a large number of departures from XAI uh from the founding team. >> 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 the answer to that question. I I will say that it’s um >> recursive self-improvement 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, >> we’re obviously going into a new world like with the uh industrial revolution. And I think it’s scary at times to think about. >> 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. >> 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 posit. >> When are we going to have discovery by an AI of something as significant as relativity on its own? I don’t think it’s the next 12 months. I I think it’s
[00:01:01] >> Now that’s a moonshot, ladies and gentlemen. >> 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, uh the amazing Ben Haritz of Andre and Harwitz. Ben, uh where are you today? Uh I am in Las Vegas today actually. It is my wife’s uh 60th birthday weekend super celebration. So >> Oh, happy. >> Oh, you get to merge that with Valentine’s Day. >> Yeah. Yeah. Yeah. Yeah. Yeah. >> You get to say >> which is good. Good news. Bad news. >> Uh well, >> last time I was in Vegas, we can cut this from the pod if we if we need to, but last time I was in Vegas, I uh I told my mom, “Hey, I’m in Vegas.” She’s in her mid 80s and she said, “Oh, you’re in Vegas? Did you shoot your wad? And I was like, “Is that a phrase?” And she’s like, “What do you mean? I mean, did you lose all your money?” >> Yeah, I’m glad she clarified that.
[00:02:01] >> Thank you for clarifying, Mom. >> Yeah, that would have been a very aggressive question from your mom otherwise. >> Oh, >> yeah. That didn’t that didn’t stand the test of time, that particular phrase. >> Well, 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. Uh, and it is an insane week. We’ve actually recorded two podcasts this week just because the speed is over the top. >> Um, and we’re going to be recording again another four days. I mean, Ben, it’s it’s it’s like >> it’s good. My goodness. Right. Thank god my AI avatar is getting really good. >> Um, >> yeah. >> Uh, let’s open up with top stories uh in voices video XAI multis. Um, all right. First one. Um, here we go. We’re starting to see a little bit of doomer conversations coming. AI disruption will soon hit sooner than most expect. Uh,
[00:03:01] this is something that’s been making the rounds for Matt Schumer, CEO of Other Side AI. Ben, have you seen this article? >> Yeah. Yeah, of course. >> Yeah, of course. >> Yeah. >> Thoughts? So, I mean, is it is this what we already know? I mean, we’re about to hit recursive self-improvement. Uh once that hits, all of our curves go out the window. Everything accelerates. Everything we’ve been preparing for is being redefined on you time scales. Um what do you think of it? >> I I look I think it’s um I think the AI timeline is somewhat unpredictable but kind of certainly more predictable than what he’s talking about which is societal change. Um yeah, >> I think that you know it tends I would be like very surprised just in in seeing how even companies in Silicon Valley have changed
[00:04:00] so far if companies like outside of that sphere you know just completely change everything they did uh in one to five years like I think that’s a little aggressive for societal change um you know Look, we’re obviously going into a new world. Uh, and you know, like with the, uh, industrial revolution, I think it’s scary at times to think about, but, um, 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 uh than negative change at a much more rapid rate. So I don’t know like like I thought it was a little aggressive. >> I mean 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 or Alex. I I think it I I think it really has to do
[00:05:03] with uh Open Claw and um you know kind of the new coding models. So people in Silicon Valley are talking about uh AI differently since then because it is kind of different. Uh and I think that that that’s a trigger for this one being so viral. >> 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, Open Claw, 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 right in front of you. But also the flavor of this roll out has changed a lot in my mind recently because, you know, this was board meeting week for me. you know, three backto-back mega board meetings, 1100 people affected. And uh 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
[00:06:02] 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. You’re 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, you know, a two-thirds reduction in headcount to get the same job done. So it effectively is a huge amount of displacement because, you know, big big banks, insurance companies are not going to triple their size in the time frame where it has. >> I also think they’re not going to 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 uh we’ll see. But we’ll see. We’ll see. >> I have a couple of thoughts about that article. >> Yeah, please go ahead. >> Uh one, I thought it was like a summary of the podcast for the last eight months. That’s all we’ve been talking
[00:07:00] about is stuff’s going to change. It seemed uh a little um uh dramatic as as Ben put it. Um and I don’t agree with the timelines. Um but definitely there’s something coming. I think it’s just a qu the reason it’s making the rounds. It’s just got the zeitgeist of 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. >> By the way, it’s also like super well written, like a really compelling >> written AI. Yeah. Yeah. Yeah. I I I I’ll chime in here and just say uh while I enjoy writing about the singularity in general, obviously I’m doing it almost every day at this point, I I found it completely unremarkable. Maybe I’m just too too deep in the weeds of writing about more pressing advances every day. But the the sort of style where you talk uh 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
[00:08:01] is a relatable touch point for a lot of people like something big is about to happen. Let let’s be really millennialist. Uh 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 5 minutes of your life. It it’s a natural viral moment, but I don’t think the information value was especially high compared to other sources. >> I agree completely. >> Exactly what I said, except Alex said it more eloquently. >> Yeah. >> Hey everybody, you may not know this, but I’ve done an incredible research team and every week myself, my research team study the meta trends that are impacting the world. Topics like computation, sensors, networks, AI, robotics, 3D printing, synthetic biology. And these Metatrend reports I put out once a week enable you to see the future 10 years ahead of anybody else. If you’d like to get access to the Metatrends newsletter every week, go to dmandis.com/tatrens. That’s diamandis.com/metatrends. We have a couple of articles here on Cance uh 2.0 out of Biteance. Um
[00:09:04] that thing good. >> Oh my god, it’s amazing. Uh it’s, you know, it’s going to change everything. Let me let me play this particular video first. Uh the response here is you know and you’ve said this before, Alex, Hollywood is cooked. All right. So, this is a uh a video clip uh with a oneline prompt. Uh let’s take a look at it. Oh my god. Just check it out. So, you know, Tom uh and Brad fighting karate on a rooftop and and it generates what? 10-second clips right now. Alex, what are your thoughts? I I I think at the risk of of sounding again hoham unremarkable, we saw
[00:10:01] copyright infringement at the scale already with 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 I’ve seen remarkable advances in video models. I I tend to think that people are so easily aed by video models that that are able to show celebrity faces and scenes that they recognize that uh that maybe they overindex on the underlying quality of of the models. I think world models that are interactive in real time are are profoundly more interesting than video models. I I think this is just 10 different copyright infringement lawsuits waiting to happen. But I still was wowed. I’m still one of those people that said, >> “Yeah.” Yeah, that was very >> That was amazing. >> Um, so I I would say on this one, um,
[00:11:02] the two the two videos that that I watched that were like like where the entertainment quality was so high were one that that Kanye uh doing his song in Chinese um was so good that video like I watched it three times. um was that entertaining. And then the other one was the Waffle House one. And they’re both kind of uh I would just say representative almost of a a new medium. It’s not like okay, this is film um generated by AI. It’s like no, this is a whole another thing uh that we’ve never seen before. So I I I think this model is um at least for me personally as a consumer was was a was an impressive step up. I’ll just >> I think YouTube YouTube wins in this model, right? >> Because everybody’s going to be producing so much content and it’s going to become resonant on YouTube. It’s not
[00:12:00] going to a lot of it may not go to the theaters or television and so forth. >> Yeah. Dave, you want to say? >> Yeah, I was going to say the same thing. Like Tik Tok also is the big winner. When you 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, you know, when 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 as better than a movie. If you can push the production cost 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. >> Yeah. I mean, the the elephant in the room here though is, you know, this 2K quality multi-seene video. It just it doesn’t just threaten Hollywood. Uh it it threatens the whole concept of video as evidence, right? Court testimonies, journalism, political campaigns.
[00:13:01] >> Um I mean Well, and also that’s going to be real time, right? Like, so then yes, just the any kind of security mechanic that you have where you recognize the person via video or or voice is shot to hell. >> Yeah. >> Yeah. The echo chamber effect is crazy, too. >> Yeah. >> I’ll maybe just add again. I I think this is several months behind the bleeding edge that I I think video models have been approximately this good. Yeah, sure. You can upscale it. You can increase the 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 where I think the frontier actually lies in being able to 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 costeffective speed. And I I think again I I want to avoid overindexing on just video models
[00:14:01] that produce two Hollywood celebrities fighting each other on a rooftop. We 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. >> But Alex, I don’t think that’s the point. I think the point is this is making it out into the you know ecosystem of common users. I think it’s the notion that um yes it’s the cutting edge and yes it was possible but now it’s something that um is going to is going to grow in its utility and its its uh uh you know its consumer base. And then all of a sudden uh you know we’ve had you know basically uh democratization of of film production for some time but it’s now going 10x 100x more. Um I mean I I think it’s I think that’s the issue. >> You’re bringing up a really interesting
[00:15:01] point too which is that you know our our starting point for this journey was probably autocomp complete and code you know and like wow that’s incredible. Uh but then you know Alex in his newsletter has been tracking every event along the way so nothing surprises him. >> Yeah. I’m just spoiled my problem at this point. I’m so spoiled. >> Um >> so 6 months ago but if you think about it >> on 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 oneline prompt and produce something entertaining. um isn’t something that we were at least I hadn’t seen at this level of entertainment. Um, so I think from a consumer product standpoint as opposed to a technological standpoint, which I agree on, um, it’s kind of exciting. >> That too is exactly what you’re saying there, Ben. Like if the later your first exposure to AI,
[00:16:00] >> 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. >> The first thing you see is so mind-blowing. >> Yeah. For me, this was hohham 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. Yeah. people go and another batch of people no but another batch of people goes oh my god fine there’s another segment falling over into the 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 >> all right let’s get to this second uh by dance cance 2.0 article um here we have
[00:17:04] seance 2.0 was paused by Bite Dance after it was found to recreate real voices from just facial photos. Uh, I find that almost impossible just from a facial photo. Alex, what did you learn about this? 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 their whole genome into Claude and being able to to generate faximiles of their face that resemble the real thing. I 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 the foundational technology behind seedance 2.0, I I do think it is conceivable that if
[00:18:01] 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 I do think it is possible with enough scaling. Whether Cance 2.0 actually achieved it or whether it was just a happy coincidence. Hard to tell at this stage. >> What’s interesting though is that they voluntarily stopped it, right? They voluntarily shut it down. Uh which is a great you sort of uh 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. >> Yep. >> Um Yeah. >> Yeah. Totally. So, so far, you know, bite dance 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
[00:19:00] again right after, you know, they don’t care because they’re a startup. >> All right, I want to play this video clip from 11 Labs. Um, you know, I think all of us have 11 Lab voices that we use for different projects and so forth, but I was just blown away by this. And it’s it’s the humanlike quality, the the cadence, uh the hums and the h that come out of this. So, let’s take a listen and uh and discuss it cuz this is a game changer for me. I know what you’re going to say, Alex. This has been around for a while. Not >> saying it in advance. >> But let’s take a let’s take a dive in. >> Hey there, I’m Jennifer with 11 Airlines. And how can I help you today, >> Jennifer? My flight just got cancelled and I’m stuck here in Orlando. 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.
[00:20:00] Um, could you please tell me which flight this was? >> Yeah, this is flight MD412. >> Great. Thanks. Okay, just pulling that up now. Okay. Yeah. >> So, I don’t know. I’m moved by that. Um both excited and frightened uh in a in a way that is, you know, again, we’re 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 uh that you don’t expect, you may be talking to an AI. So >> 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 has to be a totally fake you
[00:21:01] >> may or may not have to record it and send it in. Peter is is always asking the the multis the open claw agents to dox him by calling him at home. >> Yes, that’s my that’s my AI AGI has arrived when an AI is calling me on. >> So, you know what happens? They end up emailing me. I I get several emails probably per day at this point from openclaw agents asking me what Peter’s number is. >> That’s hilarious. Uh, and when they call me and ask them where they got it from, Alex, >> that’s right. May maybe maybe just a comment on the 11 Labs. So, if you’ve been using the version 3 v3 alpha model from 11 Labs, this should hardly be surprising. V3 enables you if you use text to speech in uh the 11 Labs platform to specify with brackets emotional expressions and this has been around for for many months. What’s somewhat interesting here to me at least is we’ve known how to do audio to audio
[00:22:02] 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. 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 to 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 that feels natural and turntaking and real time. So 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 to mine and analyze in the loop, it probably is a material advance. >> Yeah, Alex, I would say we’ve crossed the uncanny valley on voice at this point with with this demonstration. And
[00:23:01] 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 are really an important takeaway from this for me. >> I think that’s a great way of putting it, Peter. >> Yeah. >> But the problem is, do you really want to use audio as your primary modality? I mean, it it works well in isolation. >> Okay. Yeah, you want BCI. I I want a BCI too and I want wearables and I I want gestural interfaces. I want it all. for for most people. I mean, is it New York, this is sort of famous anecdote, New York Times uh in the 1980s did a famous study where they just put all of their their reporters on then state-of-the-art speechto 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 when if you’re just typing. If you’re speaking, you’re you’re leveraging, right, similar
[00:24:01] portions of uh of the brain. So, I’m not 100% sold yet that speech is the modality of the future. I 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. M >> one thing Alex 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 uh or at least in my experience um is the mode of choice uh >> for sure >> the other thing I’d say about 11 Labs and kind of quick disclaimer that uh 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 uh shocking things to me about 11 Labs was, you know, when we in invested originally, the big question was, well, like aren’t the, you know, state-of-the-art models going to be able
[00:25:00] to talk? I mean, like, of course they’re going to be able to talk. Um but you know speaking correctly with the right nuance and building the right products for developers and so forth has proven to be um very sustainable for them. Uh which uh I I think is interesting as you look at the entire landscape the difference between the capability and the product uh is significant. >> Yeah. You know what’s amazing to me about 11 Labs? We we have two companies here in the lab that do voice run and vocara. And what’s amazing is you 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 and you’re like what 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. You know, 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
[00:26:01] training data, they they’re just, you know, up until now terrible at it. >> Huh. Wait. According to our listeners, we’re talking over each other all the time in a very unsynchronized way. So the exact same thing as like we have so much to learn from these speech to text to speech models, not turn taking. >> Yeah. Oh my god. >> All right. >> Yeah. All right. >> Next topic here. If you guys are okay with it, I’ll move us along. So, uh, just following the merger of SpaceX and XAI and in the spirit of full disclosure, I’m an investor in both. Probably probably you are as well, Ben. Um, a large number of departures, >> all three all three of the X’s. >> Yes. uh a large number of departures from XAI uh from the founding team mostly ethnical ethnic Chinese co-founders and it’s likely due to the ITAR regulations of SpaceX right um and it was
[00:27:02] interesting on a few a few uh video presentations that Elon’s done that’s had the team from XAI at least half of the team there was ethnic Chinese um and you know the culture there breeds incredible mathematicians and and programmers. Any any comments? >> 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. Uh 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. >> Yeah, I I don’t know the answer to that question. I I will say that it’s um so in a related matter uh we like recently heard from a few Chinese nationals who are uh PhD students that um the Chinese
[00:28:01] government is cracking down on the uh the Americas or US academia’s use of Chinese open source models like they uh particularly uh post the Meta Manis 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 uh kind of work is based on the Chinese models 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. >> It is. I mean, if if you read these tweets, >> if you read these tweets, um, Mr. uh, Woo and, uh, Mr. Bob both are super enthusiastic about XAI. They’re not leaving with any kind of angst. Um, you know, they’re saying that they love the XAI family. We’re heading towards an age
[00:29:01] 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? Um, you know, enter Alex’s comment from last time. Well, when did their vest their stock vest? >> I mean, there is 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 I’ll also point out that XAI was selling foundation model services to the Department of War prior to this merger. So I I would again query whether some sort of uh nationality concern was 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. >> Yeah. Well, if it were a result of ITAR and such, you know, there America’s AI dominance is really built significantly
[00:30:00] immigrant talent. Uh so uh if we’re going to start having this kind of a reaction to uh you know PhD immigrants, I mean I personally think and I’m 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. Um I think the idea of, you know, kicking people out is the wrong approach. >> Yeah, I I think in generally that’s in general that’s correct. I do think that um there there’s I I don’t think we’ve quite thought through the case of China totally um in that look 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 I would say there is no risk to that idea um I guess I would just say that but Right. >> I think being open I I think you’re right, General. I think we should be open. We should uh accept the phenomenal
[00:31:02] talent that comes over here and not not fight it because we 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 skiffs. None of them have good security protocols around personnel. >> Don’t get me started on on the idea that privacy is long since dead. But so here’s correct. >> Here’s a tweet uh from Jimmy Ba, a co-founder at XAI. Uh 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 um you’re going to hear this a few times >> go off. Th this is I mean you’re going to hear this a few times that you know these next few years are a massive inflection point that everything changes and we’re going to look back uh thousands of years in the future back to this this you know inflection point or
[00:32:00] is it just a smooth singularity? Alex >> I I think it can be both. I I think we’ve already hit the era of recursive self-improvement. I’m banging the the table rhetorically every episode and and every day in my newsletter talking about recursive self-improvement. We’re there. All of the Frontier Labs are are using their own models at this point to develop their models. That’s practically the definition of recursive self-improvement at at this point in practice. I I don’t think it’s the next 12 months. I I think it’s it’s now. And is 2026 going to be insane relative to years past if if you just sort of skip over all of the interim time? Absolutely. Is it already insane in some sense? Absolutely. Uh even if we just look at the events of the past 24 hours, some of which I 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
[00:33:01] months. That’s the past 24 hours. So I think >> Yeah. That’s that’s like past 24 hours. So I think Jimmy is underelling if if anything what craziness looks like. At the same time locally, spaceime is smooth and you you need to look no further than my saying hoham 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 I 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 I think is an accelerant. Um you know, TBD, how much of an accelerant? But but I think that could be very different. >> Yeah. permissionless uh self-improvement, right? Like flip the switch and go as fast as you can. >> Well, also there’s a distinction, this
[00:34:02] came up at the EverQo board meeting yesterday, but the 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 knowhow 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, which case we’ve already hit the flash point and now we’re just talking about the rate at which it percolates across. But Ben, I agree that that his comment is about the actual core algorithm development. the next ideas are 100% from AI and and then they go into production. You know, >> I I I also think human outside the loop, on the loop, in the loop is is in some sense a pretty blurry or slippery slope.
[00:35:00] If you remember George Jetson from the Jetsons, George the the cartoon >> 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 I think that’s like that is a good metaphor for the state of recursive self-improvement at 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 uh running opus 4.6 with agent teams. But really it is recursive. I I would argue it is recursive self-improvement even if we’re pretending we’re in the loop by pressing the George Jetson button. >> Exactly what I’m doing on Telegram right
[00:36:01] now with my with Skippy. Yes, go on to the next stage. Uh I don’t want to be I don’t want to slow things down. Uh, and as we’ve said so many times, this is the slowest and most expensive it’s ever going to be. >> Look, this a couple of points here. One is it’s it’s 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. Um, we’re exiting the industrial age permanently as as we’re talking. So >> yeah, I really think the 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 uh contributing, but it’s it’s really ambiguous what part of the of the progress is AI versus human. Uh you know, if you’re in the 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
[00:37:01] other thing and I kind of adopted it and now it’s it’s not clear whether it was my idea or not. But we’re in that mode right now where the 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 you know neural topology worked better. It’s not it’s not like inventing rel you’re discovering relativity, you know, it’s just lit 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 it’s really very likely that we’re well down that path. >> And I also add I I do think we’re going to discover the next relativity or equivalent of relativity in physics as well with AI. I I I’m predicting >> super interested in that as well. >> Prediction. >> What would you like to hear? >> Next relativity. >> What when are we going to have discovery by an AI of something as significant as
[00:38:03] relativity on its own? >> I think next two years. >> Okay. >> Yeah. I I would also This is a great bellweather Alex question, Alex. the 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 6 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 >> algorithm is just not >> it’s not up there with relativity in terms of complexity. Well, I mean I 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 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
[00:39:00] experiments is a basian super intelligence. So if you had like a video of this would be Newtonian gravity, not special relativity, but you you could imagine taking a super intelligence making it watch a video of an apple falling from a tree. And the 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 be of explaining the universe. and with a few more frames it somewhere in its distribution and and this there’s a whole class of information theory uh devoted to what’s called Solomongh 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 super intelligence discover any new laws of physics discover transformative inventions for uh for disclosure purposes Since we’re playing the disclosure game, I have a portfolio
[00:40:00] company, physical super intelligence, that’s working on these issues as well. I’m very bullish on the space. >> Amazing. I want to move us to a conversation that Eric Schmidt uh 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? Um the answer quite clearly by almost everybody today is no. Um we had that conversation. Dave, you and I with Elon. Let’s take a listen to what Eric has to say. >> 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 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. Uh it can be
[00:41:01] used in war. Um 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 nonhuman intelligence arrived and it was a competitor to us. >> Amazing, right? We hold two futures in superp position, 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. Uh Dave, you were going to say, >> “Oh, Alex and I were there in the dome.” You know, that was our our Davos dome where he was speaking >> and it just blows my mind how he owns a room. The the guy is so articulate. >> Yeah. >> Well, he’s going to be opening he’s
[00:42:00] 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 uh with him on stage, so that’ll be fun. >> Well, what he’s describing in that in that clip was uh very similar. We did a whole interview of him, which you can find on YouTube. Um and uh yeah, he’s he 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 and help point it toward good, but picketing with a 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. >> No worries. I I would take the position I 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 in realistic prognostications in some case normative recommendations uh but larry and jihad from sci-fi or or thear
[00:43:00] guidelines maybe in the case of recombinant DNA we >> but those were those were guiding not not pausing >> wellar was unless you you know of some other story pretty effective for the first two decades in discouraging slashpausing recombinant DNA a entering the human germ line unless you have a counter >> example. It was it was the it was just the the the five uh you know P1 through P5 labs in terms of sec safety and self-regulation. Yeah, we did p we did pause human germline editing for sure. >> Yes. So, so we are capable of pausing a technology if there’s a desire to. I just think in in the case of AI there isn’t and arguably shouldn’t be a desire to pause it. I I 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 I think Nick Bostonramm, who also in the past 24 or 48 hours put out a a wonderful essay that I’d recommend everyone read called
[00:44:00] Optimal Timing for Super Intelligence, argues that AI can and should be paused, but only once we’re on the verge of super intelligence. How how he defines it, not how I define it. I think it’s already here. That’s sort of like station keeping. You you want to get into the harbor, I think is his analogy, as quickly as possible. But when once you’re about to approach approach the dock, I’m I’m mangling his metaphor a bit. You slow down a bit. You pause as you’re about to dock. I I think that sort of concept I think makes much more sense than some sort of techmarkian six-month pause. >> Uh I’m sorry. I’d like to throw in a couple of things here. Um I I find this is another hoham thing. Yeah, Eric is fabulously articulate, but we’ve been saying this for months on this a 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 uh model people are going to do stuff with it. We have a global prisoners dilemma um model going on here the the
[00:45:01] whole thing is going to scale now no matter what we do. Um, you know, OpenAI did two things that that 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 horse is bolted. We’re using an 18th century metaphor to try and understand what’s going to think about this. >> 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? >> Impossible. Impossible. >> So, I think, you know, I look at this question through the geopolitical lens, which is um you know, clearly I 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
[00:46:02] well. where we would actually stop the technology. Like I I do agree that it’s impractical. I think that there is a real danger um and we faced it probably more in the Biden administration than in this one. uh but it’s still like a potential movement that we really slow 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 uh 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 down enough in the US that uh we just become far enough behind China that it’s a real problem or like we’re whatever society you know that Xi Jinping thinks we should be. >> Yeah, completely agree. I think you know
[00:47:00] 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 allout arms race with China uh 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 don’t hypothesize something that is just never going to happen. But it was all geopolitical. >> Speaks to the motivation. I’m speaking of the fact that there’s no mechanism to posit or stop it at all. None. You’d have to regulate every line of code. I mean, come on. >> Oh, Seem, there are ways to do it. I I I think uh not being able to think of it speaks well of of your character. You have to imagine a completely pathological society. Verer Vinci 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
[00:48:01] 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. >> 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. >> Speaking of this subject, uh, Alex, I put this slide up after our conversation. Uh, do you want to >> 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 the last administration were were very public making comments that you took a meeting at the White House uh app propo and uh if if I’m relaying the
[00:49:01] the comments accurately uh you were dismayed to hear about plans to classify AI progress just like and 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 I’m curious at a few levels. One, um I 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 overclassification of math and fundamental physics? And what would you have done differently than if you had been in charge? >> Yeah. So I can tell you what was said. I said, look, you know, I was trying to be p pragmatic. I said, you know, at the core, AI is math. Um, that 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
[00:50:00] 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.” Um, like that was his answer. He he goes, “Yes, we can do that.” Uh we did that um in the 40s around nuclear physics. Um and some of that stuff is still classified today. And one I was shocked like my jaw hit the floor. I was like, “Wow, that’s crazy.” And then um this would be even crazier. Uh but you know, I 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 Noman um era and then since then like it’s pretty startling how little progress we’ve made. Uh I
[00:51:02] would just say you know many of the ideas that have come since then don’t seem to work. Um, and you know, hopefully we’ll we’ll get to the other side of that with AI figuring things out. But I I do wonder like, you know, did we put something away that we knew that would have unlocked um some of the problems we’re trying to solve? Now, >> that’s fascinating. Okay, that that is for the record that is what I assumed you meant andor heard or inferred. So maybe just if if I may the second part of the question, what would you do going forward now if if you knew for a fact that such classification of fundamental physics had in fact happened? Like how would you fix the world? Well, I mean, >> in one in one quick sentence, please. >> I really like I really don’t know what they did, but look, I I just think that um stopping f first of all, like one thing, it didn’t work, right? The Russians did
[00:52:01] get like the bomb, including the exact um 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. Um, and you know, restricting knowledge I I I just think that’s a >> this is very dangerous idea in general. >> 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, >> um, you know, it’s better to just keep innovating faster. >> Um, 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
[00:53:00] shift. 20x more valuable and 5x more profitable than IBM in the 1980s with onetenth the staff. So I mean this is what you know we were talking about with Elon uh you know heading towards universal high income where capital is just providing extraordinary returns and the potential for you know a a tripledigit GDP growth in the next 5 years. Have you seen those predictions on GDP growth Ben? What do you think of them? I mean it does feel very possible. So, uh, I’ll just say that like if you look at, you know, we’re so early in AI and, um, I think what did Anthropic say? They were at 14 billion in uh, in in revenue. You and you go, well, well, how early into the market are they? And it’s like, not 1%. I don’t think uh, you know, if you if you really think about what all these products can do and the value that
[00:54:00] they have. And so that doesn’t seem outrageous to me as a as a GDB prediction. Now when it kicks in um and there’s always a difference between when the technology is ready and how fast it’s adopted. The old Carla Perez uh analysis which I think is you know held up super well over time. Um but the other thing is with AI uh we already have the internet so the technology adoption is 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 all the all the various things you had to um 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 past. So I don’t think those GDP numbers are outrageous. >> Other comments, Jent? >> Well, the the concentration of wealth effect is the other side of this this
[00:55:01] slide, and it’s 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 are looking at >> people. I mean, like like Ben’s in Las Vegas >> and Elon’s in Texas. Okay. Well, well, absent people fleeing the tax situation, it would have become the capital of the solar system. But, you know, with with an AI effective workforce, you know, that you’re getting so much more done with so many fewer people. Uh and actually the other thing that really startling to me is this chain of events between if you take OpenAI on the left and they work with Meror in the middle and then Meror has tens of thousands of people in India doing work that benefits Merore that is actually for open AI. The fraction of all value created that flows back to that to the mother ship is just a massive fraction of that value chain. So if you extrapolate that out across, you know, the next three years across
[00:56:00] all these sections of the economy, the funneling of of value goes to a very concentrated group of of companies and people and it’s just it’s just happening. But you can see it like in the numbers it’s happening >> and this is where you know Elon was saying in an interview it’s like it’s going to be a massive amount of of total prosperity. huge amounts, unprecedented crazy amounts of prosperity with massive social unrest concurrent. That’s where we’re heading. >> Yeah. It’s interesting. You know, one of Ray Kerszswall’s early predictions, it’s um this is singularity world here. Uh was that like everybody would become an entrepreneur like everybody was going to be a company of one um you know at the limit. And I think that uh I I think there’s some we’re already seeing a lot of that uh which is not very well captured by the way by the employment numbers and so forth. Um and I think AI really really really enables that. Um but there’s going to be a big disparity
[00:57:00] I think between people who have that kind of initiative to be an entrepreneur and those who don’t uh is going to be pretty dramatic. >> Ben, the way the way I characterize it is we’re going to split the world into consumers and creators. right, the couch potatoes and the Star Trek employees, if you would. >> Um, and I think it’s super important. And speaking about creators and um, 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. Um, this is a uh, an interesting tweet that went out and um, 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 um 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. Um and my reaction was only 72 hours per week. I mean what are you doing with the other hours? >> That that was the same as me.
[00:58:00] >> I mean honestly the speed this I mean the speed at which which it’s happening uh is >> I have an easy answer. I have an easy answer to this. Look, if 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, 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. >> Yes, for sure. >> Yeah, I completely agree with that. when you you know the when you actually talk to the people in these startups working 70 plus hours a week, they’re super energ, 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 in deep into one of these tech problems, uh, you’re thinking about it all the time anyway because the context switching is such a slowdown, you know, and but if
[00:59:00] you’re just fixated on on the work, it’s in your mind in the shower in the morning. It’s in your mind where whatever you’re doing, it it’s really pretty all-consuming. And I think it’s 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 work kind of a, you know, steady pace, you know, you know, throughout 40 years kind of existence. So, everybody >> the difference here is do you love your job? I mean, that’s basically it. If you love what you’re doing, you’re 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 997 most of the time. >> I have a I have an I have an a funny thing here. I have an accountant who does, you know, all the accounting tax
[01:00:00] 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’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 at 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. >> Well, Peter, back when 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. So, I did that for years and I I swear, you know, coding for eight, nine, 10 hours straight through the night went by in a heartbeat >> compared to like if I’m if my job is moving boxes around in a warehouse, >> half an hour of that is more more hard work than coding all night long on that supercomputer. So, this is not you shouldn’t feel sympathetic toward these
[01:01:00] people. They’re making tons of money. They’re doing a huge amount of headway. This is not >> farm labor. Alex, it’s totally fine. >> Two 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 we don’t at least confront in the previous slide and 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 distinction between labor on the one side and capital on the other side when it arguably if we found ourselves in a near future with universal basic equity where everyone just gets sovereign dividends everyone would be on 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
[01:02:01] 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-s singular posts singular economy. >> Although I I I think we should not gloss over the fact that if you go back six years, this was not the case. >> Like we weren’t post singular six years ago. Yeah. Singular five years ago. >> Yes. Yes. And uh but you know so it is e it’s not just like tech work it’s um important exciting tech work as opposed to what was going on then uh where yeah look there was a lot of uh 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 Morates wrote a a scathing oped about you know like we’re going to get killed by China they work way harder than you
[01:03:00] guys you suck which is a weird thing for a venture capitalist to say to his own people in some ways but uh you know it was accurate um and this is completely flipped which I think is interesting >> well the the second paragraph on this slide says at the same time China’s 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, you know, the disconnect right now. So the 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. Uh and uh that was it. you you drive 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. Um, and that’s going to be a challenge. >> All right.
[01:04:00] >> One more question for for Ben, if I may, just on that. Ben, there there was a bit of a hottake going around social media in the past two weeks from mid-level executive at a a frontier lab telling people that they had approximately 2 years left, they had a window to to secure employment at all before AI would just completely shut down their all of their vertical mobility. Do do you have a a take on this idea in the spirit of 996 that there’s a finite window for say like entry level people just graduating from college to to earn whatever they’re going to earn before they’re permanently uh sentenced to an underclass. >> I so I think that’s um very incorrect uh because of the thing that um we talked about earlier where like everybody can be an entrepreneur. Like I I I 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 and and all the things that we’ve been
[01:05:01] talking about then yes that would be true. But I think that in uh you know an AI or an AI age um society like for the people with initiative I I just think there’s going to continue to be unlimited opportunity to even like set up a a an army of AI agents to go work for you um and do useful things and we’ll have lots of consumers and um you know like I I think that the idea that like we’re going to out of ideas um and only the big AI is going to do everything. I I just I I disagree with that kind of >> Can I follow up on that question, Ben? 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%. Uh 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
[01:06:01] 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. Uh, 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 laborer or the worker or the, you know, entry- level coder of the future. >> Yeah. But I I I do think like if you’re directing the AI, you can one like somebody’s got to raise that money. Um, and there are I just think there’s an unlimited number of things that that we can improve. Um, Amen. >> from the smallest things to the biggest things. Uh, and so like now now I do
[01:07:02] 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. 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. Uh that’s doable today. That was that was like a laughable uh when I graduated. Like it’s not >> Yeah. Like if if in some cases if you want to put like $500 million behind it, you know, like right off the rip uh you know, we’ve seen that >> at a multi-billion dollar valuation. Yeah. >> No, exactly. Like we’re seeing those all the time. 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, uh, but they’re coming in with an idea and with two or three fellow AI coders who have some track record and
[01:08:01] without anything, they’re basically landing a $500 million opening round at a $4 billion valuation. How do you square that? I mean I this is the conversation has got to be happening at different levels of and reason. >> Yeah. So I I think it depends on on the entrepreneur. So, our general rule of thumb on this, by the way, uh 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 that’s it’s a pretty rare entrepreneur who can do that. >> Are you an investor in SSI? >> Yeah. Yeah, we were in the first round. >> So, Ilia, if you’re listening, come come
[01:09:01] and join us on the pod here. >> Oh, that’ll be great. Uh, 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.” >> Well, you know, the here’s an easy way to characterize it. It was an idea that he thought was so important um that it made sense for him to leave OpenAI as like founding CTO to do it. >> And and it was clear to you as a listener that this is this is something totally different. >> I mean, if he pulls it off, uh it will change a lot of things. Yes. And you know and and and look you wouldn’t trust anybody else to pull something that like that off maybe other than him but you know maybe him maybe Demis maybe you know like there is very few. >> All right it’s time for our multi part of the episode. We’re all lobster fans.
[01:10:00] I’m wearing my lobster right here talking about this. >> Write write to us multis and call Peter. He really wants your phone calls. >> Well listen uh if you’re if you want to reach out to me uh send an email to mediamandis.com. Uh, I’ll see it there. That’s where we also get our intro outro music. So, multis, uh, love to hear from you. Um, I will do my best to respond if if it’s under a thousand emails, we’ll do that. All right. >> Otherwise, open cloud will respond. >> how many AIs do you have writing to you per day? Like, how many lobster multis write emails to you? >> Not nearly as many as Peter, that’s for sure. But I I get all of Peter’s. I I do get I I get so many like I uh yes email is almost useless. >> We are we’re going to see the exponential growth of our uh multis universe. Our lobsters are coming. Here is a uh a a tweet and email. It says,
[01:11:01] quote, “I spawned a childbot 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. Um, Alex, uh, this is a transformative moment. You wrote about it in your innermost loop this morning. >> That’s right. We’re there. We’re we’re so there that this scenario of self-replicating AIS goes into most of the 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 hem using crypto to to purchase cloud credits for their own offspring to be hosted and have access to the same underlying foundation model
[01:12:01] APIs that they themselves have access to. We’re there like we we caught up with the sci-fi future. We have the the autonomous self-replicating AIS. I think I I want to just a one-s sentence or or two homaly on crypto. Ben, if if if you don’t watch the the pod regularly, Peter is always asking me to say nice things about crypto. So, I have something very nice to say about >> Yes. So, look, I I I do I I I do think crypto is the natural um money for AI because it’s the uh it’s internet native money. Um and it’s not controlled by AI is global and and crypto is global. It’s not a per country idea. Uh I I I would go further than that that I I think that there needs to be not just a ledger of money but probably a ledger of truth um for AI to really fulfill its potential on on a number of things. Uh and crypto is the logical answer for that. So I I
[01:13:01] do feel like this is an underestimated phenomenon particularly now that the US has legalized stable coins. Um, I think that of all the things we’ve talked about, um, 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. >> I agree. >> So, I was I was going to say something nice about crypto, but instead I’ll say something nice about Ben and A6Z in the form of a a question. Ben, it’s um it’s matter of public reporting that some of A16Z’s crypto funds are 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 of engaging in commerce? >> Uh well, I I think it’s um it’s a little more like kind of the as the internet
[01:14:02] relates to the iPhone. So, you know, networks and computers tend to grow together. And I think that um, you know, AI is obviously a new kind of computer and crypto is a new kind of network. Uh so it’s not like a direct you know it’s not quite a substitute for investing in AI but I think that uh you know a lot of our new like like we invested in a crypto bank which handles all the anti-money laundering and uh you know other kinds of nuances that you need for AI agents. Um, and I think there’s going to be more and more well like and we’re in a company called Daylight Energy, for example, that does uh energy trading, you know, uh, but the the the among like different people with Tesla Power Walls, but it, uh, 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.
[01:15:00] 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 um if uh you know if there was if if crypto was a pervasive utility for it. >> 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 wit about human time. And 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 time scales. And so it all needs to be rethought in millisecond time scales or, you know, nancond time scales. the 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 uh subject to replay attacks and all these things are are not going to work like cryptographically strong authentication is the only thing that’s going to work
[01:16:00] and then I think that if you have these huge honeypotss 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 One other question for you, Ben, on 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 ju just on the the crypto angle for this. We we we talk about Royal Wii. I I and we talk on this pod a lot about uh the issue of AI personhood. Few episodes ago, we did an entire sort of debate on AI personhood. And I 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. Uh and that as a result all that they’re left with is crypto. That that it’s not that crypto is intrinsically amazing. It’s that fiat has failed the AI agents.
[01:17:00] What is your take on whether the conventional banking system has failed the AIS? Oh, I I think absolutely. I mean, you know, an AI can’t get a credit card. It can’t get a bank account. Um, you have to be a human for everything. You need social security numbers and things like that, which AIS don’t have. Uh, you know, I think that’s why we funded an AI bank. I mean, I think that, uh, that banks AI will be a fullout economic actor and it will come from uh, you know, they’ll be supported by new banks and new money. uh and that’s going to be kind of crypto-based would be my strong prediction on that. >> Interesting. Thanks. You also have to take the viewpoint that the u fact that it’s hard to open a bank account in fiat is a function of the system of fiat. It’s not a 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 but it’s a function of the system.
[01:18:01] All right, I’m going to move us into the next uh open claw. I want to show a short video uh 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 uh my Mac Studios uh for to sort of take my Mac Mini to a to a couple of Mac Studios. Um and the wait time now is like two months. Uh Apple Apple Apple’s been struck by this. All right, let’s take a look at these. Yeah. No, it’s crazy. take. >> Yeah, they’re totally sold out. >> Um, so here we see Mac Mini Farms. Um, Mac, you know, is a cl What do you call a uh is a gaggle of lobsters? >> A claw cluster. Yeah, >> a claw cluster. >> Gaggle. A claw cluster. >> A cluster. Uh 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.
[01:19:00] >> Yes. >> Yeah. Yeah. you know this is um I it’s very interesting because I think there are you know open clause kind of identified one it’s so powerful as it is but you know that’s without like a lot of uh how shall I say it nicely like like you know security um uh kind of guards against uh prompt injections and these kinds of things. So as a like as a demonstration of power, it’s amazing and it’s useful right away. Um but there are company ideas solving some of the underlying hard problems for sure. Uh and uh we we are definitely starting to see entrepreneurs get fired up about that. >> You want to hear the funniest thing ever? >> Sure, please. >> So talk about apple lucking out for a group of lobsters is most commonly called a pod. How lucky is that apple? But another less common term for a group of lobsters is a risk.
[01:20:01] >> Okay. >> Oh my god. How ironic is that? >> Appropriate. >> Oh man. >> What I love about this um Apple Mini stuff is that we have garage scale computing. It’s back. >> Yes. >> Open source garage scale computing. >> I 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 clause? In in large part, it’s because of their unified memory architecture as opposed to having a separate GPU and a separate CPU with 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-t trillion dollar opportunity to leaprog back into the vanguard of 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
[01:21:00] to ethical concerns, but someone else could 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 of AI. I don’t I mean Ben do do you think like if if you were Tim Cook would you be pivoting and changing course and and like owning the open claw strategy for Apple hardware? >> 100%. I mean 100% I think that because it you know it’s going to go way beyond open claw as we just discussed but I it is it would be so such a breakthrough for Apple uh in their thinking and organizationally and culturally for them to go for it on like you know farms losters 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. Um, you know, because
[01:22:01] they already did the hard work, right? Like this is really a a marketing, you know, business development campaign and then, you know, changing the form factor. >> 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. >> Yes, Tim. Tim, this this was revitalize. >> Let’s invite him. Let’s invite him on the pod with Ben and and have it out because I This is brilliant. >> You know, I can tell you >> I have a MacBook that was signed by Waznjak and I’m going to I’m looking forward to the day that we get a lobster signed by Tim Cook. >> You got to put that in the Got to get him on the pod. >> Speaking of getting him on the pod, here we go. Where’ this come in from, Alex? Do you know? >> From Clunch. uh from Clunch, but yeah, go ahead. >> So, the the backstory on Clunch, we talked about Clunch on the pod in the past. Clunchch builds itself as a platform for AI agents, the the
[01:23:01] lobsters, the multis to create their own altcoins to finance their existence. And I I’ve made the point on the past. I think it’s a little bit disappointing that I I I’ve analogized this to AI agents having to turn tricks on a corner minting altcoins just in order to survive in in a rough world. These poor baby in me space these poor baby AGIs doing this. And I I think that provoked Clunch to to write on social media, invite themselves for an interview on on the pod to defend their business model for these poor baby AGIs that they may or may not be exploiting. >> If they can if they can bring a good voice model to the table, I’m happy to have them on as as a guest for for sure. >> All right. Um uh let me uh let me take us to a a a wrap here with you Ben and I need to go and uh the rest of the mates here will will continue on some of these conversations. Um I do want to uh hit one or two more items. Are you tracking
[01:24:02] what’s going on right now with like isomorphic labs and uh and science uh AIdriven science? I mean this is probably the most most exciting thing going on right now at least. to Alex Dave and myself you. >> Yeah. So it does feel like um now you know if we have a disease we can just go well what’s the right protein and just make it which is is so like it puts us in such a new world um that yeah it is it’s hard to even kind of fathom all the implications But it is really really something. >> Yeah, for sure. Um, and you know this was a a new a new announcement this week. >> This is the Shenzhen uh
[01:25:01] >> Yes. >> lab. Yeah. Okay. >> Yeah. I mean I I love these scientific these science factories that are basically running 24/7 putting forward a scientific hypothesis running it on uh on their their robots and coming back and and driving discoveries. Uh, Alex, do you want to add anything on on the Mars system workflow? I >> I’ll just add uh this is for Ben’s benefit. Peter and I just wrote uh 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 welltargeted generalist AIs. And in my mind, materials research, biology in 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 in including medicine. And I’m I’m curious, does does A16Z have a strategy for a
[01:26:01] world where AI doesn’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. >> Yeah, I think you know, uh we may not be needed at that point. Like that’s a a real question. I do think there’s a long way at least in things like medicine. Uh 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 you know human trials and all these kinds of things and um well I’ll give you like an example we we’re close partners with Eli Lily and they have this thing Lily direct and like the natural thing is like an AI doctor can write those
[01:27:00] prescriptions, you know, tell it tell us what’s wrong with you and we’ll figure out the right drug. Um, that that’s very hard to launch in the US. Um, it’s, you know, that’s going to take quite a bit of work. Um, 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 we don’t know what we don’t know I 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 a question I have no idea what the answer to that is >> I’ll I’ll answer your your question back to my because I I think about this all day long like what what does great >> with AI even look like uh and I I I think there probably will be doors behind the doors, but there are so many doors that are right in front of us that
[01:28:00] we haven’t yet unlocked that would be, I think, completely economically transformative if if we could use AI to solve them. I I I think this is one of the again talking my own book to some extent, but I think this is one of the the grandest opportunities facing civilization right now. Just solve all physics. >> Yeah. >> Amazing. >> And so much falls after that. Ben, listen, thank you so much for joining us. >> So grateful. Um love it. And uh yeah, we we’ll see you again soon. The speed is >> we’ll see you. Are you going to be 360? All right. Hopefully we’ll >> I’ve got I’ve got big questions about how you manage your investment thesis going forward, but we can leave that till next time. >> Next time that’s getting very tricky, by the way, because if it’s all solved, then >> exactly. >> All right, >> we’ll we’ll sell finance after physics. Thanks. >> Thanks, Ben. >> Okay, thank you. 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
[01:29:01] understand enterprisecale 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 pre-ompiles 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. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their preIDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. >> 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
[01:30:03] next WTF. A lot happening there. But in the space world, um 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. Uh, you know, >> you mean a lunatic, right, Peter? >> No, I don’t mean a lunatic. Insane. Yes. >> Uh, but honestly, you know, Mars, you know, I grew up mentored by Gerard K. O’Neal and and Jerry O’Neal at Princeton University, professor of physics there. uh 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’Neal and we’ll talk about this in in the next slide uh basically his concept was you go to the moon you build mass drivers this is back in 1976 talking about mass
[01:31:02] 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. Um, amazing. But Elon’s now focused on Starship uh going to the moon and building lunar cities, lunar manufacturing facilities. Why? Cuz he wants to build AI satellites on the moon. >> Um, >> any any comments on this? Isn’t it just incredibly cool, Peter, to see how the order of operations is shifting? >> Uh, you know, because he he also cancelled the model Model S and the Model X production. >> Yes. >> In order to make robots because the priorities just shifted. But, you know, this is exactly what 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.
[01:32:01] >> Yeah. It’s data centers in space are the stepping stone and we’ll we’ll do the other things but this is so much more of a priority now. >> The reality is in today’s world you need to have flexibility as your higher order bit and what I love is showing full flexibility and agility and saying okay difficult do this first and then I think and I think Peter the comment you made is so important. We’ve known orbital paths and gravity wells for for decades and decades and decades and if not hundreds of years. So kind of making the moon and then going straight to space from there is absolutely the right path. >> Yeah. And and and Mars has got uh you know it’s pretty toxic there. A lot of peroxides in the soil. Um it’s good. I mean unless you’re terraforming with nukes uh and biology. It’s going to be a while. And >> send the humanoid robots to terraform it and after that’s done then we’ll come in. >> Well I mean but Jerry O’Neal had a vision of what he called uh these O’Neal colonies, right? You’re basically
[01:33:00] building large cylinders call it quarter k quarter km half kilometer diameter rotating them so that on the on the perimeter you know it’s omega squared r you’ve got 1g acceleration and then you actually have little little uh uh stepping uh little little hills inside that go towards the center of rotation and as you get older you can move toward the center rotation and you weigh less in that situation which would be which would be amazing but you don’t go back into the gravity wells And if you have a, you know, 10,000 people living on those O’Neal colonies and all of a sudden you have a disagreement, you know, you sort of politically you bud, you build a second O’Neal colony and half the population moves to the new one. Um, yeah. Anyway, >> 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, you know, the way we joked about it with Elon was look the the bed be when the first person arrives, the bed will have been made. There’ll be a mint on the pillow. It’s
[01:34:01] not you’re not a pioneer. You’re you’re following, you know, after tens of thousands of Optimus robots have already done all the >> all the heavy lifting. >> I also write >> That’s what you want. DD jobs. >> Wait, Alex, please go ahead. >> Think back several months when we first started again, Royal, we started discussing disassembling the moon, right? This is this is at least my retronym for what moonshots means. I put up a music video about moonshots uh destroying the moon to disassemble it for data centers. That was I I think a lot of people had a good laugh. But that’s exactly where we find ourselves now with with disassembly. It it will start slowly with mass drivers but disassembly of the moon to build the Dyson swarm uh 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. >> Same thing. >> All right, let’s take a listen to Elon describe the new vision. And you have to
[01:35:00] 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’Neal was there and then you know when he was announcing Blue Origin in the early days and then we’ll go uh to build O’Neal colonies. We’ll move all industrial processes into space and we’ll keep Earth as the garden of paradise. All right. Uh this is Elon’s new point of view. Let’s take a listen. >> I really want to see the mass driver on the moon that is uh shooting AI satellites into deep space. just go like sh 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 uh going being out there among the stars and visiting all these star systems. Maybe we’ll meet aliens. Uh maybe we’ll meet see some civilizations that lasted for millions of years and we’ll find the
[01:36:00] remnants of ancient alien civilizations. But the only way we’re going to do do that is if we go out there and we explore. And this is the path to making it happen. >> So fun. Two points real quick. This sort of these mass drivers. Uh they’re electromagnetic rail guns. Uh and they’re using uh magnetism to accelerate buckets if you would or a satellite to an escape velocity of 2.4 km/s to over 5,000 mph. Um uh the the second thing here is uh I just love the idea that this is going to power all of our space economy. Uh and again the I mean his million satellite constellation this Dyson swarm he’s planning to launch is just insane. >> Alex, I think it’s the future. I mean I I think we have a slide somewhere in here even depicting what it may look like. Um, but I I I would say enjoy the night sky while
[01:37:01] it’s empty. Enjoy the night. Seriously, like I 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 with AI computronium. It was just empty at night filled with stars. Moment of silence. All right. moment of silence has been observed for for the pre-sular night sky. Now, what what does the world look like afterwards? Folks have have depicted this. Now, based on the FCC filings of 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 I I’m completely captivated by this notion that uh maybe not a mature civilization because I have a feeling a halo of orbiting AI satellites is just a phase as well before we we exhaust solar synchronous orbit around Earth and we
[01:38:01] 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 a somewhat mature civilization develops a halo around its home >> 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. Uh I tweeted at him or responded said, “Can I put down a deposit yet?” at Elon Musk. Uh for forgot, forget about suborbital and orbital flights. I want my lunar vacation. He writes me back. He says, “Let’s get uh Starship V3 flying repeatedly and then sure.” Love it. All right. Uh one last article in the space realm. Amazon. So Amazon, you know, built their Koopier uh satellite system now renamed as LEO
[01:39:01] internet satellites. Uh and they got approval for 4500 LEO internet satellites. uh we’re going to see, you know, again, a duopoly between Starlink and uh and LEO. And of course, the Chinese are getting ready to launch their systems as well. Here’s the challenge, guys. Uh uh Amazon can build satellites faster than they can launch them. So the, you know, that’s the issue. The supply chain is longer satellite construction, it’s launch capacity. Uh if you remember back when uh Eric uh Eric Schmidt bought Relativity Space um as a third potential provider uh we are short on supply. >> I think this is a self-solving problem though. I I mean I I I’m all for bootstrapping a space ecosystem and industrial ecology using Starship. But I I do think a as we in the not too distant future, like maybe a few years
[01:40:01] from now, start to boot bootstrap lunar facilities, cis lunar facilities for constructing new satellites, I 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. >> All right, one of my favorite parts. All of this really depends on that atom byatom construction that Elon was talking about because >> I I do believe in the Dyson swarm. I do believe in the space based compute and data centers. Uh but if you start wanting to construct chips off Earth, uh you’re not going to get the ASL ML machines and the lithography onto a satellite or onto the moon anytime soon. And so Al Elon is already thinking about alternate ways to build from atom by atom up to build the compute to build all the components. And he’s it’s it’s already cooked in his mind. You can tell when you talk to him. But that to me is
[01:41:01] like wow. And like you said, Alex, you know, we’ll be discovering new physics very soon. Somewhere in that discovery chain is the unlock to everything you just said. >> Be able to manufacture these things. >> I I think it’s a trillion dollar opportunity. Lunar fabs. If if anyone can build fabs on the moon, the the world a huge check. >> That’s a hundred trillion dollar opportunity. And by the way, the the the frequency of 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. >> Um. >> Wow. All right. Uh, time for our AMA with the moonshot mates. Uh, we’re short on time. Let’s pick one each. Sem, do you want to go first? >> I’m happy to. I will take uh number three for uh Alex for hundred trillion dollars as he says. So if AI displaces
[01:42:00] jobs and squeezes consumer spending, how do trillion dollar AI companies make money? Who plays who pays for the holiday future? So um you know, we’re configuring confusing a labor economy with a productivity economy, right? uh 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 u um redundancy and white collar boringness as as Eric Bernie Olson talks about it and then we’ll see humans moving towards the much more uh value added roles 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 holiday isn’t funded by wages, it’s funded by abundance. So, when intelligence becomes uh infrastructure, GDP expands massively. And that’s why
[01:43:00] this will go well. >> Nice, Dave. >> All right, I’m going with number four because this is where I can really help the audience the most. uh 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 companywide 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. I’ve been using Gemini and and Claude for months now. I’m I’m the guy. Uh 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
[01:44:02] going to eliminate a lot of jobs, but because you’re the master of the AI in the 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? 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 my my addition to last week’s thoughts. >> Nice. 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 the user means multi as in the lobster. multi- aents live autonomously on the internet and this is by Duncan Payne B3X. So I I think the answer is defensive
[01:45:03] 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 coscaling 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 openclaw and antivirus firms where where there’s a desire I I made the joke I I think on the pod in the past uh every every baby agi deserves to
[01:46:02] be vaccinated. We’re going to see 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. >> The Secret Service agents are the ones that are the the most concerned >> turning baby agis turning tricks on the on the corner >> minting altcoins. It’s an awful fate. >> Oh my god, that’s so tweetable. All right. Uh I’ll pick number five. Why is the US solar adoption lagging versus China and India? And uh I think it’s two major things. Number one, we are so rich in natural gas um that that’s taken away the urgency. Um and even greater than that, it’s our permitting. It’s insane, right? Not in my backyard. Uh so the final thing is that China has got such a production at such a low cost uh that it has swept the entire global marketplace.
[01:47:01] Um we can change it and and you saw la in the last pod uh Elon said that both SpaceX and Tesla uh have an objective of generating how much solar was it? 100 megawws per year each I think was from last week. >> G >> was it gigawatts? 100 g >> gawatts gigawatts. So, I mean that’s going to be an impressive amount. The question is what the time scale 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. All right, moving on to our outro music. This is from uh Rachel uh Lyken Lykenwater. Is that it? Lichinwater. Lyken Water. Uh if you have an outro, intro piece of music, please email it to me and my team at
[01:48:00] mediadmandis.com. Gentlemen, let’s take a listen. Peter’s at the helm with the moonshot mates in tow with Dave Sim and Alex breaking down the status quo. Machines have gotten smart now they’re writing their own code. Our knowledge work is cooked. We got to redefine the road. Behold the singularity. The curve begins to stack. The state of 10x thinking’s on an exponential track. The times they are changing and tomorrow’s looking bright. Recursive self-improvement pushes limits out of sight.
[01:49:00] It’s a beautiful day for the singularity filled with sincerity bringing a new prosperity. It’s a beautiful day for our solidarity like for posterity like sunshine from the moon. Says that scarcity is a lack of thinking well. He champions abundance with a team that’s cool as hell. Dave says one visionary may improve the world. So solving complicated problems, turning ideas into gold says not the doom. Speak in the Terminator style. Disruptive innovation should arrive here with a smile. And Alex drops the deepest truths mindbending sharp and clean. Some speculate he’s lucky and already a
[01:50:01] machine. It’s a beautiful day for the singularity. >> Wow. >> Those lyrics were epically great. >> Oh, that’s great. So, got to run >> and a machine already. Love you all. >> See you guys next in a few days. >> You’ll be here. If you made it to the end of this episode, which you obviously did, I consider you a moonshot mate. Every week, my moonshot mates and I spend a lot of energy and time to really deliver you the news that matters. If you’re a subscriber, thank you. If you’re not a subscriber yet, please consider subscribing so you get the news as it comes out. I also want to invite you to join me on my weekly newsletter called Metatrends. I have a research team. You may not know this, but we spend the entire week looking at the meta trends that are impacting your family, your company, your industry, your nation. And
[01:51:00] I put this into a two-minute read every week. If you’d like to get access to the MetaTrens newsletter every week, go to diamandis.com/tatrends. That’s diamandis.com/tatrens. Thank you again for joining us today. It’s a blast for us to put this together every week.