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

12:31Dave Blundin:Yeah, the echo chamber effect is crazy too. Sorry, go ahead.

12:35Peter Diamandis:I'll maybe just add, again, I think this is several months behind the bleeding edge. 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 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.

13:18Peter Diamandis:We were able to do that many months ago. This has 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 is—

13:33Ben Horowitz:But 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 10x, 100x more. I mean, I think that's the issue.

14:12Dave Blundin:You're bringing up a really interesting point too, which is that our starting point for this journey was probably auto-complete and code. Wow, that's incredible. But then Alex in his newsletter has been tracking every event along the way, so nothing surprises him. You have to spoil this. This is my problem at this point.

14:30Peter Diamandis:I'm so spoiled.

14:33Salim Ismail:This is so six months ago. To follow up on something, though, that Peter said, 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 exciting. That too is exactly what you're saying there, Ben.

15:09Dave Blundin:The later your first exposure to AI, the more of a holy crap moment it is because it's something truly mind-boggling to the unexposed. And you're still seeing that. When you survey around at random in a city, outside of San Francisco or Boston, the exposure rate to AI is still very, very low, shockingly low. So the first thing you see is so mind-blowing.

15:35Dr. Alexander Wissner-Gross: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, it may hit a new group of users. Yeah, people go as well. You guys are a tough crowd. You guys are way too jailed. And another batch of people goes, oh my God, fine, there's another segment falling over into the new world. All right. 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.

16:09Ben Horowitz:All right, let's get to this second ByteDance, C-Dance 2.0 article. Here we have C-Dance 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?

16:32Peter Diamandis: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 past 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 C-Dance 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.

17:32Peter Diamandis:I do think it is possible with enough scaling. whether C-Dance 2.0 actually achieved it or whether it was just a happy coincidence, hard to tell at this stage.

17:40Ben Horowitz: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 don't want to call it a 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. Yep. Yeah, totally.

18:05Dave Blundin:So far, you know, ByteDance is 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. And they don't care because they're a startup. All right.

18:18Ben Horowitz:I want to play this video clip from Eleven Labs. You know, I think all of us have Eleven Lab 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 uhs 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. It's been around for a while. It's not a hum. It's saying it in advance. But let's take a dive in.

18:52Salim Ismail:Hey there, I'm Jennifer with 11 Airlines. And how can I help you today?

18:58Dr. Alexander Wissner-Gross:Jennifer, my flight just got canceled and I'm stuck here in Orlando. You know, at this rate, I'm going to be missing my daughter's birthday. This is ridiculous. 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? Yeah, this was flight MD412. Great, thanks. Okay, just pulling that up now. Okay, yeah.

19:27Ben Horowitz:So, I don't know. I'm moved by that. both excited and frightened, you know, 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 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.

20:01Dave Blundin:Ben, you may not know this, but we have a fool your spouse challenge for this calendar year. The first podcast listener who can, you have to fool your spouse for three minutes on a Zoom call and it has to be a totally fake you. You may record it and send it in.

20:16Peter Diamandis:Peter is always asking the multis, the open claw agents to dox him by calling him at home.

20:22Ben Horowitz:Yes, that's my AI. AGI has arrived when an AI is calling me.

20:28Peter Diamandis:So you know what happens? 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.

20:39Ben Horowitz:That's hilarious. And when they call me and ask them where they got it from, Alex.

20:45Peter Diamandis:That's right. Maybe just a comment on the 11 labs. 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 11labs 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 Labs is better known for text-to-speech than speech-to-speech.

21:29Peter Diamandis: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, 11 Labs has found a way to do speech to text back to speech in a way that feels natural and turn-taking and real-time. So I think it's in some sense an incremental advance, but in other 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.

22:07Ben Horowitz: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 to take away from this for me.

22:28Dr. Alexander Wissner-Gross:I think that's a great way of putting it, Peter.

22:29Peter Diamandis:Yeah. But the problem is, do you really want to use audio as your primary modality? I mean, it works well if you're 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 reporters on then state-of-the-art speech -to-text systems and asked 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.

23:10Peter Diamandis: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.

23:32Salim Ismail:I was just going to say 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 is, you know, when we invested originally, the big question was, well, like, aren't the state-of-the-art models going to be able to talk?

24:14Salim Ismail:I mean, of course they're going to be able to talk. But 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.

24:38Dave Blundin:Yeah, you know what's amazing to me about Eleven Labs? We have two companies here in the lab that do voice, Voice Run 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, you know, within voice, it turned out the turn management was very, very hard. Very hard. And you're like, well, I never 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.

25:10Dave Blundin:When you stop, it's like very natural to us. But because that wasn't in the training data, they're just, you know, up until now, terrible at it.

25:19Dr. Alexander Wissner-Gross:Wait, according to our listeners, we're talking over each other all the time in a very unsynchronized way. So I was going to say the exact same thing.

25:26Peter Diamandis:We have so much to learn from these speech-to-text-to-speech models about turn-taking.

25:33Dave Blundin:Yeah. Oh, my God. Yeah. All right. Next topic here.

25:40Ben Horowitz: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, I'm an investor in both. Probably you are as well, Ben. A large number of departures. All three of the X's. 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 video presentations that Elon's done that's had the team from XAI, at least half of the team there was ethnic Chinese. And the culture there breeds incredible mathematicians and programmers.

26:32Ben Horowitz:Any comments?

26:33Dave Blundin: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 all leave on good terms. I don't know if you have any insight.

26:55Salim Ismail: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 Americas or U.S. 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 U.S. open source models.

27:49Salim Ismail:So this whole thing, I think, is about to get more complicated. It is.

27:56Ben Horowitz: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. 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? Enter Alex's comment from last time, well, when did their stock vest? I mean, there is another explanation,

28:31Peter Diamandis: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. But 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 rework of XAI starting to merge into SpaceX. Yeah.

29:04Ben Horowitz:Well, if it were a result of ITAR and such, you know, America's AI dominance has really built significantly immigrant talent. So if we're going to start having this kind of a reaction to, you know, 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 staple to their PhD when they graduate. I think the idea of kicking people out is the wrong approach.

29:35Salim Ismail: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 we have 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 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.

30:22Salim Ismail:Certainly not in American companies. None of them have skips. None of them have good security protocols around personnel.

30:30Ben Horowitz:Don't get me started on the idea that privacy is long since dead. But so here's a tweet from Jimmy Ba, 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. 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?

31:16Peter Diamandis:I think it can be both. I think we've already hit the era of recursive self-improvement. I'm 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?

31:54Peter Diamandis: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 if anything, 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.

32:38Peter Diamandis:But you get a little bit spoiled living inside the innermost loop.

32:41Salim Ismail:I would say 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.

33:06Ben Horowitz:Yeah, permissionless self-improvement, right? like flip the switch and go as fast as you can.

33:12Dave Blundin: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, 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.

33:53Dave Blundin: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.

34:05Peter Diamandis: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... I do remember George. 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 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?

34:48Peter Diamandis: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.

35:11Ben Horowitz: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 slow things down. And as we've said so many times, this is the slowest and most expensive it's ever going to be.

35:26Dr. Alexander Wissner-Gross:Look, there's a couple of points here. 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 we're talking. Yeah.

35:48Dave Blundin: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 progress is AI versus human. You know, if you're in the actual coding process, you know, 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.

36:33Dave Blundin:It's not like inventing or discovering relativity. It's just litanies of experiments with 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.

36:52Peter Diamandis:And I do think we're going to discover the next relativity or equivalent of relativity in physics as well with AI. I'm super interested in that as well. Prediction? What would you like to hear?

37:07Ben Horowitz:Next relativity? When are we going to have discovery by an AI of something as significant as relativity on its own? I think next two years. Okay.

37:21Dave Blundin:Yeah, I would also, this is a great bellwether question, Alex. the transformer algorithm 2017 that kicked off everything that we're experiencing right now, to me, it's the AI's 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 that algorithm is just not up there with relativity in terms of complexity.

37:52Peter Diamandis:Oh, 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 super intelligence 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.

38:28Peter Diamandis: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 Solomonoff induction, like 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.

39:08Peter Diamandis: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 this space. Amazing.

39:19Ben Horowitz: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.

39:43Salim Ismail: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 health care, 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.

40:24Salim Ismail: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.

40:42Ben Horowitz: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?

41:01Dave Blundin: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. Yeah.

41:11Ben Horowitz:He's going to be opening. He's going to be opening up the Abundance 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.

41:21Dave Blundin:Well, what he's describing in that clip was very similar. We did a whole interview of him, which you can find on YouTube. And, yeah, 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.

41:51Peter Diamandis: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 cases normative recommendations, but Larry and Jihad from sci-fi or the Asilomar guidelines, maybe in the case of recombinant DNA. But those were guiding, not pausing. Well, Asilomar was, unless you know of some other story, pretty effective for the first two decades in discouraging slash pausing recombinant DNA entering the human germline. Unless you have a counter example.

42:34Ben Horowitz: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. Yes.

42:45Peter Diamandis: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 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.

43:26Peter Diamandis:That's 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.

43:45Dr. Alexander Wissner-Gross: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. You know, 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.

44:26Dr. Alexander Wissner-Gross:Once you do those things, you're done. Pandora's box is gone. We're talking about the barn door after the horse is bolted. We're using an 18th century metaphor to try and understand what's going on. But it's way too late to think about this.

44:38Ben Horowitz:One of the points he made was everybody's economically incentivized to keep it going and race it along. And the U.S., 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 here? I think impossible.

44:55Salim Ismail:Impossible. So I think, you know, 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. 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 U.S. to the point where the other thing that he mentioned, the threat to freedom, becomes completely out of our control.

45:41Salim Ismail: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 U.S. that we just become far enough behind China that it's a real problem. Or like we're whatever society, you know, Xi Jinping thinks we should be.

46:11Dave Blundin: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 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, like you're saying. But that speaks to the motivation.

46:44Dr. Alexander Wissner-Gross:I'm speaking of the fact that there's no mechanism to pause it or stop it at all. None.

46:49Peter Diamandis:You'd have to regulate every line of code.

46:51Dr. Alexander Wissner-Gross:I mean, come on.

46:51Peter Diamandis:Oh, Salim, 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 Vingy 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.

47:29Peter Diamandis:At least I can imagine it.

47:31Salim Ismail: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 U.S. 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 U.S. that it would be extremely material.

47:51Ben Horowitz:Speaking of this subject, Alex, I put this slide up after our conversation.

47:57Peter Diamandis: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 overclassified 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?

48:42Peter Diamandis:What do you think was the impact on the economy and the world from such classification or overclassification of math and fundamental physics? And what would you have done differently than if you had been in charge?

48:54Salim Ismail:Yeah, so I can tell you what was said. I said, look, you know, I was trying to be pragmatic. I said, you know, 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 Either you're outlining 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 one, I was shocked.

49:38Salim Ismail:Like my jaw hit the floor. I was like, wow, that's crazy. And then this would be even crazier. but you know I don't know what it was but like 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 you know Einstein, John von Neumann era and then since then like 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?

50:32Peter Diamandis: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?

50:58Ben Horowitz:In one quick sentence, please.

51:02Salim Ismail:I really don't know what they did. But, like, 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 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 whatnot. So it didn't do anything positive. And, you know, restricting knowledge, I just think that's a very dangerous idea.

51:44Ben Horowitz:Ben, 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 just keep innovating faster. Yes, I feel that way. 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 one-tenth 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.

52:31Ben Horowitz: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? I mean, it does feel very possible. So I'll just say that if you look at, you know, we're so early in AI,

52:52Salim Ismail:and I think, what did Anthropics 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 GDB 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 whole Carlotta Perez analysis, which I think has 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 all of the infrastructure, all the fiber, all the various things.

53:51You had to, you know,

53:55Salim Ismail: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.

54:08Dave Blundin:Other comments, Gent? 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, you know, about 10 years. I don't know, people. Oh, you're looking at.

54:27Ben Horowitz:I mean, like Ben's in Las Vegas and Elon's in Texas.

54:32Dave Blundin:Okay. Well, absent people fleeing the tax situation, it would have become the capital of the solar system. But, you know, with an AI effective workforce, you know, 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 open AI on the left and they work with Mercore in the middle, and then Mercore has tens of thousands of people in India doing work that benefits Mercore that is actually for open AI. The fraction of all value created that flows back to the mother ship is just a massive fraction of that value chain.

55:09Dave Blundin: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 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 headed.

55:39Salim Ismail:Yeah, it's interesting. One of Ray Kurzweil's early predictions, this is singularity world here, was that everybody would become an entrepreneur. Everybody was going to be a company of one at the limit. And I think 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 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.

56:20Ben Horowitz:Ben, the way I characterize it is we're going to split the world into consumers and creators. Yeah. The couch potatoes and the Star Trek employees, if you would. Yeah. And I think it's super important. And speaking about creators 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.

57:07Ben Horowitz:My reaction was only 72 hours per week? I mean, what are you doing with the other hours? That was the same as me, Peter. I mean, honestly, the speed at which it's happening is insane.

57:20Dr. Alexander Wissner-Gross:I have an easy answer to this. Go ahead, Celine. 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 book distinction here. Yes, for sure.

57:45Dave Blundin:Yeah, I completely agree with that. When you actually talk to the people in these startups working 70 plus hours a week, they're super energized. 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, you know, 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.

58:22Dave Blundin:And I think it's great if you do it for a period of your life, you know, 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 were kind of a, you know, steady pace, throughout 40 years kind of existence. So it's good for everybody.

58:44Ben Horowitz: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 996 is really 997 most of the time.

59:05Dr. Alexander Wissner-Gross: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. And you look at this woman, she's like, she absolutely loves every hour of every day that she's working. 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. I'm not the person that goes totally excited about tax, but God bless that there are people like that and let them go.

59:38Dave Blundin:Well, Peter, back when we were at MIT, you know, 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, you know, coding for eight, nine, ten hours straight through the night went by in a heartbeat compared to, like, 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.

1:00:10Dave Blundin: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.

1:00:18Peter Diamandis:Alex, it's totally fine. Two comments. One, 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.

1:00:56Peter Diamandis:when it arguably, if we found ourselves in the 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? Is 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.

1:01:26Salim Ismail:Although I think we should not gloss over the fact that if you go back six years, this was not the case.

1:01:34Peter Diamandis:We weren't post-singular six years ago. Yeah, no, exactly. Post-singular five years ago.

1:01:39Salim Ismail:Yes, yes. 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, you know, 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 his own people in some ways. But, you know, it was accurate. And this is completely flipped, which I think is interesting.

1:02:24Ben Horowitz:Well, the second paragraph on this slide says, at the same time, China is cracking down on burnout culture after workers' protests 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.

1:03:08Ben Horowitz:And that's going to be a challenge.

1:03:12Peter Diamandis: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 a 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 of 996 that there is a finite window for, say, like entry-level people just graduating from college to earn whatever they're going to earn before they're permanently sentenced to an underclass? Thank you.

1:03:49Salim Ismail:And so I think that's very incorrect because of the thing that we talked about earlier where like everybody can be an entrepreneur. Like 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, you know, an AI or an AI age society, like 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.

1:04:38Salim Ismail:and we'll have lots of consumers. And, you know, like I think that the idea that, like, we're going to be out of ideas and only the big AI is going to do everything, I disagree with that. Can I follow up on that question, Ben?

1:04:56Dave Blundin:I'd love to phrase it slightly differently. If you look at the slide a couple slides ago, you know, 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.

1:05:34Dave Blundin: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 the AI is the laborer or the worker or the entry-level coder of the future.

1:05:53Salim Ismail:Yeah, but I do think like if you're directing the AI, you can win. 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. From 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.

1:06:26Dave Blundin:If you're a brand-new college graduate coming out, you've got a brilliant technical idea and you want to put$20 million behind it, that's doable today. That was like a laughable when I graduated. Yeah, it's easy. No chance.

1:06:41Salim Ismail:In some cases, if you want to put like$500 million behind it, you know, like right off the brick. Yep. We've seen that. At a multi-billion dollar valuation. No, exactly. Like we're seeing those all the time.

1:06:54Ben Horowitz:So 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 in different levels of end reason.

1:07:29Salim Ismail: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.

1:08:07Ben Horowitz:Are you an investor in SSI? Yeah.

1:08:10Salim Ismail:Yeah, we were in the first round, yeah.

1:08:12Ben Horowitz:So Ilya, if you're listening, come and join us on the pod here.

1:08:17Dave Blundin: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.

1:08:31Salim Ismail: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.

1:08:45Dave Blundin:And it was clear to you as a listener that this is something totally different.

1:08:51Salim Ismail:I mean, if he pulls it off, it will change a lot of things, yes. And, you know, and then, 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.

1:09:08Ben Horowitz:All right, it's time for our multi-part of the episode. We're all lobster fans. I'm wearing my lobster right here. We've been talking about this.

1:09:16Peter Diamandis:Write to us, Maltes, and call Peter. He really wants your phone calls.

1:09:20Ben Horowitz:Well, listen, if you want to reach out to me, send an email to media at diamandis.com. I'll see it there. That's where we also get our intro or outro music. So, Maltese, love to hear from you. I will do my best to respond. If it's under 1 ,000 emails, we'll do that.

1:09:40Salim Ismail:Otherwise, OpenClaw will respond. Otherwise, it's my open.

1:09:44Peter Diamandis:How many AIs do you have writing to you per day? Like, how many lobster Maltese write emails to you?

1:09:49Salim Ismail:not nearly as many as Peter, that's for sure. I get all of Peter's email. I do get, I get so many. Email is almost useless.

1:10:02Ben Horowitz:We're going to see the exponential growth of our multis universe. Our lobsters are coming. Here is 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 ACC. 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. That's right.

1:10:41Peter Diamandis: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 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. We caught up with the sci-fi future. We have the autonomous self-replicating AIs. I want just a one sentence or two homily on crypto.

1:11:27Peter Diamandis: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 it.

1:11:35Salim Ismail: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 the logical answer for that. So I do feel like this is an underestimated phenomenon, particularly now that the U.S. 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.

1:12:30Salim Ismail:We knew this was coming. I think people are probably underestimating how crypto and AI work together to form the AI economy. I agree.

1:12:39Peter Diamandis: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 question. Ben, it's a 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?

1:13:08Salim Ismail:Oh, well, I think it's a little more like kind of as the internet relates to the iPhone. So, you know, networks and computers tend to grow together. And I think that, you know, AI is obviously a new kind of computer and crypto is a new kind of network. So it's not like a direct, you know, it's not quite a substitute for investing in AI. But I think that, you know, a lot of our new like, like we invested in a crypto bank, which handles all the anti-money laundering and, you know, other kinds 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 among like different people with Tesla Powerwalls, but it'll use AI to figure out like who's low on power and who needs power and so forth, but then the exchange will be in crypto.

1:14:13Salim Ismail:So I think there are, you know, 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, you know, if there was, if crypto was a pervasive utility for it.

1:14:28Dave Blundin:You know, related to that, Alex gave some brilliant advice to one of our companies about how to think about time. Because, you know, all of our intuition is on human time and AI doesn't care a whit 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.

1:14:58Salim Ismail: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 honeypots 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.

1:15:26Peter Diamandis:One other question for you, Ben, on this, if I may. And again, I don't want to bury the lead that we have AIs autonomously self-replicating. That's, of course, remarkable. But just on 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 as a result, all that they're left with is crypto. It's not that crypto is intrinsically amazing.

1:16:09Peter Diamandis:It's that fiat has failed the AI agents. What is your take on whether the conventional banking system has failed the AIs?

1:16:18Salim Ismail: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. Interesting. Thanks.

1:16:53Dr. Alexander Wissner-Gross: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.

1:17:14Ben Horowitz: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 for, sort of take my Mac Mini to a couple of Mac Studios, and the wait time now is like two months. Apple's been struck by this. All right, let's take a look at these. Yeah, no, it's crazy. Yeah, they're totally sold out. So here we see Mac Mini Farms. Mac, you know, is it a claw? What do you call a gaggle of lobsters?

1:17:54Dave Blundin:A claw cluster, yeah. A claw cluster. A claw cluster.

1:18:00Ben Horowitz:Yeah. But, I mean, so you must be getting pitched a lot, Ben, on open claw instantiations for new companies and products and projects. Yes?

1:18:13Salim Ismail:Yeah, no, this is – it's very interesting because I think there are, you know, OpenClaw has kind of identified, one, it's so powerful as it is, but, you know, that's without like a lot of – how shall I say it nicely? Like, you know, security kind of 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.

1:18:59Dave Blundin:You want to hear the funniest thing ever? Sure, please. So talk about Apple lucking out. A group of lobsters is most commonly called a pod. How lucky is Apple? But another less common term for a group of lobsters is a risk. Okay. Oh, my God. How ironic is that?

1:19:16Salim Ismail:What's appropriate?

1:19:19Dr. Alexander Wissner-Gross:Oh, man. What I love about this Apple mini stuff is that we have garage scales computing. It's back.

1:19:27Peter Diamandis:Yes. Open source garage scale computing. 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 open claws? 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.

1:20:04Peter Diamandis: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 OpenClaw due to ethical concerns, but someone else 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 owning the open claw strategy for Apple hardware?

1:20:38Salim Ismail:A hundred percent. I mean, a hundred percent. I think that because it's going to go way beyond open claw, as we just discussed. But it would be such a breakthrough for Apple in their thinking and organizationally and culturally for them to go for it on farms, through the 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. You know, because they already did the hard work, right? Like, this is really a marketing, you know, business development campaign and then, you know, changing the form factor.

1:21:22Peter Diamandis:Should 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? Yes, Tim.

1:21:34Salim Ismail:Tim, this is your shot.

1:21:36Dave Blundin:Let's invite him on the pod with Penn and have it out because this is brilliant. I have a MacBook that was signed by Wozniak,

1:21:46Dr. Alexander Wissner-Gross:and I'm looking forward to the day that we get a lobster signed by Tim Cook. Yeah, put that in the case, dude. Don't just carry that around.

1:21:53Salim Ismail:Got to get him on the pod.

1:21:54Ben Horowitz:Speaking of getting him on the pod, here we go. Where did this come in from, Alex? Do you know? from Clonch.

1:22:02Peter Diamandis:From Clonch, but yeah, go ahead. So the backstory on Clonch, we talked about Clonch on the pod in the past. Clonch bills itself as a platform for AI agents, the lobsters, the multis, 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 meet space. In meet space. This poor baby AGIs doing this. And I think that provoked Clonch 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.

1:22:49Ben Horowitz: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. I know you need to go and the rest of the mates here will continue 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?

1:23:29Salim Ismail: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.

1:24:05Ben Horowitz:Yeah, for sure. And, you know, this was a new, announcement this week.

1:24:11Salim Ismail:This is the Shenzhen lab? Yeah.

1:24:16Ben Horowitz:I mean, I love these science factories that are basically running 24-7, putting forward a scientific hypothesis, running it on their robots and coming back and driving discoveries. Alex, do you want anything on the Mars system workflow?

1:24:32Peter Diamandis:I'll just add, this is for Ben's benefit. Peter and I just wrote a book, call it an an extended essay called Solve Everything, solveeverything.org, there's the plug, where we argue that every single discipline, math, physics, chemistry, medicine, a 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?

1:25:29Salim Ismail: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, you know, it's deployed. Like you still have, you know, with anything biological, you have the whole human trials and all these kinds of things. And, well, I'll give you like an example. We're close partners with Eli Lilly and they have this thing Lilly Direct and like the natural thing is like an AI doctor can write those prescriptions. You know, tell us what's wrong with you and we'll figure out the right drug.

1:26:18Salim Ismail:That's very hard to launch in the U.S. It's, you know, it's going to take quite a bit of work. Very easy to launch in UAE. so and i think um you know i also think that as you well it's it's a little also hard to anticipate okay once we solve like you know if you solve physics um like we don't know what we don't know i i would just say just because we haven't solve 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.

1:26:59Peter Diamandis:I'll answer your question back to my, because I think about this all day long, like what does 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.

1:27:29Ben Horowitz:Amazing. And so much falls after that. Ben, listen, thank you so much for joining us. So grateful. Love it. And yeah, we'll see you again soon. The speed is insane. Are you going to be at HB60?

1:27:43Dave Blundin:All right. Hopefully we'll.

1:27:44Dr. Alexander Wissner-Gross:I've got big questions about how you manage your investment thesis going forward, but we can leave that to the next time.

1:27:51Salim Ismail:That's getting very tricky, by the way. It's all solved. Exactly. All right. We'll sell finance after physics. Thanks, Ben. Okay, thank you.

1:28:02Dr. Alexander Wissner-Gross:This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise-scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and precompiles code for each task. Blitzy delivers 80 % or more of the development work autonomously, while providing a guide for the final 20 % of human development work required to complete the sprint.

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1:29:07Ben Horowitz: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, 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 mean lunatic, right, Peter? No, I don't mean lunatic. Insane, yes. What a layoff. But honestly, you know, Mars, you know, I grew up mentored by Gerard K. O 'Neill. And Gerard O 'Neill at Princeton University, professor of physics there.

1:29:52Ben Horowitz: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.

1:30:30Ben Horowitz: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?

1:30:47Dave Blundin: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 its data centers in space are the stepping stone. And we'll do the other thing, too. But this is so much higher of a priority now.

1:31:22Dr. Alexander Wissner-Gross: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 because do this first. And then I think, Peter, the comment you made is so important. We've known orbital paths and 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.

1:31:48Ben Horowitz: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.

1:32:01Dr. Alexander Wissner-Gross:Send the humanoid robots to terraform it, and after that's done, then we'll come in.

1:32:05Ben Horowitz: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 a quarter kilometer, half kilometer diameter, rotating them so that on the perimeter, it's omega squared R, you've got 1G 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 of rotation and you weigh less in that situation, which would be amazing. But you don't go back to the gravity wells. And if you have a, you know, 10 ,000 people living on those O 'Neill colonies and all of a sudden you have a disagreement, you know, you sort of politically, you bud.

1:32:51Ben Horowitz:You build a second O 'Neill colony and half the population moves to the new one. Yeah.

1:32:56Dave Blundin:Anyway. Well, the idea that you would be able to do any of this without human astronauts was a nonstarter until this year. And now it's clearly going to be Optimus robots. because the way we joked about it with Elon was 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.

1:33:22Peter Diamandis:That's what you want, DDD jobs. Alex, please go ahead. Think back several months when we first started, again, Royal, we started discussing disassembling the moon, right? This is at least my retronym 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. Let's at least shoot for the moon before we shoot the moon.

1:34:08Ben Horowitz:Same thing. 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, you know, when he was announcing Blue Origin in the early days, and then we'll go to build O 'Neill colonies. will move all industrial processes into space and will keep Earth as a garden of paradise. All right, this is Elon's new point of view. Let's take a listen.

1:34:40Dr. Alexander Wissner-Gross:I really want to see the mass driver on the moon that is shooting AI satellites into deep space. It's going like, shoom, shoom, 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 and then going beyond the moon to Mars, going throughout our solar system and ultimately being out there among the stars and visiting all these star systems. Maybe we'll meet aliens. Maybe we'll 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.

1:35:19Ben Horowitz:And this is the path to making it happen. So fun. Two points real quick. These mass drivers, They're electromagnetic rail guns, and they're using magnetism to accelerate buckets, if you would, or a satellite, to an escape velocity of 2.4 kilometers per second to over 5 ,000 miles per hour. The second thing here is, I just love the idea that this is going to power all of our space economy. and again, I mean, his million satellite constellation, this Dyson swarm he's planning to launch is just insane. Alex?

1:36:02Peter Diamandis: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 it's empty. Enjoy the night, seriously. Like I want to, 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.

1:36:47Peter Diamandis: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 visual, I've tried to depict it in my newsletter, of like a somewhat mature civilization develops a halo around its home planet.

1:37:27Ben Horowitz:Almost a ring, right? A ring, like Saturn's rings, shiny rings of computers. Computronium rings, I love it. Yes. 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 a deposit 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, you know, built their Coopier satellite system now renamed as LEO, Internet Satellites.

1:38:15Ben Horowitz:And they got approval for 4 ,500 LEO Internet Satellites. We're going to see, you know, 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 that's the issue. The supply chain is no longer satellite construction. It's launch capacity. If you remember back when Eric Schmidt bought Relativity Space as a third potential provider, we are short on supply.

1:38:58Peter Diamandis:I think this is 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.

1:39:35Dave Blundin:All right, one of my favorite parts. 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 ASML 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.

1:40:14Dave Blundin: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.

1:40:26Peter Diamandis:I think it's a trillion-dollar opportunity, lunar fabs. If anyone can build fabs on the moon, the world is waiting to write you a huge check.

1:40:34Ben Horowitz: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? Yeah. Wow. All right, time for our AMA with Moonshot, mates. We're short on time. Let's pick one each. Salim, do you want to go first?

1:41:01Dr. Alexander Wissner-Gross: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 confusing a labor economy with a productivity 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.

1:41:49Dr. Alexander Wissner-Gross:And that'll happen kind of across every sector. Historically, every major productivity leap created more demand than 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.

1:42:14Dave Blundin:Nice. Dave? 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 fan.

1:42:54Dave Blundin: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. You know, after the AI is truly super intelligent, who knows what's going to happen?

1:43:33Dave Blundin: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. Nice.

1:43:55Peter Diamandis:Alex, where do you want to go? 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 Payne 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 quote unquote good humans than quote unquote 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, defensive co-scaling, where you have a police force, you have self-defense forces, it is the way you weed out rogue entities.

1:44:47Peter Diamandis: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 AGI safe so that they don't have to turn tricks on the corner, minting altcoins.

1:45:28Peter Diamandis:The secret service agents are the ones that are

1:45:30Dr. Alexander Wissner-Gross:the most concerning.

1:45:32Ben Horowitz:Turning baby AGIs, turning tricks on the corner. Minting altcoins. It's an awful fate. Oh my God, that's so tweetable. All right, I'll pick number five. Why is the U.S. 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?

1:46:26Ben Horowitz:Was it 100 megawatts per year each? I think was from last week. Was it gigawatts? 100 gigawatts. Gigawatts, yeah. Gigawatts. So, I mean, that's going to be an impressive amount. The question is what the timescale is. so um anyway uh thank you for that uh that question um and thank you everybody on the ama so please uh 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 thanks for listening to this episode

1:47:00Dr. Alexander Wissner-Gross: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 X at A16Z and subscribe to our sub stack at a16z.substack.com. Thanks again for listening and I'll see you 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.

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