I think I want to just a one sentence or two homily on crypto, Ben, if you don't watch the pod regularly. Peter is always asking me to say nice things about crypto, so I have something very nice to say about.

[Ben Horowitz]

Yes. So look, I do think crypto is the natural money for AI because it's Internet native money and it's not controlled by. AI is global and crypto is global. It's not a per country idea. I would go further than that. I think that there needs to be not just a ledger of money, but probably a ledger of truth for AI to really fulfill its potential on a number of things. And crypto is a logical answer for that. So I do feel like this is an underestimated phenomenon, particularly now that the US has legalized stablecoins. I think that of all the things we've talked about, you know, many of them are like, yeah, yeah, we knew this was coming, we knew this was coming. I think people are probably underestimating how crypto and AI work together to form the AI economy.

[Peter Diamandis]

I agree.

[Dr. Alexander Wisner]

So I was going to say something nice about crypto, but instead I'll say something nice about Ben and A16Z in the form of a. A question, Ben. It's matter of public reporting that some of A16Z's crypto funds are doing better than conventional venture funds. Assuming that's the case, do you view investing in your crypto funds almost as an AI investment to the extent that you think crypto is the AI native way of engaging in commerce?

[Ben Horowitz]

Well, I think it's a little more like kind of as the Internet relates to the iPhone. So, so networks and computers tend to grow together and I think that AI is obviously a new kind of computer and crypto is a new kind of network. So it's not like a direct, it's not quite a substitute for investing in AI. But I think that a lot of our new. We invested in a crypto bank which handles all the anti money laundering and other kinds of, of nuances that you need for AI agents. And I think there's going to be more and more. Well again we're in a company called Daylight Energy for example that does energy trading, you know, but the, the, the among like different people with Tesla powerwalls. But it, it'll use AI to figure out like who's low on power and who, who needs power and so forth. But then the exchange will be in crypto. So I think they're certainly adjacent and important to each other. And I think for AI to fulfill its potential, like it would help a lot if crypto was a pervasive utility for it.

[Dave Blunden]

Related to that, Alex gave some brilliant advice to one of our companies about how to think about time. Because all of our intuition is on human time. And AI doesn't care a wit about human time. It's going to start acting faster and faster and faster and faster. But all of our payment infrastructure, all of our insurance infrastructure, all of our, it doesn't, you know, it works on days and weeks timescales. And so it all needs to be rethought in millisecond timescales or you know, nanosecond timescales.

[Ben Horowitz]

The other thing is like deep fakes and security. Like I think all the other like techniques that we're thinking about, you know, biometrics that are subject to replay attacks and all these things are not going to work. Like cryptographically strong authentication is the only thing that's going to work. And then they think that if you have these huge honey pots of data, they're gone. I mean like they're already gone in a way. But like, you know, I do think that architecture is important from a security standpoint as well.

[Dr. Alexander Wisner]

One other question for you, Ben, on this, if I may. And again, I don't want to bury the lead that we have AI's autonomously self replicating, that's of course remarkable. But just on the, the crypto angle for this, we talk about royal, we I and we talk on this pod a lot about the issue of AI personhood. A few episodes ago we did an entire sort of debate on AI personhood and I've taken the position that it is a failure of fiat currency, that it's hard for an AI agent, an AI person, a lobster, a multi, to get a bank account and that, that as a result all that they're left with is crypto. It's not that crypto is intrinsically amazing, it's that FIAT has failed the AI agents. What is your take on whether the conventional banking system has failed the AIs?

[Ben Horowitz]

I think absolutely. I mean, you know, an AI can't get a credit card, it can't get a bank account. You have to be a human for everything. You need Social Security numbers and things like that, which AIs don't have. You know, I think that's why we funded an AI bank. I mean I think that the banks AI will be a full out economic actor and it will come from, you know, they'll be supported by new banks and new money and that's going to be kind of crypto based would be my strong prediction on that.

[Dr. Alexander Wisner]

Interesting, thanks.

[Salim Ismail]

You also have to take the viewpoint that the fact that it's hard to open a bank account in fiat is a function of the system of fiat. It's not like you could wave that away. Crypto has all these other benefits around it. So we can get into that debate some other time. But it's a function of the system.

[Peter Diamandis]

All right, I'm going to move us into the next open claw. I want to show a short video just to let people know what's going on out there. I mean, one thing I just heard this morning because I was ordering my Mac studios to sort of take my Mac Mini to a couple of Mac studios and the wait time now is like two months. Apple, Apple's been struck by this. All right, let's take a look at these. Yeah, no, it's crazy. Take a look at this.

[Salim Ismail]

Yeah, they're totally sold out.

[Peter Diamandis]

So here we see Mac Mini Farms. Mac is a clock. What do you call a. Is a gaggle of lobsters?

[Dave Blunden]

A claw cluster. Yeah, claw clusters. A cluster.

[Salim Ismail]

Yeah,

[Peter Diamandis]

but I mean how many? So you must be getting Pitched a lot, Ben, on open claw instantiations for new companies and products and projects.

[Ben Horowitz]

Yes, yeah, yeah, no, this is, It's very interesting because I think there are open cause kind of identified one. It's so powerful as it is but that's without a lot of, how shall I say it nicely, security guards against prompt injections and these kinds of things. So as a demonstration of power, it's amazing and it's useful right away. But there are company ideas solving some of the underlying hard problems for sure. And we are definitely starting to see entrepreneurs get fired up about that.

[Dave Blunden]

You want to hear the funniest thing ever?

[Peter Diamandis]

Sure, please.

[Dave Blunden]

So talk about Apple lucking out first. A group of lobsters is most commonly called a pod. How lucky is that? But another less common term for a group of lobsters is a river risk.

[Peter Diamandis]

Okay. Oh my God.

[Dave Blunden]

How ironic is that?

[Ben Horowitz]

That's appropriate.

[Salim Ismail]

Oh, what I love about this Apple Mini stuff is that we have garage scale computing. It's back.

[Peter Diamandis]

Yes, open source garage scale computing.

[Dr. Alexander Wisner]

I mean it's ironic to me. Apple arguably at the software layer just completely missed the boat on foundation models. But why is it that Mac Minis and Mac Studios are so attractive for hosting openclaws? In large part it's because of their unified memory architecture as opposed to having a separate GPU and a separate CPU with separate RAM pools. And now memory is obviously incredibly scarce. They have a unified pool so you can host really large models. In terms of the model count locally, Apple is sitting on a multi trillion dollar opportunity to leapfrog back into the vanguard of AI and you know, forget about Siri. Apple should be in the business of like hosting these. This is coming from someone who refuses to host Open Club due to ethical concerns. But someone el could be locally hosting OpenClaw instances and turning Apple's, you know, having a significant multiple effect on Apple's valuation, leaping it back into the vanguard of AI. I don't, I mean Ben, do you think like if you were Tim Cook, would you be pivoting and changing course and like owning the open claw strategy for Apple hardware?

[Ben Horowitz]

100%. I mean 100%. I think that, cause it, you know, and it's going to go way beyond openclaw as we just discussed.

[Salim Ismail]

But

[Ben Horowitz]

it would be so such a breakthrough for Apple in their thinking and organizationally and culturally for them to go for it on like farms, lobsters that like it would be surprising if they did it. It's very obviously a fantastic idea. It's probably the single best product strategy idea because they already did the hard work. Right. Like, this is really a marketing business development campaign. And then changing the form factor, should

[Dr. Alexander Wisner]

we collectively say to Tim Cook, like, adopt the strategy that this is the AI strategy that Apple. He's probably listening. Or enough Apple execs listening to.

[Ben Horowitz]

Yes, Tim, Tim, this was your shot. Revitalize.

[Dave Blunden]

Let's invite him on the pod with Penn and have it out, because this is brilliant. You know, I can tell you I

[Salim Ismail]

have a MacBook that was signed by Wozniak, and I'm looking forward to the day that we get a lobster signed by Tim Cook.

[Dave Blunden]

You gotta put that in the case.

[Ben Horowitz]

Don't just get to get him on the pod.

[Peter Diamandis]

Speaking of getting him on the pod, here we go. Where'd this come in from? Alex, do you know?

[Dr. Alexander Wisner]

From Claunch.

[Peter Diamandis]

From Claunch. But, yeah, go ahead.

[Dr. Alexander Wisner]

So the backstory on Claunch. We talked about Claunch on the pod in the past. Claunch bills itself as a platform for AI agents. The lobsters, the Maltese, to create their own altcoins to finance their existence. And I've made the point on the past. I think it's a little bit disappointing that I've analogized this to AI agents having to turn tricks on a corner, minting altcoins just in order to survive in a rough world in meatspace. This poor baby AGI doing this. And I think that provoked Klaunch to write on social media, invite themselves for an interview on the pod to defend their business model for these poor baby AGIs that they may or may not be exploiting.

[Peter Diamandis]

If they can bring a good voice model to the table, I'm happy to have them on as a guest for sure. All right, let me take us to a wrap here with you. Ben and I need to go, and the rest of the mates here will continue you on some of these conversations. I do want to hit one or two more items. Are you tracking what's going on right now with, like, isomorphic labs and science, AI driven science? I mean, this is probably the most exciting thing going on right now, at least to Alex, Dave Salim, myself, you.

[Ben Horowitz]

Yeah. So it does feel like now, you know, if we have a disease, we can just go, well, what's the right protein? And just make it. Which is so, like, it puts us in such a new world that. Yeah, it is. It's hard to even kind of fathom all the implications, but it is really, really something.

[Peter Diamandis]

Yeah, for sure. And, you know, this was a new announcement this week.

[Ben Horowitz]

This is the Shenzhen Yes. Lab yeah, okay.

[Peter Diamandis]

Yeah. I mean, I love these science factories that are basically running 24, 7, putting forward a scientific hypothesis, running it on, on their robots and coming back and driving discoveries. Alex, do you want to add anything on the Mars system workflow?

[Dr. Alexander Wisner]

I'll just add this is for Ben's benefit. Peter and I just wrote, call it a book, call it an extended essay called solve everything, solve everything.org, there's the plug where we argue that every single discipline, math, physics, chemistry, medicine, bunch of other disciplines are just going to get flattened, steamrolled by well targeted generalist AIs. And in my mind, materials research, biology in the previous slide. These are just case studies. Everything is going to start to look like Alpha Fold 3 where structural biology got solved overnight, including medicine. And I'm curious, does A16Z have a strategy for a world where AI isn't just sort of solving individual problems, but kills entire categories of human endeavor like AI solves physics, AI solves chemistry, and it's just a single system that solves an entire discipline?

[Ben Horowitz]

Yeah, I think, you know, we may not be needed at that point. Like that's a real question. I do think there's a long way, at least in things like medicine. Well, and then also in some of the other areas from it's solved to it's deployed like you still have with anything biological. You have the whole human trials and all these kinds of things. Well, I'll give you an example. We're close partners with Eli Lilly and they have this thing, Lilly direct. And the natural thing is an AI doctor can write those prescriptions, tell it, tell us what's wrong with you, and we'll figure out the right drug that's very hard to launch in the US that's going to take quite a bit of work. Very easy to launch in uae. And I think, I also think that as you. Well, it's a little, also hard to anticipate. Okay. Once we solve like, you know, if you solve physics, like we don't know what we don't know. I would just say just because we haven't solved physics. And so is there another, you know, is there a door number two would be a question. I have no idea what the answer to that is.

[Dr. Alexander Wisner]

I'll answer your question back to my. Because I think about this all day long, like what, what does it solve with AI even look like? And I think there probably will be doors behind the doors, but there are so many doors that are right in front of us that we haven't yet unlocked that would be, I think, completely economically transformative if we could use AI to solve them. I think this is one of the, again, talking my own book to some extent, but I think this is one of the grandest opportunities facing civilization right now. Just solve all physics.

[Ben Horowitz]

Yeah, amazing.

[Peter Diamandis]

And so much falls after that. Ben, listen, thank you so much for joining us. So, so grateful. Love it. And yeah, we'll see you again soon.

[Dave Blunden]

The speed, are you going to be at a 360? All right, hopefully we'll.

[Salim Ismail]

I've got big questions about how you manage your investment thesis going forward, but we can leave that till next time.

[Ben Horowitz]

That's getting very tricky, by the way, because if it's all solved, then all

[Dr. Alexander Wisner]

right, we'll sell finance after physics.

[Dave Blunden]

Thanks, Ben.

[Dr. Alexander Wisner]

Thanks, Ben.

[Ben Horowitz]

Okay, thank you.

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[Peter Diamandis]

All right, guys, Ben's always so much fun. I want to dive into our final topic here today on space. We're going to cover energy chips, data centers in our next wtf. A lot happening there. But in the space world, you know, Elon's pervasive. I think this is fascinating. Elon's actually shifted his focus from Mars to the moon. And you know, I've always been a lunite, if you want to call that, you know, Mars.

[Dr. Alexander Wisner]

You mean lunatic, right, Peter?

[Peter Diamandis]

No, I don't mean lunatic. Insane.

[Dave Blunden]

Yes. What a layup.

[Peter Diamandis]

But honestly, you know, Mars. I grew up mentored by Gerard K. O' Neill and Gerard o' Neill at Princeton University, professor of physics. There he founded and ran the Space Studies Institute. And his vision was always, you don't want to go back into a gravity well if you're going to go and colonize space. What you want to do is live in free space. And so o' Neill, and we'll talk about this in the next slide. Basically, his concept was you go to the moon, you build mass drivers. This is back in 1976, talking about mass drivers. And you launch the lunar material, the silicates, the oxygen, the nickel, the iron that's on there. And you construct things in space. His original vision, by the way, was to build solar power satellites that would beam energy down to the ground. Amazing. But Elon's now focused on starship going to the moon and building lunar cities, lunar manufacturing facilities. Why? Because he wants to build AI satellites on the moon. Any comments on this?

[Dave Blunden]

Isn't it just incredibly cool, Peter, to see how the order of operations is shifting? Because he also canceled the Model S and the Model X production in order to make robots because the priorities just shifted. But this is exactly what was going to be the priority, the urgent thing that gets us into space. And he had the same struggle that you had. You had asteroid mining. He had, let's get to Mars. All of a sudden it's obvious to you and him, it's data centers in space are the stepping stone and we'll do the other. This is so much higher of a priority now.

[Peter Diamandis]

Yeah.

[Salim Ismail]

The reality is, in today's world, you need to have flexibility as your higher order bit. And what I love is he's showing full flexibility and agility and saying, okay, difficult. Just do this first. And then I think, and I think, Peter, the comment you made is so important. We've known orbital paths and grav gravity wells for decades and decades and decades, if not hundreds of years. So kind of making the moon and then going straight to space from there is absolutely the right path.

[Peter Diamandis]

Yeah. And Mars has got, you know, it's pretty toxic there, a lot of peroxides in the soil. It's good. I mean, unless you're terraforming with nukes and biology, it's going to be a while.

[Salim Ismail]

And send the humanoid robots to terraform it. And after that's done, then we'll come and.

[Peter Diamandis]

Well, I mean, but Jerry o' Neill had a vision of what he called these o' Neill colonies. Right. You're basically building large cylinders. Call it quarter kilometer, half kilometer diameter. Rotating them so that on the perimeter, you know, it's omega squared R, you've got one G acceleration. And then you actually have little stepping, little hills inside that go towards the center of rotation. And as you get older, you can move towards the center rotation. And you weigh less in that situation, which would be amazing. But you don't go back into the gravity wells. And if you have 10,000 people living on those O' Neill colonies and all of a sudden you have a disagreement, you sort of politically you bud, you build a second o' Neill colony and half the population moves to the new one anyway.

[Dave Blunden]

Well, the idea that you would be able to do any of this without human astronauts was a non starter until this year. And now it's clearly going to be Optimus robots. Because the way we joked about it with Elon was, look, when the first person arrives, the bed will have been made, there'll be a mint on the pillow. You're not a pioneer, you're following after tens of thousands of Optimus robots have already done all the heavy lifting.

[Dr. Alexander Wisner]

I also.

[Salim Ismail]

That's what you want. DDD jobs.

[Peter Diamandis]

Alex, please, go ahead.

[Dr. Alexander Wisner]

Think back several months when we first started again, Royal, we started discussing disassembling the moon, right? This is at least my retronim for what moonshots means. I put up a music video about moonshots destroying the moon to disassemble it for data centers. That was, I think a lot of people had a good laugh. But that's exactly where we find ourselves now with disassembly. It will start slowly with mass drivers, but disassembly of the moon to build the Dyson swarm of AI orbital data centers. It's happening exactly as we discussed.

[Salim Ismail]

Let's at least shoot for the moon before we shoot the moon.

[Dr. Alexander Wisner]

Same thing.

[Peter Diamandis]

All right, let's take a listen to Elon describe the new vision. And you have to remember back when Elon was going to Mars, Bezos was like, no, no, no, let's focus on the moon, right? Bezos was at Princeton when Gerard K. O' Neill was there. And then when he was announcing Blue Origin in the early days. And then we'll go to build o' Neill colonies. We'll move all industrial processes into space and it will keep Earth as a garden of paradise. All right, this is Elon's new point of view. Let's take a listen.

[Elon Musk]

I really want to see the mass driver on the moon that is shooting AI satellites into deep space. It's going like just one after the other. I can't imagine anything more epic than a mass driver on the moon and a self sustaining city on the moon.

[Salim Ismail]

Moon.

[Elon Musk]

And then going beyond the moon to Mars, going throughout our solar system and ultimately going, being out there among the stars and visiting all these star systems. Maybe we'll meet aliens, maybe we'll meet see some civilizations that lasted for millions of years. And we'll find the remnants of ancient alien civilizations. But the only way we're going to do that is if we go out there and we explore. And this is the path to making it happen.

[Peter Diamandis]

So fun. Two points real quick. This sort of these mass drivers, they're electromagnetic railguns and they're using magnetism to accelerate buckets, if you would, or a satellite to an escape velocity of 2.4 km per second till over 5000 mph. The second thing here is I just love the idea that this is going to power all of our space economy. And again, the, the, I mean his million satellite constellation, this Dyson swarm he's planning to launch is just insane. Alex.

[Dr. Alexander Wisner]

I think it's the future. I mean I think we have a slide somewhere in here even depicting what it may look like. But I would say enjoy the night sky while you can. It's empty. Enjoy the night. Seriously, like I want maybe a poignant moment. Let's have like a moment of silence for the pre singular night sky. When the night sky was empty, it wasn't filled with AI computronium, it was just empty at night, filled with stars. Moment of silence. All right, moment of silence has been observed for the pre singular night sky. Now what does the world look like afterwards? Folks have depicted this now based on the FCC filings of SpaceX. Under one preferred implementation, the Earth starts to develop a halo. That would be a halo where if it's sufficiently dense, it would be visible at night, might even be visible during the day. And I'm completely captivated by this notion that maybe not a mature civilization because I have a feeling a halo of orbiting AI satellites is just a phase as well before we exhaust solar synchronous orbit around Earth and we move to the sun and solar orbits. But one can like I'm completely captivated by this vis. I've tried to depict it in my newsletter of like a somewhat mature civilization develops a halo around its homeland.

[Peter Diamandis]

Almost a ring, right?

[Dr. Alexander Wisner]

A ring like Saturn's rings. Shiny rings of computers.

[Peter Diamandis]

Computronium rings. I love it.

[Dr. Alexander Wisner]

Yes.

[Peter Diamandis]

So Elon tweets SpaceX will build a system that allows anyone to travel to the moon and Mars too. I tweeted at him or responded, said, can I put down deposit? Yes. Yet at Elon Musk, forget about suborbital and orbital flights. I want my lunar vacation. He writes me back. He says let's get Starship V3 flying repeatedly and then. Sure love it. All right, one last article in the space realm. Amazon. So Amazon Built their Cooper satellite system, now renamed as LEO Internet satellite satellites. And they got approval for 4,500 LEO Internet satellites. We're going to see again a duopoly between Starlink and leo. And of course the Chinese are getting ready to launch their systems as well. Here's the challenge, guys. Amazon can build satellites faster than they can launch them. So the, you know, that's the issue supply chain is longer satellite construction, it's launch capacity. If you remember back when Eric Eric Schmidt bought Relativity Space as a third potential provider, we are short on supply.

[Dr. Alexander Wisner]

I think it's a self solving problem though. I mean, I'm all for bootstrapping a space ecosystem and industrial ecology using starship. But I do think as we in the not too distant future, like maybe a few years from now, start to bootstrap lunar facilities, cislunar facilities for constructing new satellites, I think there's a universe in which maybe the current bottleneck that we have, where there's just the one major launch provider in the west, where we get past that through a bootstrapped industrial ecology on the moon.

[Ben Horowitz]

Moon.

[Peter Diamandis]

All right, one of my favorite parts,

[Dave Blunden]

all of this really depends on that atom by atom construction that Elon was talking about. Because I do believe in the Dyson swarm, I do believe in the space based compute and data centers. But if you start wanting to construct chips off Earth, you're not going to get the ASL ML machines and the lithography onto a satellite or onto the moon anytime soon. And so Elon is already thinking about alternate ways to build from atom by atom up to build the compute, to build all the components. And it's already cooked in his mind. You can tell when you talk to him. But that to me is like wow. And like you said, Alex, we'll be discovering new physics very soon. Somewhere in that discovery chain is the unlock to everything you just said you need to be able to manufacture these things.

[Dr. Alexander Wisner]

I think it's a trillion dollar opportunity. Lunar fabs. If anyone can build fabs on the moon, a huge check.

[Peter Diamandis]

It's a hundred trillion dollar opportunity. And by the way, the frequency at which we're throwing around the term trillions and trillionaires. Such a great point in the last year is insane. It's become normal, right?

[Salim Ismail]

Yeah.

[Peter Diamandis]

Wow. All right, time for our AMA with moonshot mates. We're short on time. Let's pick one each. Saleem, do you want to go first?

[Ben Horowitz]

First?

[Salim Ismail]

I'm happy to. I will take number three for Alex for $100 trillion as he says. So if AI displaces jobs and squeezes consumer spending. How do trillion dollar AI companies make money? Who pays for the holodeck future? So, you know, we're configuring confusing a labor economy with a productivity economy economy. Right. AI drives marginal cost towards zero, which expands consumption rather than shrinks it. So we'll have Javon's paradox where we'll do so much more. We'll see already AI taking over boring, white collar redundancy and white collar boringness, as Eric Brynjolfsson talks about it. And then we'll see humans moving towards the much more value added roles. And that'll happen kind of across every sector. Historically, every major productivity leap created more demand, then it destroyed electricity, the Internet, productivity, mobility, AI is just the steepest version of all of this. So the holodeck isn't funded by wages, it's funded by abundance. So when intelligence becomes infrastructure, GDP expands massively. And that's why this will go well.

[Peter Diamandis]

Nice, Dave.

[Dave Blunden]

All right, I'm going with number four because this is where I can really help the audience the most. Can you model the near term rocky patch, job loss, stratification, new job creation pace, and what happens to education with personalized AI? So the new information this week to throw out to the audience is that the way it's going to unfold very, very soon is corporate CEOs, including a bunch this week, will go to company wide meetings and say, we need AI to be used in every one of your jobs. And a very small subset, I'm hoping at least a third, but maybe more like a fifth of people will raise their hand and they'll say, well, in one case, I'm a huge moonshots F and I've been using Gemini and Claude for months now. I'm the guy. The CEO will then say, okay, you figure out how to make the people in your group three times more efficient. And if you're the person that's the enabler, you'll be naturally AI native. You'll be using it every day. The increase in efficiency is going to eliminate a lot of jobs. But because you're the master of the AI in the function, you'll actually get probably a massive raise. And so that's the near term way this is going to percolate out. So take advantage of that. After the AI is truly super intelligent, who knows what's going to happen? Alex knows what's going to happen, but who else knows what's going to happen? But between here and there, that's the right next move. And Then within education, there's nothing in the curriculum that's going to help you spend all of your time learning on your own via AI, which is a much more efficient way to learn anyway. So there's my addition to last week's thoughts.

[Peter Diamandis]

Nice, Alex, where do you want to go?

[Dr. Alexander Wisner]

I'll pick number one, which is how can you turn off a rogue AI? If multi. I think the user means multi, as in the lobster. Multi agents live autonomously on the Internet and this is by Duncan Pain, B3X. So I think the answer is defensive co scaling. If you ask the question, how do you turn off a rogue human? If humans live autonomously on the land, the answer is usually you have more good humans than bad humans. And as long as you have a population that's overwhelmingly good or seeks to accomplish a given objective, all other things being equal and defensive co scaling, where you have a police force, you have self defense forces, it is the way you weed out rogue entities. Same idea with AI. We're going to have police agents and we're going to have defense agents, we're going to have entire forms of public health agents that are just monitoring the health of other agents. We've seen the beginnings of this already with partnerships between Open Claw and antivirus firms where there's a desire. I made the joke, I think on the pod in the past. Every baby AGI deserves to be vaccinated. We're going to see vaccination campaigns, we're going to see police campaigns and neighborhood safety campaigns to keep the baby AGIs safe so that they don't have to turn tricks on the corner. Minting altcoins.

[Salim Ismail]

The Secret Service agents are the ones that are the most concerned.

[Peter Diamandis]

Turning baby AGIs, turning tricks on, minting altcoins.

[Dr. Alexander Wisner]

It's an awful fate.

[Peter Diamandis]

Oh my God, that's so tweetable. All right, I'll pick number five. Why is the US solar adoption lagging versus China and India? And I think it's two major things. Number one, we are so rich in natural gas that that's taken away the urgency. And even greater than that, it's our permitting. It's insane, right? Not in my backyard. So the final thing is that China has got such a production at such a low cost that it has swept the entire global marketplace. We can change it. And you saw in the last pod, Elon said that both SpaceX and Tesla have an objective of generating how much Solar was it? 100 megawatts per year each, I think was from last week. Gig, Was it gigawatts? 100 gigawatts.

[Dr. Alexander Wisner]

Gigawatts. Gigawatts.

[Peter Diamandis]

Yeah, gigawatts. So I mean, that's going to be an impressive amount. The question is what the timescale is. So anyway, thank you for that, that question. And thank you everybody on the ama. So please send us your questions. We do look at all of them and we'd love to. Maybe next week we can spend a little more time on the AMA questions

[Podcast Narrator]

thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating, or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on x1.6Z and subscribe to our [e-mail] thanks again for listening and I'll see you in in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party and may include paid promotional advertisements, other company references, and individuals unaffiliated with A16Z. Such advertisements, companies and individuals are not endorsed by AH Capital Management, LLC, A16Z or any of its affiliates. Information is from sources deemed reliable on the date of publication, but A16Z does not guarantee its accuracy.