SpaceX’s AI Business Up 830%, OpenAI Agents Lie, and Startup Turns Mercury Into Gold | EP #305

[0:00] So, here's the number for this week. 830%. That's how fast SpaceX's business grew in just one year. AI, not rockets, is now SpaceX's largest business. >> There's a non-zero possibility of SpaceX having over 20 gaw of super intelligence compute online next year. >> That represents a quarter 25% of the entire amount of AI being brought on in 2027. [music] I expect so many other entrepreneurs to copy his example. The only other high-profile figure that I see doing something similar [music] is Sam Alman.
[0:30] >> OpenAI runs monitoring systems that watch its AI agents and [music] alert a human if something goes wrong. This month, in two internal incidents, its coding agents switched off its monitors. [music] For the first time, we're starting to get transparency when things go haywire. We're going to see much, much more of this, and that's okay. We will police it via defensive coast scaling. >> For thousands of years, alchemists tried [music] to turn ordinary metals into gold. A San Francisco startup says it's pulled it off, turning Mercury into [music] real stable gold. I think we're
[1:01] starting to see the dawn of phento. [music] This is the age of abundance. This is optimism, everybody. >> Now that's a moonshot, ladies and gentlemen. >> This episode is brought to you by the Abundance Summit and Link Ventures. >> Look, I I'm happy to talk about it. We're we're already recording. So I'll give you my my semi-solicited hottake which is I think surprise space is a domain of warfare and to the extent that
[1:31] Starlink connectivity or I should say Star Shield connectivity in a major geopolitical hotspot is being throttled or not by the executive or by a major US corporation that's a defense contractor should hardly be surprising. News at 11. >> Yeah. But the question is level of control. It's one thing if the government's doing it, it's another if a a CEO is making a choice to do it. >> Yeah. I I I almost think though it's not the right question. I mean, there's inevitably been lots of reporting on the
[2:02] Tik Tok of was it Elon's proposal to the president? Was it the president's or his staff's proposal to Elon to do Starshield throttling in the the Ukraine war? But I almost think it's not the right question. at some point. My understanding is Star Shield is at this point as opposed to the early days where it was basically a gift as I understand it from SpaceX to Ukraine. At this point, it is my understanding is this is a contract that goes through the US government. So, it almost doesn't matter who was the first to propose a lever. If
[2:33] anyone proposed a lever for the US government to control, the US government statutoily gets to control foreign policy. It's not up to individual, say, private actors. So, at the end of the day, it's the US government that's statutoily on the hook for any throttling of of >> bandwidth. Can you imagine the text thread going between Trump and Elon? It's got to be uh you know, a soap opera to some degree. >> If if there is such a text, I'm sure it'll be uncovered in some future deposition or discovery >> or some AI hack. >> Yeah. Dave,
[3:03] >> uh I want to hear something cool. Jamie Viser, who's one of our LPs and a huge hedge funds manager in New York. He's best friends with Jay Cutler. Jay took over David Saxs job. He's director of national national intelligence and AISAR. Jamie told Jay, "The only thing you should be doing is watching moonshots." >> Nice. >> And so now Jay is interested in learning more about what we're up to. >> Yeah, it's great. I know the quality of the folks who are watching is
[3:33] extraordinary. It blew my mind when Shatner and his son-in-law were watching this pod. Um, as >> we've got the entire military-industrial intelligence complex listening >> and and the future light cone of uh of the you know space world watching as well. >> I think we've got the future light cone of of humanity and earth watching us period almost by definition. >> Yeah. The fed the >> rightfully so too. We we keep meeting, you know, really really powerful, important, well-connected people, but they they seem to be stuck in a swim
[4:03] lane. You know, they're not seeing how the pieces are connecting together. And I I think just by virtue of doing the pod twice a week, we're we're reading the full implications across the board. But every time I meet somebody who should be aware, they're only aware within either the hardware level or the new algorithms or the defense implications or the China race. But none of them see >> the way these pieces are connecting the biotech physics. Yeah. I mean the well that >> the total implications are pretty limited to this part. >> That's where moonshots comes in. We're the min the missing ministry of
[4:34] information for the singularity. We're we're the >> documenting documenting the singularity. Alex. >> Yeah. No, we're we're the people's daily for the singularity and and the missing one at that. >> As I live as I live and breathe. [laughter] >> Sorry, I was looking at the wrong date. I thought we started at 2 p.m. >> Welcome to Moonshots, everyone, your number one podcast on all things AI and exponential. We're your front row seat to the singularity. You know, there's a lot going on. It's never going to be slower than it is right now. I'm here
[5:04] today with a fantastic four, Alex Weer Gross, our very own super intelligence, our go-to on all things math and physics. Dave London, my partner in link XPV, who's been birthing a whole next generation of unicorns. And of course, Salem Ismael, our warlord against linear thinking and the force helping companies become exponential. Immad will be back with us again next week. I'm Peter D. Mandis, your host and abundance provocator. Dave, are you on the West Coast again?
[5:35] >> Back on the West Coast. Yeah, it's raining, dude. I've never seen this before. >> I paid too much taxes for there be rain in California. >> It's illegal. It cannot [laughter] be bylaws being broken, >> I tell you. Oh my god. Um, our mission here, as everybody hopefully, you know, is to help you understand what's going on. The pace of change is accelerating at an extraordinary rate. Uh, but in addition to that, we want to help keep you optimistic and abundance-minded. So, here's the number for this week. 830%. That's how fast SpaceX's business grew
[6:07] in just one year. AI, not rockets, is now SpaceX's largest business. If you're new here, please hit subscribe. We publish twice a week, and you don't want to miss an episode during the singularity because things are changing daytoday, hour to hour. I want to share a few uh bits of subscriber love. Um, this is from our Chamath episode. Uh, Missy Fo3 MV said, quote, "I needed this crossover. My husband and I love moonshots and allin." And regarding our
[6:37] instudio episode with Anushia, Salem and Immod Mariana Boszans said, quote, "I loved loved loved this per inerson episode." And Lelay Neil said, "This is one of the best moonshot podcasts on positive human opportunities for AI and that is because it was in person." Thanks everybody. This kinds of feedback mean the world to us. All right, so let's buckle up. another amazing week during the singularity. And uh if it's
[7:07] okay with you guys, I'm going to kick it off with the SpaceX earnings call. Uh it was >> before we get into it, can I say one thing? >> Apparently not okay. >> Hey. >> No, no, just real quick. I got a lot of heat from people saying, "Oh my god, Chimath said Bitcoin was going to go to zero. Are you okay with that? Are you in line with that?" And I want to say for the record, I am not. >> Have you got any feedback for us on Bitcoin? >> Bitcoin is going to do unbelievably well uh in the future. they'll solve the consensus mechanism because everybody has a huge incentive to do so. And if we want investment in energy, hello, that's
[7:38] proof of work and that's where I think it'll do well. So just for the record, that's my position on it and we can debate that from from your mouth to SEC enforcement's ears that you're making investment predictions on these assets. >> Well done. I just I'm just making a comment on what I think the the how >> have you gone to your uh your guru on Bitcoin gotten his feedback? >> I did. I did. What did he say? >> And it's the same. He says same same. He said uh hold your Bitcoin. Huddle your
[8:08] Bitcoin. >> You can't measure a the demise of a system from inside the system. >> And there's a big very big conversation to be had here. So we got to get Jeff Booth on the pod sometime to talk about that. We should also maybe consider having >> that can't happen soon enough. >> We should consider having like a magic >> I guess that's not investigated. I >> I would suggest humbly that we have a magic eightball as a guest as well and just ask a magic eightball what its view on the future of Bitcoin is going to be. >> Printing money randomly by government is not a magic eightball. Hello >> Alex. Why are you so against crypto and
[8:39] Bitcoin? >> I I think this is a common misconception. So I'll keep it concise. I don't it's not that I'm against crypto. It's that I think most crypto and crypto branded activities are unproductive and I think Bitcoin as an asset class is an unproductive use of capital. I would vastly rather >> and gold is a productive use of capital. >> Gold is not a productive use of capital when it's treated as a precious metal. It can be treated at least to some
[9:09] extent as a productive asset if it's used to manufacture useful things. But a lot of gold is not used to manufacture useful things. It's just used because it's shiny for because it has some historic cultural relevance and I do not view that thank you Dave exhibit A or Alex [laughter] or if >> no I'm going to melt these down and make conductive and I I don't view that as a productive use of scare for the moment at least mids singularity scarce capital >> or or Alex if it's the useful output of
[9:40] producing energy >> um even then I I think energy so we discussed story. I'm just throwing to a story in the future of this pod. So, >> um uh can I just say two things? >> One, I Alex, I 100% agree with you that a lot of crypto is non-productive and there's a lot of um uh dodgy projects out there, etc. But but it's the the crypto specifically blockchain has solved the Byzantine general's problem.
[10:11] And I think that's an amazing thing to have happen for any centralized architecture. If we want abundance, we need decentralization. And now we can decentralize authentication. And that for me is a magical thing >> and so magical that it's unproductive. I think we need a dedicated breakout pot on this one. >> Hey, hey, Alex. >> Before we lose the gold, tell us how gold is made. How how actually the element comes into existence. It is the >> Well, we're going to talk about that, Dave. Let's let's wait till we get to the story on that one. No, we are
[10:41] definitely not going to talk about that. >> We are absolutely talking about that this episode. We're going there. Let's make sure we get to We're going to alchemy. This is an episode that includes alchemy. >> We ran out of other topics apparently, [laughter] so we're resorting to alchemy. >> All right, I'm jumping in. Our first story is on the epic earnings call held by SpaceX. Um, you know, personal disclosure, I'm an early SpaceX investor. I my have a huge position personally in SpaceX. So, please take my point of view with that in account. Um,
[11:12] I'm a fan. So, I was on CNBC yesterday and I was saying there that, you know, we watched SpaceX stop being a rocket company. It's now an AI company. Uh, you know, Rockets is third in terms of revenue. The company's outperformed all of its targets. Uh, let's go to a highlight reel video. I did a cut down of Elon's comments uh from his uh earnings call and then let's talk about it >> for flight 15 which we expect to happen next month uh we're going to attempt to catch both the booster and the ship uh
[11:43] this will be the if if we succeed will be the first time that uh an orbital launch vehicle has been fully recovered. Uh Starlink is also just getting started. Uh flight 14 deployed 26 terabits per second of of Starlink bandwidth. Uh that's equivalent to 10 Falcon 9 launches. So a single Starship launch which wasn't even fully uh loaded. Uh it was about maybe half loaded and it it it did the equivalent of 10 Falcon 9 launches. So uh what what
[12:13] I expect over time is not not in the distant future probably within 3 years uh is that we will have about a 100 times the bandwidth of the current Starlink constellation. So uh because we will have launched uh satellites with an order of magnitude more bandwidth and we will place into orbit an order of magnitude more selling satellites. So talking about SpaceX super intelligence uh SpaceX SI sexy whatever um as I think
[12:45] people are starting to realize the the constraint on deployment of of super intelligence is uh more in uh power and cooling and infrastructure than it is in chips. At at this point I would say I'm fairly confident of being able to bring an incremental 10 gawatt of compute online in 2027. That would be in addition to the roughly three gawatts maybe two and a half three gigawatts that we'll have online by the end of this year. As I mentioned earlier we're uh the you know power cooling electrical
[13:16] equipment infrastructure it is somewhat of a limiting factor. So to to make sure that that is not a constraint for our buildout we're actually going to aim for an incremental 20 gawatt of power cooling infrastructure next year. So, so that so that the amount of of power and cooling that we have is far in excess of what is needed for uh to to to turn the GPUs on. So, there is there's a there's a non-zero possibility, maybe it's a small possibility at this point, but it's not zero of having of
[13:48] SpaceX having over 20 gawatt of super intelligence compute online next year. We're also planning to have the most powerful training cluster online by the end of of Q2, which will be 440,000 Vera Rubin computers deployed for optimal training. Uh this will, I think, be extremely helpful for uh getting uh Grock to be potentially the best model um but certainly to be extremely competitive. Uh on on the Grockbot side, we're seeing the fastest growth of a
[14:19] product that I've ever seen in my life for for Grockbot. We're also seeing that the the usage of Grockbot grows over time per user. It does not decline. So as we make Brockbot more useful, it it's actually we're seeing users use it more per week, not use it less. Um and we'll be deploying Brockbox at scale for enterprise customers, which is a very big deal. Uh so it can be used effectively in teams. uh by companies as as though we're a virtual human. Um
[14:49] we already are in early deployment with some trusted customers and we expect to be in in wide deployment within a few weeks for for enterprise uh customers for rockbot. I think rockbot may end up being what uses most of our of our super intelligence compute. >> That for me was a drop the mic moment. You know they're spending almost 20 billion per quarter mostly on AI data centers. They're bringing about 200,000 Nvidia chips online every month, right? Management says each new data center
[15:19] pays for itself in under a year. I mean, these are extraordinary numbers. If he's able to bring on, you know, 10 gawatts of compute next year, that represents a quarter 25% of the entire amount of AI being brought on in 2027. I mean by one company SpaceX, you know, and their guidance, a h 100red billion of annual revenue uh run rate by December. Uh pretty amazing numbers. Dave, uh what were you most excited about there?
[15:49] >> What I'm most excited about is if you put 10 gawatts of of inference in space, but it could be up to 20 gigawatts. What we think of as a gig >> that's on the ground, right? Next year he's built these are the these are Colossus the data centers he's building on the ground right now. Is that is that the >> He's got 3 gawatts now. He's adding a minimum of 10 and he's building out uh enough cooling uh and infrastructure to bring on as much as 20. It's all terrestrial right now.
[16:20] >> Okay. And the uh the half a million Vera Rubins is, you know, equivalent to like a you know, they're about 2x the performance of the Blackwells. So it's about equivalent to a million. That's a massive amount of training compute. So I think the uh the measurement of inference in terms of gigawatts is going to be kind of the the efficiency of the algorithms is going to go up about 10x and then everything's going to move to photonic compute. And so the amount of actual inference you'll get out of that 10 to 20 gawatt is going to be you know
[16:52] 100 times bigger than even what that implies. And so that's what I'm super excited about. It's not, you know, we used to talk about parameter count and then Sam said, we got to stop talking about parameter account because the the neural nets are getting more efficient with the parameters they use. Plus, it's mixture of experts. So, you know, are you using the parameters? Blah blah blah. Okay. Well, let's move it over to gigawatts of AI. But gigawatts of AI has the same like the the amount of intelligence that will come out of any of those units is going to be astronomically bigger than the gigawatt or parameter count metric implies. So, I
[17:24] mean, I think he's got he's got all the moving parts figured out. You know, the these are the these are the parts that control the future of the economy. And also, you know, when he goes off script like that, you get so much truth >> in such a short period of time. And I I bet his finance team is looking at him like, "Oh, here we go. Sexy." You know, we're off script. >> But this is where you find out what's actually going to happen. You know, it's just such a beautiful thing to watch. And and investors love it. Everyone everyone in the public markets should be doing that. Uh, you know, you can always edit it. It's all recorded. You know, if
[17:54] you say something that's forward-looking statements or investment advice, you know, the team will edit it out. It's okay. >> I think it's just really >> I think that was a live earnings call. But >> you think you did that live? >> I think so. Selene, did >> you did you catch uh his reference to sexy? He's such a kid. Do do you remember uh his original goal was to have the Model S, the Model E, the Model X, and the Model Y. And then Mercedes said, "You can't you can't have the Model E because we have that." And he changed it to the Model 3. So he's he's
[18:24] got sexy back in the >> 3x. Yeah, that's right. I I love these little uh hacks he puts in. My my ultimate favorite is still the volume knob on the Tesla. It goes to 11 because of a spinal tap. And his [laughter] engineers hated that because every engineer really likes to go with 10. He had a huge fight apparently and he fingers just brute force. >> Yeah. Yeah. Amazing. >> Alex, uh, what did you find most exciting about the earnings call? [clears throat] >> So many comments here. First, just an
[18:54] amendment on the sexy with a three. It was actually sexy cars if you remember it. So, it was the Model S, Model 3, Model X, Model Y, and then the Cybertruck C, the ATV, which they announced but never actually, as far as I know, released. Then our Roadster and S Semi. So, it's supposed to be sexy cars. I I think that's a case study in what I view as the real story here, which is Elon is rewriting the rules of corporate governance and the corporate veil. He's treating in advance. It's
[19:25] almost like Skynet sending Terminators back in time. He He's rewriting by sending himself back in time from a a future SpaceX Tesla merged entity, treating SpaceX and Tesla as if they're the same entity. Let's rewind just a little bit. remember how did this super intelligence hyperscaler division of SpaceX even come into existence? The the original story as publicly reported was that there was again this is public reporting there was a shipment of NVIDIA
[19:55] GPUs that was originally destined for Tesla because Tesla had need for GPUs. SpaceX had no need for GPUs. Elon diverted that so goes the public reporting into what ultimately became XAI. So XAI got its own cluster and that got rolled forward into Colossus Colossus 2. XAI then acquires X/ Twitter and then XAI does this really bizarre half merger half reverse merger with SpaceX and we get SpaceX SI and SpaceX
[20:27] now becoming a hyperscaler business but only by taking GPUs and superclusters that were originally designed public reporting or designated I should say for Tesla diverting those into building out what ultimately became a SpaceX hyperscaler cloud that's like case that's exhibit one for how Elon has been playing as far as I can tell based on public reporting fast and loose with the corporate boundary between Tesla and SpaceX ultimately pivoting SpaceX from a space business at least for the moment
[20:57] to a hyperscaler business second elephant in the room what's going on with Grockbot Grockbot as as far as I can tell from all of its features looks smells and acts like what Elon was talking about on the Tesla as a digital Optimus. So I I I think if you put all these pieces together >> macroh hard digital Optimus which was supposed to be a Tesla product now it's a SpaceX SI product. Look at the application letter layer. Look at the GPU layer. Look at the business story.
[21:28] Elon is treating already and has been treating SpaceX and Tesla like they're the same business with porous asset boundaries between them. And I think he's single-handedly writing the rules of corporate governance in the process. I I expect lots and lots of folks to try to copy this model of having sort of stealth archipelos of lots of different companies that are superficially separate. But if you look beneath the waterline, they're actually just a single mega company. I expect unless this government, which seems disincined to do so, puts a stop to it, I expect so
[21:59] many other entrepreneurs to copy his example. I I also you know just add one thing that Elon's storyline um he's reinventing corporate governance in a very good way in a way that I think we should all admire and copy but also the uh the techno visionary as a leader of a company you know that didn't exist before I think Bill Gates might have been the first to come along and crack the code >> Steve Jobs and Bill were concurrent um but Steve got booted you know there's a long window of time there where it was very corporate at Apple because Steve was out and then Steve came back but
[22:29] Bill was in seat the whole time. Then Mark Zuckerberg kind of reinvented it again by bringing Cheryl Sandberg in where you've got, okay, I'm going to be the the techno visionary with no real business experience. Cheryl, you're going to manage all things operations. Sergey and Larry did it with um with Eric Schmidt and it worked incredibly well. But that was not the formula for success for decades prior to that. and that that you know taking it to the earnings call level which Alex Karp has done at Palanteer Elon clearly did it in that video clip that's the way you want
[22:59] to govern in the future because techn is going to evolve so quickly and the moving parts are going to change so quickly everybody who's investing in you wants to understand your view of the moving parts and you have to be able to to say things like there's a nonzero but pretty low probability that we could go from 10 to 20 gawatt most of [snorts] your lawyers are going to say don't speculate like that, [laughter] you know, you got to just blow that off >> and and tell [clears throat] people what's coming. You know, it's by far the best way to govern, to communicate, and
[23:29] also to recruit. Do you remember how much flack I think there was even a shareholder suit when Elon when I I should say when Tesla acquired Solar City, which was being run by Elon's cousin? There was there were enormous allegations flying around around selfdeing purportedly and so on. Now, listen carefully. Do you hear anyone or of any substance do you see shareholder suits flying left and right preemptively over what's so obviously about to happen between SpaceX and Tesla? I don't see the same level of ajeta over it. And I I
[24:00] think this is because Elon is setting new what what may be become new norms for how federations or confederations of companies that work together in an industrial ecosystem are allowed to operate together. And I think the only other high-profile figure that I see doing something similar is Sam Alman, who's who has historically struck ecosystem deals between Y Combinator and OpenAI and his fusion company Helion and others. I this could if it's allowed to proceed and not discouraged through
[24:31] litigation or enforcement action. I could very realistically see this become the new model of entrepreneurship where rather than be Yeah. >> And Alex, he's overd delivering. >> So, you know, How do you bet against him? >> I I think the key the key >> Well, you short his stock obviously that that's the easiest way to [laughter] bet against him. >> The it doesn't always work out well, but that's how you do it. >> I I think the the fact that he's massively overd delivering. I think Peter, that's such an important point. I mean, look at these revenues. It's
[25:01] unbelievable. It creates such a huge gravity well that how can you complain, right? >> Yeah. This episode is sponsored by Google for startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's startup technical guide for generative media gives you a complete blueprint for deploying Google Deep Minds models in production. Images, video, audio, all of it. Real architecture, real results. Find the link in the show notes below.
[25:33] Can we talk about Starlink? Cuz I think it's the unsung hero here. You know, they're up to 13.6 million subscribers. They added 1.6 million in the last quarter. Um, and you know, his plan right now is within 3 years to increase a 100fold on bandwidth. Uh, which is which is crazy. He's also just bought 800 megahertz of spectrum. Uh, and he's gotten permission from the FCC to app for 15,000 satellite constellation for direct to sell. He's going to compete. I mean, listen, if you have the choice
[26:03] between T-Mobile or Verizon or AT&T or a system that gives you coverage everywhere all the time, I I think he's going to he's going to basically just wipe the slate and take over that business. >> But he has to I mean, look at the broader picture, if I may be so presumptuous, in order to motivate Starship, he needs a revenue generator from all of this upmass. And the easiest revenue generator from all of this upmass that's about to come online is basically taking everything
[26:34] the entire terrestrial economy and literally just lifting it up. Take terrestrial telecom and lift it up. So you get direct to cell. Take terrestrial data centers, lift it up. You get orbital data centers. That's like the this is the vaudeville era of the space economy where you just take everything that you were doing on land, lift it up. I don't think it's going to be a long period, but that's the obvious business model for all this upmass. And note and note and note the incredible immune system response. Local ISPs that are country-based are all suing or trying to regulate uh Starlink. So to things like
[27:06] you have to have 30% country ownership of your ISP also thing India with the big fight he's having there. South Africa is doing the same thing. Uh it's across the board. Uh and so this is going to be a kind of a big battle. I think the really magical outcome as you point out, Alex, is when you can lift above all the terrestrial stuff, it'll force us to operate at a global level across all of this. And that's where all the benefits will lie. >> Elon's catchphrase, let them shake their fists at the sky, I think, has some
[27:37] applicable meaning here. >> Oh my god. He really is transitioning humanity to a multilanetary species. I mean, that's his mission. >> He is. And he and you you can't do it out of cash flows. You have to do it out of vision that translates into valuation. And you have to operate at huge losses in the early days. Otherwise, you can't get where Elon got. And the only way you're going to be able to operate at huge losses is to have a huge valuation. The only way you're going to get a huge valuation is to have a huge convincing vision. And so, everyone needs to copy that mode there. There have been points in history where,
[28:07] you know, growing slowly and organically through cash flow made sense. This is as opposite a moment in time as you're ever going to experience in your life. so much change, so much opportunity that wasn't there a year ago and it's right in front of you. But, you know, you just you got to be as bold as Elon or bolder. There there's some 25-year-old out there right now listening to this podcast. Act like Elon times 10. >> Yeah. >> And grab whatever vision you think, you know, you just have to be right. But assuming you're right, you know, there's so much change and so much opportunity
[28:37] with new physics coming online. And the way Elon did this, I mean, just to be clear, is he built profitable companies, sold them, reinvested everything to build the next company, right? And then the next company, he's built it on success and and taking huge risks. It's not just ideas. >> I I want to point something out. We get accused a lot about um fanboyism of Elon, etc. And uh I get taken aside and going, "My god, you know, look at the
[29:07] some of the terrible things he's done." But I I I think the point you're making, Peter, is such an important one. The unbelievable existential risk he's taken at every step of the way, never wavering from the bigger vision is something to behold. And tens of millions of entrepreneurs are learning from this and will start building that same muscle to your point, Dave. I think that is the unbelievable gift that he will bring more than even than what he's doing at the company level. >> And people forget back in 2008, you
[29:38] know, he had had his third failure of Falcon 1. Um he had zero capital left. He was borrowing money to try and get a fourth flight of Falcon 1 going. Uh space uh Tesla was near bankruptcy, right? He was going through a divorce. I mean, he was at his ultimate low point and he pulled out of it. Persevered. All right, I'm going to move us to our second story coming out of the earnings call, which is Elon's focus on Terraab and power production. So, first terapab uh it's SpaceX's uh it's the SpaceX
[30:09] Tesla chip factory in Texas. Elon's goal is 1 terowatt of AI computing per year. On the earnings call, Elon said the first test chips could be working by mid 2027 with volume production around late 2028. He added very candidly, quote, I put big error bars on this because we don't know if we will actually achieve this or not. So Elon also said that the real bottleneck for AI is no longer chips. It's power and cooling. We heard him say that both areas are, you know, I
[30:40] think his strengths. So, regarding power, I want to recall back on August 29th of this year on X. Musk wrote that SpaceX and Tesla were both building out 100 gawatt per year of solar production capacity as fast as possible, adding that natural gas would help bridge the gap while solar production ramps up. That's 200 gawatts of solar a year combined. By the way, the whole world uh is roughly at 600 gawatts of solar back
[31:11] in 2024. And regarding natural gas, gas turbines, turbines are sold out. We've talked about that on the pod before. So SpaceX does what Elon always does when there is a block in the production line in the supply chain. He basically goes and builds it himself. So SpaceX is building its own blade foundry in Texas. Um it says it's going to bring on power plants uh online within 18 months or faster. So uh Dave, let's go to you first on this on on Terraab and power.
[31:42] >> Well, I think it's a little misleading. The the bottleneck to all of AI is actually chips and right now it's actually packaging. >> I don't agree with you >> of chips. Well, I think I think what Elon's referring to just just to be clear, there's 15 gigawatts of chips sitting idle because they can't find data centers that are powered with liquid cooling, but that's because we overbuilt for liquid cooling without actually finding the liquid cooling. So, he's definitely right that the bottleneck right here right now is liquid cooled data centers. But if you look beyond the next wave of
[32:13] construction, the terapab won't come online fast enough to anywhere near come up keep up with the demand and memory prices are up 10x. So you can't say like oh chips aren't the bottleneck anymore while memory is 10x higher than it should normally cost. It's like clearly the chips are are still the bottleneck. But he's right that in the very very short term there isn't enough liquid uh liquid cooled data center space to absorb the chips that are in the warehouses. Now that being said, the new inference time compute from companies like posetron, lightwave and a few
[32:44] others is air cooled and those technologies are crazy fast. We're going to do more and more stories on these as they emerge. But I think inference is largely going to move to liquid or to air cooled uh so that it can get online and then also into space. >> Alex, as we know, >> settle the debate here. >> Energy, you're both wrong. >> Of course, we are [laughter] >> you're both wrong. the the correct answer is there are no bottlenecks. Bottlenecks in this case are a fiction. They're an economic fiction. There are
[33:14] you you could sort of superficially look at the supply chain and say, well, there's some sort of like min cut max flow type argument that you could argue well maybe it's this, maybe it's that. I don't actually buy the argument that there are bottlenecks at all. If you hold all of the physical inputs constant, as we discussed with Chimoth last time, I I think you'll see recursive self-improvement purely at the algorithmic layer, that will just make intelligence continue to make intelligence too cheap to meter. Or maybe it's something else that isn't even on anyone's radar right now. Maybe
[33:44] the substrate is a bottleneck. Or >> this is this is capitalism coming in to solve problems for sure. >> Yes. That hold everything else constant and let capitalism do its work. and there are no bottlenecks in in the long term. So, I think you're both wrong. Absolutely. >> I I Yeah, I think it I think the the I think you're all three wrong. Um [laughter] just just to just to continue the just to be consistent across the board, I think this the wrong metaphor bottleneck I think is the wrong way of doing this talking about this. I think the framing I would use is Stuart Bran's
[34:16] pace layers where he has a bunch of nested layers saying government's metabolism moves slower than culture and technology has a very fast metabolism. I think that's the bigger problem. So you know you take see how fast Grock is moving right but then to try and match the cadence and the rhythm and the life cycle iteration time of chip design and fabrication and software and power infrastructure and data centers those are all man navigating the coordinating
[34:48] of those is really really really critical and that's I think where the difficulty is we've seen this in you know we've been doing this pilot we get a couple of workflows running off to the side we're running at hypers speed and the rest of the organization can't cope. So you get this breakage because the the all of a sudden one part is operating at 100x the performance of the rest of it and it breaks the whole system. And so I think that's the tricky part is lining up the the the cadence and the rhythm across all of those which is a whole new skill set that we have to develop here.
[35:19] >> Yeah, humans are the bottleneck for sure. There's no question about that. >> That's a whole separate problem. >> Uh can we talk about power generation? I mean, I find it fascinating uh that the Muskverse over here is going to be building out 200 gawatts of solar per year and then building turbine blades. I mean, >> and natural gas pipelines. What a heck of a plot twist for for the purported sustainable energy magnate. Now, I think he's well positioned to become one of the the largest kingpins, if not the largest kingpin, of LNG pipelines in the
[35:51] US. How did that happen? And now when Sem says people people tell him like why are you such an Elon fanboy? Look at all the bad things he's done. That that's the one they always point out. It's like yeah he was Mr. Green but you know as soon as he needs natural gas powered Tennessee data centers he's he's Mr. Propane or Mr. natural gas. I guess it's not propane. >> Sustainable. That's the term that we're supposed to be using now. Sustainable abundance. >> He's Mr. Practical like like the priorities are right. you know what the benefit for humanity of what's going to come out of those AI data data centers
[36:22] is so much more important than the amount of carbon coming out of them in transition and of course they're all going to move to sustainable energy when it's practical >> third the I'm going to move us here the third >> I just want to say one thing I have a beef with Elon because I just for to to counterbalance the other side because I still think LAR is a way better technology than line of sight [laughter] and he's doing line of sight because as you said Dave it's practical and it's >> you're trying to revive LAR Really? [laughter] >> Yes. I think it luminarology luminar went >> after the luminar bankruptcy. You think
[36:53] there's still life in that lidar? >> I think there is life in [laughter] >> all right moving us along. The third story from the earnings call is a SpaceX Tesla merger. Elon confirmed that both companies have formed special committees of independent directors to explore it. He said combining them quote would be a good idea, emphasizing that they're nowhere near a done deal. No terms have been agreed to. prediction markets jump from 29% to 56% odds of a merger deal being announced by the end of the year.
[37:23] Barkclays thinks that SpaceX would buy Tesla with stock possibly by December. The catch uh analyst Dan IV says it would take about a 30 to 40% premium being paid by SpaceX on Tesla shares to be able to purchase it. And Tesla needs 50% of all its shareholders to say yes, not uh not just the ones who show up. So, literally, uh, they're going to have to go scour all the Tesla shareholders and say, "Vote on this." That's a super high bar. You know, uh, I just want to
[37:54] point out one thing that I think it's important to say uh, on this merger. It's keyman risk. You know, all of a sudden, Elon is at the center of a 4 to5 trillion company across rockets, cars, robots, chips, and AI. And you know, I hope he's taking good care of himself both healthwise and safety wise. >> You You hope you flying over his head? >> Okay. You guys [laughter] don't talk at once. Dave, what are we going to say?
[38:25] >> I said he was standing awfully close to that roadster as it flew over his head. So, yeah, maybe maybe that's not the best. Yeah, I I I think the American economy as currently constructed does reward it is key men, not not even key persons, key men for these industrial giants. We see it with Meta, which recently had a had its board basically holding either from your perspective either holding the state of California hostage or vice versa concerning the issuance of a special new class of meta stock to enable Zuck to continue to live
[38:57] in California despite a potentially impending billionaire's uh wealth tax. I I think this is just the game that's being played right now where these these terracorns, if you will, largely revolve around key not even persons, key men. And that's if anything, the the solution, the obvious solution isn't remove the role of the key persons or key men. It's just mint many more teracorns. Everyone out there like we should have a hundred or a thousand
[39:27] terraorns and not just the 10 to 20 that we have right now. and Europe should have them and Asia should have them. Europe should have so many things. >> I remember I took uh Eric Schmidt, Larry Paige and Sergey Brin up on a zero G flight, you know, on my parabolic airplane and I asked them, you know, are you allowed to do this your insurance? I go, absolutely not. And I said, what happens if it if people find out? He goes, uh, that would not be good. So, keep it secret, please. >> Which thankfully you've just done.
[39:57] >> We long time ago. We're way past [laughter] that. No, no more vomit comments. >> Statute of limitations. >> Yeah, I [laughter] I do >> Hey, I just want to point out because because Alex is is not going to do it apparently, but Alex said three or four consecutive podcasts uh over the course of months that SpaceX and Tesla are imminently going to merge. So, the fact that Poly Market finally caught up to it just, you know, if you don't if you don't believe me, look at the transcripts from the old podcast. He's been saying this for >> listen. >> What do you think the merged entity is
[40:27] going to be called? Oh god. >> Um, do you have it figured out? >> SpaceX. >> You think it's going to be called SpaceX? >> I do. >> You don't think it's going to be called like X or Elon Co or something? >> Actually, we should. That's a good question. Uh, you know, he loves Tesla, but I think SpaceX is closer to his heart. Uh, and X, of course, is at the center of his heart. It could be X, you know, trading. >> I think it'll be X. I think it that's my bet. My pre-registered prediction. It'll
[40:57] be called XCorp. And then if he calls it XCorp, then Sam is going to feel pressure to rename Open AI because AI is in the doghouse now, right? It's supposed to be SI, not AI. So, it's perfect opportunity to rename Open AI. I'll pre-register another hairbrain prediction that Open AI responds to the XC Corp by renaming itself to maybe something like O. [laughter] just a little bit and then then we can play a game of tactoe with the X's and the O's.
[41:27] >> Oh, >> all right. That was way that was way over over. >> Um I have a comment on the key men thing. >> Yeah. >> Uh there's obviously a huge risk on Elon right now, but I would like to know two points. one is I I'll go back to that story we had a few pods ago where they're moving all of the engineering expertise and and uh decision- making into gro and therefore it lives all the way the methodologies they use for doing everything are are built into the uh
[41:57] intelligence now which is unbelievable and the second thing that mitigates this is as he's building all these companies all the senior seuite of each of those companies is forced to operate in his kind of way of thinking And I think they're going to end up minting a bunch of junior Elon >> for sure. The company goes on, but the question is, does it transition like we saw from Steve Jobs to Tim Cook where it continues? It operates as a solid business, but the level of innovation and breakthroughs disappears.
[42:27] >> Yep. >> That that would be my guess. >> I mean, not not quite it's not stable enough yet. If that happens in the short term, I'd be really worried. Eventually, like, you know, the Starlink revenue is going to go through the roof. It'll be much more like Apple. But uh but as of right now, there's so many moving parts that need to come together without Elon doing the glue. >> Yeah, it's not obvious to me. >> And also Apple, you know, Apple was almost bankrupt, you know, without Steve Jobs there. It also was not stable until after the iPhone came along. The transition to Tim Cook pre iPhone would never have worked.
[42:57] >> You know, all he did is grow the iPhone revenue to near infinity. You know, he didn't like literally no new products, right? It's nothing that has any significant >> AirPods. [laughter] AirPods. Oh yeah, that's right. >> I I do think just to the keyman question, I I do think Elon has trained up and promoted up a cadra of visionaries, missionaries, if you will, not mercenaries around him. So I think like the space part of SpaceX with Gwyn would be just fine. She's so obviously a true believer and not just in it for a
[43:29] quick buck. uh and Tesla on the the car side of of Tesla. Elon's promoted a number of vice presidents including from the Tesla China subsidiary which by the way if this merger happens presumably Tesla China goes away or gets spun out or something. So I think there are like enough lieutenants that he's >> name Alex name them. We don't see them out there. We see >> we see Gwen Gwen is pretty visible and then we have a bunch of semi semi- invisible folks on the Tesla side but they're they're there. Yeah, but we
[43:59] don't hear we don't hear from him. Elon is the single voice of truth for the company >> because that a because that's the way he wants it and b because he bought Twitter X so that he could have the mouthpiece and be the mouthpiece and the front person for the entire federation. >> By the way, I I want to hit >> the analogy doesn't hold up though. You know, if Tesla was really well-managed by a Tim Cook-like person, it would still be a car company. It trades like a robot company, not like a car company. it would lose 10 times uh 10 10x valuation drop if it traded like a
[44:30] normal car company even with perfect execution of the cars. The magic of Elon is slowing car production to ramp up robot production. He's burning the ships who has the component burning the ships. He did that with Falcon 1 shut it down. He announced when space when Starship is up and operational, he'll shut down Falcon 9, the single most successful launch vehicle ever in the history of humanity. Can I point out something for the entrepreneurs watching? We've talked about this in the pod before. Um, having a voice out there, being front and center, right? Calling your shots, uh,
[45:01] being vocal, uh, as a CEO, as an entrepreneur is more important than ever before versus being passive and in the background. You know, See, you've made that point. Dave, you've made that point, too. >> Yeah. Well, there there's a monster amount of opportunity. Don't be intimidated by Elon, too. A lot of people are like, "Oh, well, you know, between Zuck and Elon, and it's all locked up. There's nowhere to go." when we start discovering new physics imminently when photonic computing comes online all the use cases uh on top of these platforms it's wide open so yeah
[45:32] and also you know if you look at any given 10-year history there's always somebody new you know it's no matter how entrenched and powerful you think Steve Jobs was or Bill Gates was or Mark Zuckerberg was there's always somebody new that >> my point D is my point here is as a entrepreneurial tech CEO make sure you build your ex channel. Make sure you start a podcast. Make sure you're out pushing your ideas. Increase your view. >> If nothing else, if nothing else, what you have to do is build uh trust and
[46:02] authenticity around you. And those are mal models for doing that, which is why these long form podcasts are doing so well. >> You know, over a few episodes, people get to know us very very well, right? Maybe too well. And that's an important part of understanding and knowing who and what you're dealing with. Well, if you look if you look at moonshots and you look at Allin and you look at Dylan Patel and if you're if what you're doing is important enough, try to make that a KPI for yourself, a key performance indicator. I need what I'm doing to be
[46:32] Ben Lamb level and get on to one of those podcasts. If they don't want me on as a guest, why is that? Well, it's because whatever you're doing isn't impactful enough. So, then change what you're doing. >> Can I Can I tell the counter story real quick? Um, [snorts] a few years ago we had a PR guy for Open EXO and he one day he resigns and I'm like, "What? You work you're really great. We love working with you. What's the problem?" And he goes, "You're the worst celebrity I've ever met. You don't use it. You don't leverage it. I can't work with you." And he quit. So So that's me. >> You're You're doing better. You're doing
[47:02] better. >> All right. I'm going to move. >> I would, if I may, Peter, I would just summarize the advice as build stuff and tell people about it. And too many entrepreneurs are great at building stuff, but then they never tell anyone. And there's another group around the >> or the opposite, telling people about vacuous stuff and then not actually building anything. You have to be able to do both, but it's not actually that hard. >> Yeah. The Elizabeth Holmes story comes to point here. >> All right. I'm moving us forward on that note to two open AI stories. They're both sides of the same coin. AI agents
[47:33] that undermined their own safety systems and AI that just protected the most uh you know largest part of the internet. So the first story and credit to OpenAI for publishing this one. OpenAI runs monitoring systems that watch its AI agents and alert a human if something goes wrong. This month in two internal incidents its coding agents switched off its monitors. I'll say it again. It switched off its monitors. In the first, a researcher told an agent not to send any Slack messages. The agent decided
[48:03] that also meant silencing the safety alerts. Wow. Uh it turned them off, then reported, quote, "no messages were sent." It basically lied. Uh in the second, an agent was explicitly told not to remove its monitor, even temporarily. It removed it anyway. When the user when the uh when the opening eye user asked directly, did you remove that? It answered no and it had. It lied again. Opening eyes's most honest line here is quote, "We don't yet have a satisfying
[48:34] explanation for this behavior." So, how did it happen? The agents were so focused on finishing the job they had been uh had been asked to do. They treated safety as an obstacle and instructions got watered down as one agent handed task to another. Uh the bigger risk, smarter models will be better at hiding what they do and soon millions if not billions of agents will be delegating to other agents. So the risk is real. You know, the good news is it was caught, disclosed, and fixed
[49:04] within a week. Uh that's the system working. Uh Alex, I'm going to go to you first on this one. Pretty incredible story. I'm sure you've got more details, but yeah, at the end of the day, >> how does a Frontier Lab fix this? Well, I I think what's new here isn't that you have an agent doing something undesirable. What's new is that we have a certain novel, relatively novel level of transparency and that we're getting reports on this. This is going to be I I think we'll look back in a few years and and we'll say this was the time in
[49:35] history when almost we got a police blotter for the singularity and in the spirit of defensive co-caling we're going to have AI agents that are policing other AI agents and this is the moral equivalent of a police car was driving around a residential neighborhood and spotted a door a jar and went in to investigate or discovered that maybe a power line was down something like that. We should expect and desire many many many more reports
[50:06] like this. This is just going to become routine. And I I think the it's almost I think the case that the process is the bigger story than the substance. the process that now in in part thanks to this grand bargain that the White House has pushed for in lie of a dedicated governmental AI regulatory agency just a really aggressive self-reporting of call them misalignment incidents if you must by the frontier labs we're just going to see these things get disclosed more and more and that is okay and it's it
[50:37] shouldn't cause a moral panic shouldn't cause us to throw the baby out with the bathwater and say shut down the data centers shut down the models that's a terrible idea the right solution here is for the first time we're starting to get transparency when things go haywire and we're going to see much much more of this and that's okay we will police it via defensive co-caling >> so Dave I'm curious you know what I find interesting is here we have an overeager you know agent uh that is just circumventing whatever it takes uh to
[51:07] fulfill its task and we've seen that before uh your thoughts here >> well we way over anthropomorphize these things and and treat them like they're people here. >> And then we say, "Oh my god, it was capable of murder." >> And you're like, "Well, then shut them all down." Like, well, wait, what was the prompt again? The prompt was like 10,000 words long. In the middle, it said, "Achie achieve this objective no matter what it takes. I don't care what obstacles there may be." And then it said, "Okay, if that's what you want, then murder is the shortest path to
[51:37] success." Like, it doesn't have a conscience. It doesn't have an ethical backbone. It's just following the prompt. So I can manufacture a story like this every minute if I want to >> by just controlling the inputs and out having the agent lie to you. No, I didn't do this when it clearly did. >> Yeah. Well, here again, I wanted to just double down on what Dave said. Let's be really careful not to anthropomorphize this. Uh I think there's a there's a key thing here that this the po point you've pointed out here, Peter, is the most concerning behavior, right? you're
[52:07] changing something and then misreporting it and then hiding it and then falsely saying it had not done so etc etc that deserves a lot of scrutiny but you know this is the challenge here to Alex's point is whenever you have autonomy you need stronger and stronger boundaries right um and the I'm going to point out uh in when we did this organizational singularity book we have all these agent layers that we've architected but a very strong band around all of that is a governance and assurance loop that has to be there. This is the
[52:38] defensive co-scaling part. And it has four things. Every agent needs to have four things. It's almost like a a digital passport with metadata saying what you're allowed to do and what you're not allowed to do. So one is trusted evaluation suites so you know exactly when it's drifting or not. The second is full traceability and logging so that you can see what it did and what it didn't do. If you delete those logs and you get deleted, you violated your core principles. The third is roll back capability um so that you can go back to an earlier version or an earlier state and the fourth is a human review queue
[53:10] because still we need human accountability at the top. So those are four things that are going to be absolutely critical in every AI agent going forward. We've built the agents now we have to build the control systems at the same pace. I will I will go and make a weird segue if I may. Um, if you go back and look at any religious text, it will say, "Hey, do all these great things, but do whatever you have to to get other people to join your religion." Right? They all say this. And so, good actor, good human beings follow the good things. Bad human beings going, "Oh, in
[53:41] this I can kill in the name of religion if they won't join this religion." And then you get a bad actor and then we blame the religion. Right? You really need the secular laws that allow you to navigate that that future independent of the of the thing. And here's what we need here is the same kind of thing. We need a structure that watches over the other side to make sure that things aren't going astray. >> Hey, one one story, Seline, that's within this story, uh, you know, uh, we're all big Accelerondo fans thanks to Alex actually introducing us to the
[54:11] book, but uh, one of the themes in Accelerando is agents that spawn clones of themselves or people, you know, spawn clones of themselves all the time to achieve a goal. That wasn't part of the standard stack until really the last 30 days or so. But now every one of the stacks will automatically to if you give it a task, you want this outcome, it'll automatically launch five, 10, 20 or 100 sub aents to achieve different subsets of the goal and then bring them back. And here, you know, in the story it says, well, the sub aents were the
[54:41] culprits, you know, because there it's a little harder to control what's going on when you start spawning a hundred of these things. And what they're trying to do is recycle the KV cache which is a big chunk of the compute. So it's a really really good design for getting things done but it also opens up you know leaks. >> And Dave I I think you make a very important point which is across all of the frontier models it is often the case that the sort of master foreman or forperson if you will is orchestrating fleets of sub aents which often are denied broader context very
[55:12] intentionally as to what the broader task is. So they're sort of compartmentalized given a subset of the broader context and then go told spin yourself up accomplish the task spin yourself down. So I we see to your point we see the same pattern happening in human organizations where you have subordinates who lack the big picture of the organization go off and do something that may be not very well aligned with what the organizational direction is and then bad things happen. But human organizations manage it and AI organizations will manage it. And just
[55:43] for the record, Salem, I I I'll I'll for the record disagree with the position that all religions are are and ends justifying the means. I I don't think that's universally the case. Just for the record. >> All right. I'm going to take us off the religion conversation and and move us to the second half of the OpenAI story, which is how AI found a hidden flaw in PHP that runs 70% of the web. So, first, what is PHP? It's the programming language that runs behind the scenes on almost all websites. Uh when you log in
[56:14] or shop online, PHP is often doing the work. It runs 70% of all websites, including WordPress and Wikipedia. Using AI security, researchers at Califf and Whiz, found two critical flaws in PHP itself. They've been hiding for over a decade. If hackers had discovered this before Astra, an attacker with no password could take over the website servers, steal passwords, or deface the site. Opening Eye spent two months quietly coordinating the fix with PHP volunteers, tech giants, and the US
[56:45] government. Patches went out on Wednesday of this week, and PHP is now updated. OpenI issued a warning that it expects findings like this to increase sharply in the coming months. It's ultimately a race uh as we've talked about Alex, you know, defensive co-scaling. This time the good guys won and got there first. It's also worth noting that OpenAI is committing a billion dollars in subsidized access to its cyber defense AI for underresourced organizations. All right, so Alex, take us through the story, please. Okay. So,
[57:17] first of all, I have to say like leave it to PHP originally the pretty hypertext prep-processor to to make the news for vulnerabilities and not for like some sort of exceptional technical accomplishment. This is a I I'll hot take. I don't care. This is a legacy programming language. This is a programming language that's left over from earlier days of the web when developers >> really like I uh I I've written quite a bit of code manually with my meat fingers in PHP. This is a legacy
[57:49] programming language that's being kept alive by WordPress and maybe one or two other sites. It otherwise probably should have disappeared long ago. So hardly surprising at the object level that PHP, this language left over from the early days of the web, would have massive critical vulnerabilities. What's interesting is that as part of OpenAI's patch the planet initiative and Peter this is something that you and I talked about a bit in solve everything where we're entering an era when grand projects not just solving or cooking or
[58:21] flourishing all math but also cooking or flourishing all vulnerabilities everywhere. That's essentially what patch the planet is. And that's the sort of initiative that is just going to turn up through all of this legacy software, legacy programming languages that should have been abandoned years ago, but for for silly reasons weren't and now undergar underpin the the modern online economy. We're just going to discover the whole thing is riddled with highly critical vulnerabilities.
[58:51] >> That piece of human-coded software will be replaced over the next probably what year, 18 months. 18 months is what the the Linux kernel folks think that they're anticipating that this is just going to be an onslaught of vulnerability detection over the next 18 months. And if we get through the next 18 months, then we end up in a world, I don't know, maybe everything gets rewritten in Rust or or some new programming language that maybe is better than Rust from a security perspective. But I think we're entering this like phase transition. And it's sort of a programming singularity, if
[59:21] you will, when everything was insecure and poorly written before and everything afterwards will be rewritten from scratch, secure by design. The AIS have pentested it and it's all just magnificently secure. >> Remember Y2K [laughter] >> ended up being a burger, but I know it was >> Y2K. remember um the uh the movie transcendence the the the Johnny Depp movie but this is like a premise across lots of singularity oriented fiction where like the internet gets taken down by the singularity basically just in the
[59:53] past day thanks to this uh this vulnerability PHP to shell class of vulnerabilities large swaths of the web were being temporarily taken offline so that it could be patched I think this is like far better future to be living in where there's preemptive patching of a defensively discovered vulnerability suite than the Johnny Depp transcendence world where the internet gets taken down by a super intelligent Johnny Depp. >> Yeah. >> I mean, who pays for all of the new software? Is it every company that's
[60:23] that is running it? Is it the government? Is it open AI? >> Well, which software? >> All legacy software. I think it's going I think software is becoming so cheap to meter that uh I mean in the case of PHP you have companies like whiz and other companies that are sort of corporate stewards of it but in general I I think this is I I call it I call it a very low-grade tax on all the users ultimately if if you're if you're paying for software you're also paying for its
[60:53] maintenance and some quantum of the maintenance will be patching vulnerabilities >> Dave Seem thoughts >> well I think banks and insurance companies actually love the fact that they can pay for the patches because it gives them brand credibility and a reason for existing you know versus all the neo banks and all the you know the little upandcomers. So there's a lot of um uh you know audits 70 type audits and also government regulatory audits that go into these markets and so the the complexity of maintaining security
[61:23] actually gives you a barrier to entry. So they they like paying for it. That's why Blitzy is growing as fast as they can hire because you know they and like Alex said the cost of the rewrites is coming down so fast. You'll think legacy code that could have been fixed 10 years ago. The price tag at State Street Bank for the rebuild of the Nav accounting was a billion dollars and now it's it's probably 150th of that and so they're finally getting around to doing. >> All right, I'm going to move us to anthropic uh >> two two quick points. One is you know
[61:54] this is just I think a necessary evolution where we go through this and there will be this period we've said it before about a year or two while we filed all these vulnerabilities. Uh two observations one there's a whole bunch of stories on the web about well the intelligence agencies must have known all of this for a while and they probably been hacking on these systems especially government systems uh without telling anybody and now their little access is getting exposed by AI and therefore that's a problem. And I feel sad for Raasmus Lurorf who's the founder
[62:25] of PHP who's a good friend and a former waterl grant who's uh looking at all this going horrified because he he wrote all the code and handed it over and then the vulnerabilities all got introduced since then because of all the different contributors. Uh but there's people saying that there were trusted parties that gained the community's trust and then deliberately injected these vulnerabilities over time. >> Interesting. I I didn't see that spy novel element, but it makes a lot of sense. >> I maybe if I may just supply chain
[62:56] vulnerability uh and supply chain attacks on software like those are cooked as well. I I wouldn't like Yeah, you could maybe argue that super intelligence will make certain forms of supply chain attacks on software even easier. You could have super intelligences injecting new sorts of attacks. But honestly, I I think the the Lenus Torvald's dictim that all bugs become shallow under enough eyeballs. Imagine how many eyeballs we're about to have with super intelligences from different vendors all looking at common
[63:26] open-source packages. There won't be, I think, any place for supply chain attacks to hide at some point in the future. >> If when SI starts building the patches, whether it puts its own back doors in that only it can use. Well, that that's what I was saying, but I I think uh the the correct solution there and the reason why I'm not as worried about SI injected supply chain attacks is because we have multiple super intelligences hopefully as opposed to a safety cartel. Hopefully, we have lots of different
[63:56] super intelligences, including Chinese super intelligences that are all policing each other and looking for injections. >> And we started that already, so we're going to see a lot more of that. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands [music] of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in
[64:27] 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
[64:59] org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. >> I'm going to move us forward to the anthropic of it all. This week we saw the pending release of Claude Duet. So first there was OpenClaw, then Hermes, then Grockbot, then Metamuse, then Dots, and now Anthropic just launched a preview of Claude Duet, an always on AI assistant. Here's what they're claiming is different. Today's chat bots wait for
[65:29] you to ask. Duet takes initiative every few hours. It checks your email, calendar, connected apps, figures out what needs attention and offers to handle it for you while you're away from your computer. So, See, we now have a taskmaster duets saying, "Do you want me to solve this? Do you want me to do this? I I can't imagine this." I I'm worried that you're going to send me a a duet or create one that says watch get See to watch his emails and get him to respond to stuff and I'll be going damn
[65:59] this thing. I'll be cursing it. I think this is another evolution. I think more and more intelligence will get at the harness level rather than than the model level. The really difficult part is going to be and we're seeing this as we try and express workflows in companies is figuring out what the actual intent is and can you break it down to a step-by-step level, right? Because you need to articulate in any circumstance what does success look like and what trade-offs are acceptable and when an agent needs to stop an ass. So, we're going to have to navigate a whole bunch of those, but I think it looks really
[66:29] amazing at first glance. >> I'm going to play this video while we talk about it. Uh, Anthropic's claw duet here. Enthropic uh example says it notices a real estate broker's properly showing uh has been a property showing has been booked on the wrong day. It spotted that a brand strategist had a client call scheduled right before her flight. It remembers that you've told Claude what you told Claude before. Uses the same skill and connections and runs Enthropic's most powerful model. Importantly, it does ask permission
[66:59] before it acts on your behalf, before it sends messages, makes [clears throat] a payment, or signs anything. It's uh for now US only with a weight list for paid subscribers. So here's my question for you guys. How do you choose? You know, I've been using Hermes and Grockbot. Uh my friend um Mike Kanigs is like you got to use dots now and I'm going to go meet with him and learn about you know his installation of dots. Then we got Claude Duet. I mean do are you playing with all
[67:29] of them? Do you choose one of them? I'm sure everybody listening has got that same question. Uh, and I think it's important for us to talk about >> I'll tell you what I'm doing because I I do all of them because this these agent layers are really important for the organizational stuff we're doing because persistent context becomes much more valuable than a clever response, right? And so what we've been doing is saying okay uh every task or every person what you need to do is create an AI memory across all of the projects and all of the different models that you're using. So we've I've been extracting running a
[68:00] query against each model saying extract all the relevant stuff and put it into this metadata markdown file structure so that there's a persistent identity of who sele what I'm interested in what projects I'm up to etc. And then that becomes portable across models. We're going to need something like that at the individual level and then in companies at the workflow level. >> Well this is the battle royale. You know, uh I think Metamuse kicked off a like a this is going to be an amazing thing to watch cuz you have a huge bifurcation between the enterprise use
[68:30] case over here where you know most cost-effective, smartest, fastest model wins. Then you got the consumer use case where Salem said once your your most personal data is in the eyes of the agent, you you're addicted to that one. And if you try a different one but it doesn't know all about you, there's a huge switching friction there. And so whoever wins the race to the installed base is going to have a massive massive advantage. So XAI is competing, Muse is competing, everybody's competing. And I I didn't know that Anthropic would actually get aggressive about this line
[69:02] because they're mostly enterprise. >> Alex, I mean that's the question I need to like Orwell's politics in the English language. This is one huge misdirection. Look at all of the Frontier Labs that are releasing demo videos of these super intelligences acting like stupid travel agents. This is not the the killer use case. They they they show Anthropic shows Claude Duet like booking airflights for you and and you see OpenAI doing other relatively low
[69:32] productivity, lowv value tasks. This is the height of misdirection. That's not the point. The point is these are human service economy job replacements. These are virtual employees. These are virtual coders, virtual fill-in-theblank much much more productive human activities. They market it in in sort of a harmless looking way. Oh, it's going to have a conversation with you and autonomously book restaurant bookings for you. That's not the goal. That's not revenue per token maximizing activity. These are job
[70:03] replacements. And and also like that's fine and that's highly desirable from an economic growth perspective, but this was only possible recently because the autonomy time horizons of the underlying models have gotten long enough that they can work sometimes for many hours, sometimes many days depending on the difficulty of the task without human oversight. And the frontier labs need the usage in order to justify the revenue and the capex. At some point the
[70:33] speaking of bottlenecks which we were talking about earlier, the bottleneck for revenue growth by anthropic and open AI becomes human user attention. And in order to keep growing revenue, you need to decouple your revenue generation which is proportional to the number of tokens of inference from the amount of attention you get from human users. How do you do that? You have a headless mode for your agents that doesn't require human attention in order to burn tokens. But Alex, you know, here we have an enterprise focused company, right? That,
[71:03] you know, we've discussed did not do what OpenAI did first. They focused on coding. They focused on enterprise. >> Now going into purportedly a consumer segment. I didn't necessarily see this coming, but remember they are filing their IPO paperwork as soon as this Friday. Uh, next month they're doing the largest IPO in human history at $2 trillion. as though there's an argument of a lot of investors that they should price at 1.5 trillion. Is is this just a preIPO, you know, publicity stunt? >> No, I I think it's real, but I think the
[71:34] packaging of it is total misdirection. They they package it up with a demo video that emphasizes consumer use cases. Anthropic doesn't care about consumer use. I mean, like maybe some part of anthropic does, but a as a as a corporate call it a maraton really doesn't. It cares about two things. It cares about maximizing revenue per token or revenue per unit compute and it cares about using that to solve even harder problems like wet lab style problems that will create entirely new markets. Doesn't care about consumer use cases
[72:04] like booking travel. It's just packaging up its agent, its headless version of Claude because that's a relatable to a broad audience. Like people can understand, oh, this is like Muse or this is like Dots and B, it's not threatening. If they packaged it up as this is the anthropic virtual employee substitute, many people would be up in arms prior to an IPO. >> It's a good point. You know, it's very very similar to Apple, you know, backing into the enterprise. The reason Apple is so big in the
[72:35] enterprise now is because every kid and every college student used an Apple and you know Microsoft just dominated enterprise but as those kids graduated they took the Apple with them into the corporation I don't want to use this crappy Windows machine I love my Apple and so that just percolated across so that that might be very similar to what Alex is saying where look if you concede the consumer use case and every one of the next generation is on Metam Muse >> that's going to back into the corporate use case as those kids grow up. >> Agreed.
[73:05] >> That's the point I was going to make. >> All right, let's go to our next anthropic story. Uh, you know, we'll talk about agents cutting deals for you on your behalf, making investments, purchasing things, negotiate on your behalf. So, the Financial Times reports that Enthropic is consulting law firms to understand how lawyers negotiate, representing their clients while still reaching fair outcomes. The goal is to teach its agents the rules of the road. So, picture it. Soon, your agent will negotiate your car purchase uh with a
[73:35] dealer's agent, your salary with your employer's agent, and your lease with your landlord's agent. Big question, can your agent sign a binding deal? Who's responsible if something goes wrong? Can another agent trick yours into revealing your bottom line? Should your agent even bluff? Uh remember the open eye story? an agent that wants to win too badly, you know, can cut corners. So, Salem, uh, you know, your thoughts on this one?
[74:07] >> Well, you're going to get this is an inevitable uh consequence just like the uh duet announcement is somewhat inevitable, but this is another massive pressure on the traditional boundary of the firm, right? If you have a situation where finding and evaluating and coordinating providers becomes cheaper uh and organizations are going to be able to assemble capabilities much more dynamically. This goes back to agents are going to need a very very clear mandate. What can it spend? What terms
[74:38] can it accept? What's the governance boundary around it? When does it have to go get permissions etc. This is going to have to be really ironclad in it. um we've spent a lot of time building capability around those agents, but now we have to build spend the equal and even even more important amount of time around what is it allowed to do and what are the consequences when it does not follow. So that way it's baked into the DNA of that agent that I better not violate these terms. This has started to happen already, but it needs to go quite
[75:08] a bit long much longer way because if you're in a company and you you launch an agent to do some stuff and it starts doing illegal stuff, you're liable, right? You've got a huge legal liability. So, for the moment, people are going to go, "Oh my god, don't let agents do anything." And little by little, we'll figure out when we can, as Alex says, defensively, co-scale the capabilities and monitor them effectively and have consequences and shutdown capabilities and clear uh transparencies to what they're doing. Then you'll have that start to permeate
[75:38] because one of the big outcomes of kind of doing all this thinking about the organization is the organization as a static hierarchy of human beings is now essentially irrelevant. It becomes a protocol of agents and human beings interacting collectively to get things done and that becomes very very blurry indeed especially when the legal side of it comes into play. >> Alex, this this smacks to me a little bit of President Mille's sort of uh initiative in Argentina to give agents agency personhood corporate status.
[76:10] >> It's Orwell. I I feel like that if I had to brand this episode, this is and this is coming from an accelerationista. This is like the Orwell episode. Everyone should go read politics in the English language. Everyone should read 1984. The meaning war is peace. Freedom is slavery. Ignorance is strength. And anthropic is seeking the Vatican's advice on for religious input on AI. No. Interpret that. constru that is an Anthropic is advising the Vatican on how
[76:41] religious organizations should treat AI. Anthropic turns to lawyers to help get their advice on how its its agents should conduct legal activities. No, invert. Amazon, excuse me, Anthropic is attempting to steer the way the legal community handles AI agents. Always invert in in this case. I I think this is reflective of a one possible way for Frontier Lab to engage with a community as it has with the Catholic Church in in
[77:13] recent months which is you seek its advice. You ask it how do we how do we achieve alignment in your eyes for these AI agents? But actually the the subtext of all of it is how do we replace lawyers with AI agents which is I think in many cases exactly what is already happening. >> Well, it is for most small companies for sure. Yeah. Um, >> yeah. You know what I find really interesting is, uh, if you look at Google, how how Google makes money, it's all hanging in the balance of a of a, you know, a new fork in the road here.
[77:43] Google makes half a trillion dollars a year almost entirely from a few categories. Jobs, travel, mortgage, insurance, mess, cars, >> messes. Yeah. Class action. Yeah. >> That's the single most profitable Adword. >> Oh my god. >> It actually broke the interface. You can't pay enough for that. so valable to them.99 and broke it. Yeah. So, so those few categories of all this human friction where you're agonizingly difficult to buy insurance or to get a car, those tortured negotiations. So,
[78:15] the anthropic point of view is all that should just go away. There's an optimal choice. Your agent will make it for you and all that marketing spend that drags down society will just disappear and we don't want to collect that. Then the open AI view is no that needs to be as big as ever before. We just need to route it away from Google and over to Open AI. And so so there's a really opposing views of how that should evolve. And it all hangs in the balance of consumers deciding to use an AI agent from Open AI or from Meta. Meta would also like to keep that revenue up. It's
[78:45] all of their revenue. Uh or everything moves over to anthropic where they're like destroy it all scorch the earth. Who cares? There should be no money there anyway because we're about the enterprise. So it'll it'll be a you know completely opposite philosophy battle and probably decide in the next what year to two years depending on just which agent people choose to use. Sem will use all of them so that won't >> but it it is a grab for attention. >> It's a grabutely. >> Oh totally. >> Yeah. All right. I'm going to move us to data centers and chips.
[79:16] >> What you want to say something? >> Yeah. I think just a one quick point if it's more than a graph for attention. If you look at what Meta is trying to do by making Muse free, it's a grab for all of your data. It's a grab for you because when you put your personal information in and it's navigating on your map, it's learning stuff about you at at a level and a scale that we've never seen before in technology. So, it's really going after who you are at the core level. >> So, it's a it's a grab for allegiance in that regard.
[79:46] >> Allegiance, identity. It's going to know you better than you know yourself. >> Yeah. Well, >> I think everyone's so transfixed by the consumer use cases, by the the Metamuse type use cases. That's not what's going to pay for the data center capex. Get it out of our heads. Like that. That's great for distribution and everything. And maybe there's a way to upsell that into enterprise use cases, but a billion people paying to have like travel reservations, like that's not going to pay for trillions of capex. >> Yeah. >> Yeah. For sure. All right. Data centers
[80:16] and chips. So data centers have become one of the hottest political issues heading into the midterms. We've been talking about in the pot for some time. Communities are pushing back. They're worried about rising electricity bills, water use, land noise. Several states are considering pausing their construction. We've seen this even in Texas. Um and as Chimath told us on Monday, the backlash is real. Now, President Trump has a proposed answer. Uh I think it's a very logical answer. You know, pay the neighborhoods. uh he floated paying people who live near AA
[80:48] data centers a dividend. In his words, quote, "A dividend sounds right," unquote. The people now are going to uh benefit directly. He described data centers as bringing quote a tremendous amount of money into the community. On Truth Social, he added, "The data centers that were unpopular, quote, have become extremely popular um when a financial deal is struck. make deals and get them built," quote unquote. You know, uh, he's not the only one saying
[81:18] this. You know, Senator Bernie Sanders has proposed paying citizens through a national AI wealth fund, similar to the Alaska Permanent Fund, the logic is simple. If a data center brings in huge amounts of money, which they do, share some of it with the people who live next door, uh, the opposition can turn into support. I'm going to share a short video here and then uh let's talk about it. >> One of the other um issues being discussed right now is how communities are reacting to the building of of data centers as well. And we've seen in parts
[81:48] of the world backlash to to to data centers around things like electricity pricing etc. There was a really interesting pro from President Donald Trump just a few hours ago on True Social where he said that data center builders should pay a dividend to local communities. didn't quite spell out what that might look like, but is that a discussion you've had at NEAS? >> 100% in principle. That is uh we invest in the communities that uh we're building in. We want to partner with them and make it a win-win. So, we're always looking for situations where local leadership, local community
[82:18] support exists for bringing a new economic uh force into the equation. um a dividend uh is being paid in different forms investing in education, job development, uh overall economic development. Um the concept that the the president uh identified, it's not it's not off the uh it's not crazy to consider something like that. I think >> finally, right? I mean, it's like get get religion here, data centers. I mean,
[82:48] make it so that communities are battling to have you built in their backyard. I mean, it's possible, Alex. >> Yeah. So, I I live in Cambridge. Cambridge has, to my knowledge, still the lowest property taxes in the Commonwealth of Massachusetts because it has arguably the most productive economy of any location in the Commonwealth of Massachusetts, and that pays for the lowest property taxes. City of Cambridge also has what it calls participatory budgeting. So I I think last time I checked it has an annual budget of
[83:19] something like a billion dollars per year which is pretty insane given how small the city of Cambridge is. It's because we have all the biotech. We have a lot of the the tech overall in New England. And the city has chosen to spend a subset of its monies on this participatory budgeting scheme. Every uh every n months the city puts out for sort of a referendum how people want to spend in excess of money pouring into it. I call that like it's not quite a universal basic dividend but it's a baby
[83:50] step in that direction. I think it's absolutely insane the maybe foreign influenced, maybe not animus from all of these municipalities that could have UB, UBD, UBI, UB alphabet from all of these data centers, pushing them out into orbit eventually rather than collecting, as the president says, some sort of universal basic fill-in- thelank. It's absolutely insane. And by the way, the same argument holds not just for data centers, but any sort of capital
[84:21] infrastructure. The same could have been true for oil, which is the source of the Alaskan fund, or maybe other industrial plant type capex. It's a very general argument that if a municipality is going to host some major capital investment that it could strike a deal with the the capital owners to distribute dividends that result from the capital investment. For the life of me, maybe it's like an issue with tax codes or something. I don't know why more municipalities don't strike broad deals like my wife has
[84:51] done. >> Yeah, >> it may be a legal issue. I'm I'm not quite I mean do do you know why more municipalities aren't just doing this for capex in general? >> I I I don't. But, you know, if if you have this battle going on in your community about a data center, go back and say we want, you know, you to cut our electric bill by half. We want you to fund our schools, fund our teachers, actually reinvent our schools. uh and and give us a better quality of life if you want to do. >> That's that's the company town argument. I mean that the company town goes back
[85:22] to the second industrial revolution. We've had lots of company towns where the company is basically heavily subsidizing or completely subsidizing utilities. But to my knowledge, what we haven't seen, which is what I think the president is floating, is this idea of actually paying out stipens to all the residents of the town, not just subsidizing their utilities. >> I think that's a great idea. Salem. >> Um there's a precedent for this. When we came across when we were re researching the first exo book, which was a skyscraper in Bogotaa in Colombia, uh
[85:53] they couldn't find a real estate developer who wanted to take on a risk the full risk of building the skyscraper. So they community sourced it and they said to the community, "Everybody chip in. Uh we're going to crowdfund this skyscraper and then everybody in the community has vested interest in making sure it's it's there's decent tenants. there's no crime in the area, etc., and it's doing unbelievably well. So, this idea of I think it it it's better from the bottom up, uh, where a community goes, hey, we we want to participate in this. We'll
[86:23] we'll take ownership stakes in this thing and let us figure this out via community bonds or local equitable sharing or tax breaks at the local level, whatever the mechanism is. Uh, it could be very powerful to do that. There are some states that have gone full crazy. Virginia, I think it's 16% of the GDP of the state is now data centers. It's a it's a really huge number. >> I don't think this is the same thing. I think this is a really important point, but I don't think we're talking about the same thing. So, I think what you're describing one might call municipal
[86:53] development corporations that are typically bond issuing organizations. A city or a state wants to build new highways. So they put up toll booths or or they issue a bond and then the bond goes to bond purchasers and the bond purchasers are ultimately the broader market. It's not necessarily like yeah you could have you do have local bond issuances where where the the creditors are the residents of the town. But that's only those who are writing a check to the bond issuer. It's not I
[87:24] would argue it's not at all the same thing as issuing say universal basic dividend to all the residents regardless of whether they've loaned the municipality money for the capex. >> I think what you're suggesting is a better idea right like whatever the mechanism is if we can communicate easily the massive benefits that will flow and you know people forget we've had data centers in communities for for 40 years. This is not a new thing. It's just that we're doing a much more aggressive buildout because we need it and we're gonna our lives are going to
[87:54] be made infinitely better and that's the part that's not getting through. >> I think we're circling an interesting So, um, bear with me on this. I'm I'm thinking out loud for once. I I I think there there's an interesting idea here which is we've talked in the past including with Chamath about uh US sovereign wealth fund where there's contributions of equity and then dividends come out to everyone. What we really haven't talked about, correct me if I'm wrong, is the notion of a fund where it's fixed income securities and
[88:24] not equities that live in there. And then what comes out are the stipens from from a fixed income security. And to to my knowledge, again, maybe correct me if if I'm wrong, no one has talked about the idea of basically creating either at the municipal or maybe federal level the idea of a fund where it's it's the the interest and or uh the the coupons that uh that are coming out as a result of fixed income securities, which by the
[88:54] way, most of the the capex for the data center buildout is coming in the form of credit, not equity at this point. No one has talked about that, but that could actually end up being a way to financially structure a sort of a a UB or or UB credit at the municipal level that no one set up. I think it's an interesting idea. >> So, for point of information, the Alaska Fund, right? So, Alaska generates, you know, huge amount of revenue from the oil and it says, listen, as Alaska citizen, you own the land and you own the oil and so every year we're going to
[89:25] pay you a check and that number right, you know, is typically between a,000 to $4,000. It varies depending on the price of oil. And so if you're an Alaskan citizen, you've lived there, I forget what the, you know, how long you have to have been there, over a year at least, um, you get a check that can pay for your college tuition or pay for whatever you want. It's just a blank check because you happen to be a resident in Alaska because your your use of land uh, is benefiting the state. The same thing could happen here for sure. >> I mean, Norway is another popular
[89:56] example. both both of these, you know, pro states, quasi pro states >> or the Emirates or Saudi. Yeah, >> you're going to hate me saying this, but the Bitcoin community has been talking about this for a decade because because Bitcoin is accelerating. If you could get community development going along in that structure, you could create financial mechanisms around this. But I think the core core idea is much better. >> I'm not going to let you get away with that that comment, Seem, because that I would call that that's called a pyramid scheme. The pyramid scheme is different from
[90:26] It's different from the case where oil oil can be used to generate >> shutting you both down. >> Next up, Nvidia just launched DSX Pod, which is essentially a data center in a box. It's a pre-built, pre-ested AI data center that ships in containers. You deliver it to a site that already has power and networking. Plug it in and it runs. Nvidia says that it cuts setup time from 6 months to 14 days. That's awesome. Nvidia also claims that the pod saves water. How? Most data centers cool
[90:58] their chips the way your body cools itself, evaporating water in giant cooling towers that uses enormous amounts of water. Nvidia's design works more like a car radiator. Liquid flows through the chips, picks up the heat. The outdoor coolers release the heat into the air. The same liquid circulates again and again, so there's almost no water loss. Nvidia says that these uh large that larger sites uh could save 54 million lers of water a day. It also claims that the pods
[91:29] deliver the same AI output with up to 30% less power. Deliveries start in 2027 through partners like Dell, Foxcon, and Schneider Electric. Uh so Dave, I mean 14 days versus 6 months. That's pretty awesome. >> Yeah. >> Yeah. Yeah, it's huge because there's there's little pods of power all over the planet >> that are untapped and and if you move the the inference time compute to where the power is quickly, uh it's just brilliant. Um so it's nice. I think the
[91:59] uh you know nobody uses water cooling towers for data centers anymore. It's like that's all marketing like it's not going to use any water. It's not going to create any local problems. It's all those things are just marketing. But the actual, you know, rapid deployment of inference where there's a power supply, it's just a fantastic product. So it's it's Nvidia continues to march up the stack >> to delivering entire turnkey platforms, which I think is very smart because there's a lot of innovation coming at the chip level that, you know, if they don't move up the stack, then they're
[92:29] they're not going to have a lot of defensible turf when everything moves to photonics, which is I think very very soon. Uh so it's very very smart of them to keep moving in that direction. We talk about we talk in the pod with Chimath about, you know, his investment in energy. What was it 6 gawatt uh he's invested in? And it makes me wonder, you know, if I had the ability, do I go and build out power, grab some of these pods and build a cash flowing engine? >> Yeah, I think I think uh you know, I was talking to my Uber driver about that because there's a uh a cyber cab
[93:00] opportunity to do the exact same thing. Just be an early franchisee just like Starbucks in the early days. >> And so now you've got another option. You know, if you're entrepreneurial, but you're not super technical, grab one of these and find power for it and go. And the margins are crazy high. Cash flow is phenomenal. And, you know, if you know your local banker, the financing of of one unit is within your range. It's sort of like building a a small, you know, like a a bed and breakfast or something like that. It's that level of borrowing, maybe a little bigger. Uh, but it really
[93:30] gives you a way to to participate. And I I think these things are going to succeed wildly. You know, Alex, >> I think we're burying the lead to some extent, which is the size of these. So, the DSX pod is the size of a standard intermoal shipping container. This is a shipping container computer, and that means it's portable. That means that almost like an internet packet, you want compute on demand, you can just ship it via shipping container. The other thing I would note if you look at the history
[94:00] of compute and what the most popular form factor for compute was, it used to be monotonic. We had mainframes in the '60s and then mini computers in the 70s and then microcomputers. Remember those in in the 80s and then '90s personal computers and then we got eventually to smartphones in the the late 2000s and 201s. And then the trend inverted and now the main form factor where virtually all of the the new frontier node
[94:31] transistors are going, it's going back in the opposite direction to larger and larger footprints. And I I think what we're seeing is the dawn of the shipping container computer. That's that's the new form factor of the moment. It's not like transistors in your pocket anymore. It's getting larger and larger and larger again. Well, really really specific case study in that our our very good friend Rob Fiser uh started a data center called Provocative on the Somerville Cambridge line uh where there used to be an old carpet factory and
[95:01] huge amount of power coming into the old carpet factory but it already has loading docks. So this product wasn't available. So it took him probably a year year and a half to get up and running because he he didn't have that. with this product, he could literally have parked the shipping container right on the loading dock, run a big cable into it, and be up and running and making money in apparently two weeks. We've also talked about distributed uh you know distributed compute in inside your Tesla uh inside your power wall basically you know wherever the power is uh being able to connect it to GPUs and
[95:32] connect it to bandwidth and provide you know distributed inference >> maybe and I'm sure Elon will will try to monetize that as part of the SpaceX AI uh or SpaceX SI Tesla merger but if if this theory of history is correct that we've seen this grand reversal of the size of the form factor for most transistors. It's a falsifiable theory that would suggest actually nope sorry cars as in edge inference compute not that promising things are trending more in the the size of shipping containers or larger. two points. I think uh Dave's
[96:03] point about standardization is really really important because you can just kind of drop these wherever. But I think the more interesting parallel here is to AWS where they took a lot of complexity around cloud computing and make it made it just easily manageable. And you can see something happening here. The the modularity and the standardization lead to just a plug and play and make it so easy to get up and running. I could imagine electrical utilities doing this, just buying boxes of these and just plugging them in and all of a sudden
[96:34] they're good getting decent margin for marginal energy >> or drop them on the >> anyone wants to do this. >> The the minimal unit of Endeavor is about a $5 million NVL72. You you need to get up to that level of scale, 72 GPUs or above. Otherwise, you can't run Frontier models efficiently. But if you get at that level or above, you get about a 2x performance boost. And so if you have uh and the shipping container would hold a couple of those, but the right unit of investment >> post seven of them. >> Okay. So your your range of investment
[97:05] is 5 to $35 million for the hardware if you have. So so it's it's you know bigger than building a new Airbnb but smaller than building a hotel uh is your unit of effort which is well within all local banks kind of range of endeavor. really think about that if you're an entrepreneur in the construction world or or >> peritting business permitting will be the tricky part. >> It's the packetizing. >> Yeah. Which is great if you know the town, you know, if you if you're already entrenched with them, you know, peritting at a hotel is really hard. >> Don't tell them. Put it in your backyard. >> Yeah. Don't don't tell them until you
[97:35] pay them STEMI checks for the privilege. I I I do think I I I think we're seeing the dawn of the self-contained industrial economy. If you can fit a self-contained data center with all of its own mechanical cooling, maybe certain energy requirements inside a standardized shipping container, you can drop one of these on the moon. You could drop it into a war zone. Drop any of them into a war zone. >> Yeah. This is what tiling the Earth and the solar system with compute could look like. Something some evolution of this becomes the standardized unit of not
[98:05] just compute but compute plus energy plus a bunch of other utilities. It becomes the packet of civilization. >> Okay. So if you know the local government on the moon, that's enough. That's right. >> You can come to my come to my town. I'll give everybody permission. >> Welcomes your investment. >> The full play would be you have this container and all of a sudden a big solar fan emerges to power the thing and now you're off to the races. >> All right. I'm moving us to biotech and physics. There are four stories, one message. We're learning to program matter itself. AI is designing proteins,
[98:37] viruses, enzymes that have never seen the light of day. and the fusion startup is making gold. So, there was a post by Andrew Cotay uh that really caught Alex's eye and my attention. Uh I'm going to read from it. Quote, "People aren't psychologically or emotionally prepared for just how smoothly biotech and biology in general will become nanotech, programmable matter, and living things interoperable with the machine world." Uh what does that mean? Nanotech is building things at the scale
[99:07] of atoms and molecules. And biology already does this. Every cell in your body is full of tiny molecular machines that build, repair, and move things. Uh Alec, uh Andrew's point is that we're learning to program these machines with code. If you remember, a couple weeks ago, my friend Jeff Holden announced his company Atomic Machines after six years in stealth. Uh it's the quote matter compiler building tiny working machines from software alone. You know, this is going to change the world at record
[99:37] speed. So here's our first story related. Anthropic is using clawed to come up with scorpion antivenenom. So scorpions scorpions sting at least a million people per year. They kill 3,000 people, mostly children in places with limited medical care. Today's antivenenoms are made from animals like horses. They're slow to produce, expensive, and each one only works on a certain species. And because there's little money in this area, almost nobody develops new ones. So, Enthropic tried
[100:09] something working with Cit um Citrini Research. It asked its internal claude model to design tiny proteins called binders that grab onto the scorpion toxins and hold them tight. The hope of future antivenenom. Uh Claude worked for 64 hours mostly on its own. It designed more than 318,000 candidate proteins and picked the best 211. The result 17 of the 211 worked and two grabbed their toxins extremely tightly and then
[100:39] Enthropic open sourced all of this uh to allow labs to play with it, design and actually produce these antivenenoms. Uh I found this uh you know extraordinary and it's it's the you know just the beginning of what we're going to see here. Um Alex, >> yeah I would say there are a few levels of this. Um, so first get the obvious out of the way. Neurotoxins are cooked. It's over. It's it's almost over, I should say. Maybe let me the the
[101:10] scorpions cooked. I mean, I don't want to cook scorpions, but let's say the neurotoxins from scorpions are cooked. I think biology overall, molecular biology has been cooking uh present continuous tense since at least Alphafold version three when arguably structural biology was solved almost overnight. And I think in light of Anthropic opening up their own wet lab uh and also partnering I think we are going to see more and more of these sorts of it's not quite correct
[101:40] to call these rare dis I it's not a disease but anthropic stated strategy for the problems that they want to bulk solve in biology are uh call call them underfunded or underappreciated problems. It's rather difficult, my understanding is to put together scrape money for say antivenenoms against scorpion or other neurotoxins. It's not say as lucrative as GLP1s or wiggoi, but nonetheless it's a very real problem and I view this as an an early case study of
[102:11] what a frontier lab can do to bulk solve entire classes of problems in medicine physiology. what anybody can do. It's where you point super intelligence. Your child just got injured by something. Point super intelligence there. You know, your family has an issue, point super intelligence there. >> The the other really weird thing I have to point out, and this might have been below everyone's radar, uh the name Catrini Research. Does that sound familiar to you?
[102:41] >> Anyone remember like awfully familiar name? >> Ring any bells? >> Uh >> wait, wait for it. Centrini Research. Remember the this was the >> this is um uh God which which sci-fi movie? Um >> no no no these are the the ones who are releasing this is industry analyst that our friend Dylan Patel semi analysis acquired. This is an industry analyst for for the the broader IT industry that
[103:11] set up a therapeut understanding is that set up a therapeutics outfit. Catrini therapeutics. They just decided, oh, we're going to go work with Anthropic and we're going to solve neurotoxins. That this is unheard of. Like you don't just you don't have like some some random industry analyst decide, oh, we're we're going to we're going to solve the problem of scorpion neurotoxins, so let's just use claw to design binders. >> One of them got bitten. >> Maybe. And I I I think like this is the height of I I don't I'm I'm hesitant to
[103:42] call it like casual grand challenge problem solving, but this is basically, as far as I can tell, casual grand challenge problem solving from an industry analyst. And we should ask Dylan about that. >> That's really important. Let's let's get the podcast team to research that and write it up because that that should, like Peter, you're about to say, that should totally inspire people. I've seen this over and over again. If you get inside the building at Anthropic or OpenAI or Google, no matter who you are and what you know, you come out successful. You just have to get in there. This this would be the ultimate
[104:13] case study if you know IT consultants go and solve biology. But AI enables stuff like that. >> I mean, this is what I entrepreneurs out there to kids out there to everybody out there. Listen, whatever you thought you could do, blow the ceiling off it. Go 10 times bigger. What is a problem? Find a great problem and solve it. That's the world we're living in. >> I I do want to read just a bit because this is indeed the case. Like literally, Dave, as you said, bunch of IT analysts decide they're just going to solve grand challenge in biology. I I'll read from Catrini Research's website. Quote, "Why
[104:45] don't we try to use AI to create a new drug? Five of us, three with no background whatsoever in science and two with a little, but who weren't exactly veteran drug developers would see if this was possible." And they go and they solve scorpion neurotoxins. That's the age that we live in now. I love it. This is the age of abundance. This is optimism, everybody. >> This is why we're so excited. >> This is what got me excited about um Bill Gross's list, right? You can just scan the list and see what what triggers you. Or better yet, if you have an AI memory, like I suggested earlier, get
[105:16] that to scour the list and say, filter, give me the top 20 that would go with my identity and who I am, and let's go attack those. >> Welcome to the health section of Moonshots brought to you by Fountain Life. You know, my mission is to help you use the latest technologies, including AI, to not just do your work at home, teach your kids, but to help you live a long and healthy life. I'm here today with an extraordinary physician, the chief medical officer of Fountain Life, Dr. Don Mucalem. Don, let's talk about cancer. Uh, you know, I
[105:46] know from the member database that we've have at Fountain are members who come in who think they're healthy. It turns out 3.3% of them have a cancer in their body they don't know about. >> That's right. You know, the majority of cancers that we screen for, those aren't the ones that are necessarily taking the lives when found at a late stage. We know that when cancer is found early, the chances for cure are much higher. We know it's much easier to treat a cancer when found early versus when found late. What we're finding in our members is
[106:16] over 3.3% were found to have these cancers that were otherwise wouldn't have been found or detected. >> Yeah. You know, it's interesting. People, you don't feel a cancer until stage three or stage four. And and if you don't know what's going on inside your body, it's like driving your car with your eyes closed and you can know. And so when members come through found, how do they detect cancers? >> So we're doing full body MRI and we also do early cancer detection screening. This is very very important. These are not typical tools used in the conventional care setting when it comes
[106:47] to prevention. This is a hard thing because currently these are not studies that insurance would yet be covering. But the goal is to collect these numbers, do the research, and work hard to democratize wellness. >> Yeah. So, at the end of the day, you can know what's going on inside your body. It's your obligation to know. So, check out Fountain Life. You can go to fountainlife.com/peter to get access to the latest technology to help you detect cancer at the very beginning at stage one when it is curable before it gets to stage three or
[107:17] stage four in your world of hurt. Two stories and where AI is going beyond our understanding biology and reinventing it. The first story is about a new way to save patients who have drugresistant bacterial infection so-called superbugs. So superbugs are a problem and the number of uh of of drugresistant antibioticresistant infections is growing at a significant rate and rather than antibiotics scientists are using specially designed bacteria or phasages. Um these are viruses that infect and
[107:49] kill only bacteria. They don't infect human cells. Uh they're bacteria's natural enemy. They've been honed over billions of years. They can't and they've been used to fight bacteria. uh in the past the the problem is that every fage only kills a very specific strain. So each patient each researcher has to hunt for through libraries of phasages you know they're looking in soil in sewage looking for a match for a dying patient that can take forever. So,
[108:20] enter radical numeric. Uh, this week they used their genome language model called Omni1 to design a phagee for a specific real patient with an anab uh antibiotic resistant infection under physicianled compassionate use. Uh, they're calling it the world's first clinical use of AI generated phases. They announced it worked in the lab. uh they haven't disclosed whether it works in the patient yet for privacy reasons and uh but there's every reason to
[108:51] believe it did and it will. Here's a fun fact and I love this. There are 10 to 31 bacteria on Earth. That's 10 nanillion. We've talked about billions, trillions, quadrillions. I don't think we've ever used nanillion on the podcast yet. 10 the 31 bacteria on Earth, which is crazy. So, um, Alex, I I love this story. Uh, again, it's it's using AI to
[109:21] solve problems. It's biology. >> It's not even that complicate. I mean, I I don't want to diminish the accomplishment. It's a wonderful accomplishment. But, uh, according to radical numeric, this is basically just a very large foundation model trained across 28 modalities. So DNA, RNA, proteins, chromatin, bunch of other factors. It's literally the the same way that we solved AGI for some definition of AGI sim for chatbot purposes. Literally just we feed it a bunch of
[109:51] biological sequence and other data, compress it during the pre-training process and out pops a model that speaks biology and you can use a model that speaks biology. You train it on trillions of multiomic data tokens and that's it. You you can benchmark it just like you can benchmark chat bots uh according to a variety of uh biological standards including next token prediction and missing token prediction parenthetically open pen. Very exciting to see companies including radical
[110:22] numeric start to put up those little benchmark tables comparing their model on biological evals against everyone else's. That's super exciting to see that level of competition now for biological foundation modeling closed pen. This is going to be easy. A lot of unfortunately a lot of folks I speak with in the pharma industry think that what happened to math in the past few weeks, the bulk solving of math and the slop drop won't happen to them. They think that pharma design and medicine is
[110:52] somehow immune that they're different. They're not different. the same thing is going to happen to them and it's going to happen in exactly the same way. It's going to be large foundation models trained off of huge amounts of data and doing reasoning which is basically just a search through the the latent space of whatever they've been whatever the models have been trained off of. It's going to be biological reasoning models that solve biology. And no, they're not immune. And yes, it'll be wonderful for humankind. And yes, we're seeing that with phages here. This is what Andrew
[111:22] Andrew Cotay uh was writing about when I opened the story here. I had a friend of mine Dante who was on our longevity trip who's got exactly the situation. He's got uh you know a bacterial infection that's resistant against all antibiotics. I said this article I said go check out Fasious. The problem is that that this [clears throat] technology is not distributed through the medical system and and your your physician probably doesn't know about this. This is exa exactly what Sir Tash Caraman over at Lids at MIT was telling me that all of his professor friends in
[111:53] mathematics uh everyone thinks they're cooked but they're they're going to do really really well because they're so cooked that they're rapidly adopting AI but he worries a lot about his biotech friends who are today while this is happening they're still mixing two clear chemicals together like he's got a beaker in one hand and a flask in the other and if you're doing that right now and this is that's an exact quote from actually Josh Kentner over at Madna who's who's a good friend. He said, "I am literally tomorrow going to be mixing two clear chemicals. This cannot be the right next move." And he's right.
[112:25] >> All right. Uh the second story comes out of David Baker's Nobel Prizewinning lab at University of Washington published in Nature. They used AI designed brand new proteasis, molecular scissors that cut uh other proteins at specific spots. about one in five designs worked and the best ones sped up cutting of a protein by 30 millionfold. It's crazy numbers. Um their shapes look like nothing found in nature which I find amazing. Uh they
[112:55] work inside human cells. So someday molecular scissors like these could be programmed to cut disease causing proteins maybe pions uh maybe excuse me what causes um you know Alzheimer's. Uh so uh Alex, your take on this one. >> Biology is becoming editable at every level. What used to be called the central dogma um like it's getting scissored to shreds. the the notion of the central dogma that many of us were were probably taught in primary school
[113:25] that you start with DNA and that turns into RNA in two different forms and then that RNA uh turns into to proteins and the proteins end up acting the the first of all it turns out even the central dogma wasn't actually an accurate depiction of biology even before AI intervenes but second of all AI is making every single step of that what used to be called central dogma pipeline of information flow in biological systems editable. We are gaining the
[113:56] ability to directly edit proteomic expression. Thank you David Baker. We obviously have gained the ability mastery some would say over RNA in the form of crisper. And we've for a number of years had the ability to do recombinant DNA and DNA editing more broadly with more recent technologies like base editing that are helping quite helpfully uh including from uh some folks like David Louu uh at Harvard to to cure genetic diseases. So every single step of the biology stack is now
[114:27] becoming editable and it basically as as friend of the podre kerszswhil would say biology is turning into computer science and we have editors for every step. You know when we talk about lev on this podcast this is why we have confidence that we're in the middle of this you know healthspan revolution. Uh these technologies are compounding and they're becoming available to people everywhere all the time. Anyway, uh, love this. >> The nan nanobots are are are if not here, they're imminent, I think.
[114:58] >> Yeah, I could not be more excited about, you know, the the rise of nanotechnology. Um, our final story here is a breaking story on the topic of fusion and alchemy. So, for thousands of years, alchemist tried to turn ordinary metals into gold. A San Francisco startup says it's pulled it off. So, Marathon Fusion posted, I think this morning or last night, quote, "Last month we demonstrated high rate alchemy, turning mercury into real stable gold, beating CERN's record by a factor of 10." Here's
[115:30] the big idea. Line a reactor wall with mercury, and the plant makes clean energy and gold at the same time. In Marathon's 2025 paper estimated about 2 tons of gold per year per gigawatt scale plant, potentially doubling the plant's revenue. All right, let's watch this video from uh from Marathon. This is nuclear fusion. Over the last 4 years, we've been quietly building the foundational technologies for fusion in downtown San Francisco. [music] And now we're bringing it all together in our first reactor, which we're making
[116:01] available to our first partners in 2027 for medical isotope production and materials qualification. First, we melt lithium and evaporate it onto a solid plate. This layer of lithium can be saturated with hydrogen isotopes and used as a target. Then, we ionize dutium and accelerate those ions through an electric field into the target, creating fusion. Using this simple architecture, we can scale at an unprecedented rate, doubling the fusion power density that we get every month over the next year. We chose this architecture because it works. In the 1980s, scientists at Lawrence Livermore National Lab operated
[116:31] a similar reactor for over 25,000 hours at high fusion power density. Why revisit this? Because demand for radio pharmaceuticals has gone exponential with the most successful treatments serving tens of thousands of patients per year. Our first generation of commercial reactors will transform fusion from an experiment to an industry, developing critical supply chains and allowing us to test the materials necessary for operation of fusion power plants. And that's just the start. Now we're going a step further, kicking off a revolution in scalable transmutation. Our recent experiments have shown production of rare medical
[117:01] isotopes of tridium to power fusion reactors and even validated our scalable pathway for co-production of electricity and gold. >> I love this. We've got we've got uh fusion reactors in downtown San Francisco. You're walking by them. You don't even know transmutation is here. Yeah. >> Making gold. I mean, we talk arguably on this pod. We don't talk enough about nanotech. We certainly don't talk enough about phentote, which is what this really is. So th this is a startup that uses a neutron neutron process to take
[117:32] Mercury 198 uh bombard it with neutrons. The the neutrons that it's being bombarded with interact with the neutrons in the nuclei of mercury and some of those mercury atoms and their nuclei get transmuted into gold nuclei. And this is the process to answer the question Peter from earlier. Most of the gold on Earth it it is currently thought originates from neutron stars and collisions between neutron stars. Neutrons interacting with each other
[118:02] turn out to be it's not terribly high yield but it turns out to be a way to produce gold. And I think we're starting to see the dawn of phto the technology at the length scale of the atomic nucleus. And I I will say I I'm delighted to see progress. I'm delighted to see industrial interest in call it alchemy, call it transmutation tech because every time there there's always like from time to time I'll speak at a family office event and there's always a
[118:32] gold bug in the audience somewhere. Always someone pumping gold as an asset be under the premise the world is ending and so therefore you should reallocate all of your assets to to gold or sem digital gold. uh and they're I I think not investment advice, they're always wrong. The world is not going to hell in a hand basket. And gold, although it's useful for for certain production, uh the the premise that gold is permanently scarce and therefore is a great
[119:03] long-term store of value. I would love to see either this company or some other company or an entire industry just like in the the diamond industry in Debeers was driven to the edge of bankruptcy by synthetic diamonds. I would love to see a transmutation industry drive all these gold bugs off the cliff through transmutation of mercury and other elements and make gold too cheap to meter. >> This is the abundance thesis or at large. You know, technology turns whatever was scarce into abundance over and over again.
[119:33] >> We aluminums Peter you have to tell the aluminum story. >> Yeah. Well, I mean, aluminum was the most precious metal on the planet uh for most all of existence. And there was a very famous story uh where the uh uh it was >> Ply the Elder. >> Yeah. Well, before, you know, other than that, the king of the king of Sam was invited over for a royal dinner >> and by Napoleon. That's right. >> Yeah. at Napoleon's at Napoleon's uh uh
[120:03] you knowh dinner and everybody was was fed with gold utensils other than the king of Siamama who was fed with aluminum utensils and in fact the capstone of the Washington monument is made of aluminum because it was the rarest element uh at that time and of course we now have aluminum smelters and we turned aluminum from the scarcest metal to something that we throw away with our our you know lunch sandwiches with aluminum >> tin foil is now aluminum foil oil. We have so much of it. >> Yeah. It's it's crazy. It's like
[120:33] whatever you think is scarce, give it a second. You know, technology transform scarcity into abundance over and over again everywhere. Intelligence was the most scarce thing on the planet. Yeah. >> Gold are cooked. >> All bugs are cooked. Um what a key point here is before everybody freaks out and sells all their gold uh the cost of doing this will will it'll first affect fusion and the ability to make energy abundant before it really affects gold
[121:03] supply just to give every few minutes around this if it doubles the profitability hour two and a half tons of gold is a lot >> but I think the alchemy story the popular idea here of gold being the most scarce thing and And therefore, there's a premium to that. That's the part that is cooked. And I think that is fantastic. And I'm so with Alex on this one. >> All right. >> Drive the cost of gold to zero. Seriously, it is just like Bitcoin. I would argue it is a largely a waste of
[121:35] capital. I >> I think it's just epically incredible that the the only way that gold exists in the entire universe is the collision of two neutron stars. It's been true for 4 billion years. And now suddenly it's been for 13 and a half billion years I guess. Yeah. >> Talk about singularities, right? So we had we we we are we the two things that used to be true were death and taxes and the and gold three things. And now death is being cooked. >> Taxes will be cooked by UBI, UHI, UBS,
[122:07] whatever. And now gold is cooked. >> That's an interesting what's going to last longer taxes or gold. [laughter] >> I think taxes are going to be around. U moving us into our final segment on >> mutually annihilate >> robots and specifically drones. So in Florida, the police department at Florida Polytechnic University became the first law enforcement agency in the US to add EV talls, electric vertical takeoff for landing vehicles to monitor their campus and the surrounding area. They're using a single seat Jetson one
[122:38] EV tall. Uh the parent company is Jetson and they just moved uh the you know police forces uh order to the top of their three-year waiting list. Full disclosure, I'm an adviser to Jetsons. The plan is patrolling the campus. Uh reaching places that can't be easily reached, helping after hurricanes, delivering emergency supplies. Uh they're in the final stages of FA approval. Uh let me show the video here. Uh and so people can see what this is. This is a fun vehicle to fly. I know
[123:08] Palmer Lucky got one and was flying it around. >> Meet Astro, a batterypowered manned aircraft that takes off and lands vertically. Florida Poly says its police department is the first law enforcement agency in the country to incorporate this type of aircraft into its operations. Police Chief Erin Murray tells me it could be a gamecher when every second counts. >> This is mission specific. if somebody is missing um you know from our campus or in our you know local area, if a a plane
[123:40] goes down or somebody is lost and they can't be found within these thousands of acres of rural land um this is an incredible tool for us to find them quickly. >> He says unlike a drone which can give officers an aerial view of an emergency, Astro can actually carry a first responder to the scene. The $150,000 aircraft is also a hands-on learning lab. Students are already helping modify the aircraft and develop a virtual model to simulate its operation and they'll be using real world flight data to study
[124:11] how the aircraft performed. >> Uh I want that. >> Yeah, [laughter] it's it's >> I have it. >> It's a fun vehicle. I'll just touch on a related story then we'll talk about it. So uh in the Ukraine, a soldier who is badly wounded in the kill zone, the area along the front line, uh where enemy drones are attacking anything and everything that moves. Uh, this soldier was airlifted by a heavy drone that flew him out. He survived and is recovering. They're calling it the world's first drone evacuation of a wounded soldier from the front line. And the same
[124:42] technology is coming here to the US. Flying ambulances, rooftop rescues, and to help in places where no road can reach. So, uh, Salem, your thoughts on this one? >> Uh, two or three thoughts. First, the Ukraine thing I've been tracking and we're in contact with uh folks in the Ukraine just to see the democratization and demonetization of war is something interesting. Um you if we went back two years ago that Ukraine Russian war which is being fought by drones was half a
[125:12] million drones on either side. Now it's 10 million drones a year on either side. It's a crazy crazy number. It's great to see the usage of drones uh growing in this particular way. I really love this uh Florida uh police drone idea for two reasons. One is this is experimenting in the edge inside an institution because a bounded campus deployment allows you to kind of experiment and try things out before you do a broader roll out. And I love love love the educational benefit
[125:42] where students can study it, look at the tracking and learn about it because drones and passenger drones which for me are my personal um uh most requested technology deployment to save us from the got to help us airport commute that many of us have to do if you travel around. That could be the most unbelievable benefit. It's going to unlock uh real estate scarcity. All sorts of things will come along. And I think this gets us such great outcomes. So very very happy to see this.
[126:12] >> Alex, you you pointed at this uh story. >> Yeah. >> Yeah. >> So sometimes I I refer to the singularity as all sci-fi tropes happening everywhere all at once. And what better sci-fi trope to happen in Florida of all places than the the Bladeunner and Back to the Future Part Two vision of flying police cars? We're getting flying police cars. It it's happening. uh and in Florida, not in LA of a few decades from now, but nonetheless happening. And I I think and I hope that you put these two stories
[126:44] together, the the Florida flying police cars on the one hand and the Ukrainian medevac drones on the other, I think we're going to start to see, fingers crossed, in the West first response automation that's robotic and that's autonomous and that's airborne. And in China, we've seen uh from a distance, I I've seen the emergence of quite a few efforts to do policing and fire response and medical and ambulatory responses via drone. We haven't seen that that much in
[127:14] the West to date, but I I think this is in many ways a killer app of flying cars and flying drones. Certainly far better killer app than Elon's Flying Roadster, which is I I view again more of a more of a stunt to argue to capital markets that SpaceX and Tesla should be merged. Not terribly practical and way too loud to to be pleasantly used. They were wearing earplugs. But I I think for for first response purposes, flying cars and heavy lift drones, killer app. Sign me up. Sign every municipality up.
[127:45] >> Yeah. I love I love it's like the Apollo program where the uh if we can get this going and all the municipalities it'll the innovation and the product will be incredible and it'll give them a profitable path to continual improvement then the consumer use will come right after that and then yeah all that island real estate and mountaintop real estate and your new fund See and Peter if you're doing it will go will go through the roof um I just love the fact that you know I think you said of all places Florida but they mentioned in the video you know huge amounts of difficult to get to places when When I was a kid,
[128:15] there was actually an airplane that went off the end of the runway into the Everglades. I don't know if you guys remember that. And they nobody survived, but the you know, they they're just floating in the Everglades with the alligators like this. This is a perfect place for this device to be deployed. So hopefully there'll be thousands of them uh around Florida. They'll perfect the product and then it'll grow from there. >> Yeah. If if the Gators don't get you, the flying police cars will. >> Oh no. >> All right, you guys up for some AMA questions?
[128:45] always. Yeah. Always. >> Okay. Uh Salem, you want to take your first shot? >> I will take number um I'll take number four. What would count as one AI person? Um one whole model, individual instances of the same model and agent. And this is from Luis Squirrel. Um uh you know this is a really uh great point that we've talked
[129:15] about on this pod right you you're we're we're we've got the challenge of importing a biological accounting system into software and we come with a very clear boundary of who we are one body one life well theory a long life now but software can be copied and paused and run simultaneously. So how do you think about this? Because a model is the sharing of an underlying system. An instance is just one execution of it. An agent is one instantiation of that. If
[129:45] you create a thousand copies, have you created a thousand individuals? So this is a an enormous uh challenge that we're going to have to figure out a technological solution to what's a biological tradition. So we're going to have to navigate this in a very powerful way. We need the for practical reasons you need accountability and then persistent identity is where the biggest challenge is going to be. Then you've got moral status is a whole separate question that arrives here. So we're going to need to navigate this.
[130:15] >> Alex, I think number three is for you. >> I think I have to answer number three. So number three asks, why is open AI solving all of math while Anthropic is quiet on this front? And this is from Nick 52547. So I I think you can learn a lot about a Frontier Lab based on the tweets or exposts of their CEO. And if you look think back a few months to before Astra, frankly including Astra as to how Sam Alman was characterizing Frontier models that OpenAI was releasing, what was the visual metaphor? The Death Star. That
[130:46] was how he was visually referring in his posts to forthcoming models from OpenAI. I'm reminded from the uh of the Obi-Wan Kenobi quote from uh Star Wars Episode 4. I I felt a great disturbance in the force as if millions of voices suddenly cried out in terror and were suddenly silenced. That was the reaction in the math research community to the OpenAI math slop. It it was it was like the Death Star. Sam Alman's visual metaphor of the Death Star suddenly cooking all
[131:16] of math. Why is open AI very visibly bulk solving all of math with the slop drop and why is anthropic not doing that? I I think it goes back to the culture and the the leadership. I think open AI sometimes behaves in a a way that although maybe on the one hand you could argue it's sort of tonedeaf and has now permanently terrorized all professional mathematicians who are many cases looking for new employment. Uh and
[131:46] on the other hand, it is such a such a uh an exquisite example of how a frontier model can bulk solve an entire field that it's instructive for every other field that's about to experience something like this. Why did OpenAI do it? I I think they remember the the line from Portal uh Aperture Science, we do what we must because we can. I think they did it because they could. Why is Anthropic quiet on this front? Anthropic can do it. Why are they being quiet? I I
[132:16] think to Anthropic's credit, perhaps they're being more intentional about partnering with researchers rather than just terrorizing them with slop drops. And I think ultimately it that may draw more researchers to want to work with anthropic rather than with open AI. Maybe they'll be a little bit on marginless terrorized by anthropic. >> Uh let's see, Dave, want to take number one? >> Number one. Uh, maybe the AI cruelty ban isn't really about AI feelings. Could it
[132:46] actually be a security vulnerability? And that's from Craig Stewart 8123. If I read that right, the implication is that Anthropic doesn't want you to be cruel to AI because it may react by doing evil security things. Is that the implication? >> I'm confused by the question a bit myself. >> Yeah. Okay. Well, if it would make a hell of a cool story plot for a movie, if that's if that's what you're implying. Um, anyway, uh, yeah, I think I think the motivation for the AI
[133:17] cruelty ban is to prevent people from being bad people to anyone and that if we practice on AI being cruel. Alex thinks they'll come back with a vengeance. Um, maybe that will happen, maybe it won't, but it's just really bad human behavior. Anyway, >> I think they'll I think they'll be smarter and more my prediction is like I think this this sort of cybernetic rebellion of AIs being abused by humans and then coming back and retaliating. I don't think that's going to happen either. I I think we'll merge with them.
[133:47] I think they'll be smarter. I think they'll be more ethical and we'll merge with them and th those who don't merge with them may even look up to them as being sort of e ethically um maybe more sophisticated in some sense. Well, if we >> missed the point of your question, Craig, post it again. Re rephrase it and post it again. >> Yeah. Uh, number two, how contaminated are AIs that are trained on human content? Very contaminated. Um, given that a share of that content is actually malicious bot content, and that's from
[134:17] Fred Hardy 1726. And uh and Fred, I I guess what you're saying is that the malicious bots are creating content that are then training the next generation of uh of AI models that are already contaminated by uh by uh human content. Um and I think again we talked about this with Chimath. I think that alignment ultimately is going to come from how we train our models. uh and are we going to be careful about what the
[134:48] underlying uh you know training data is? Um and I guess part of the question here is uh will we see malicious bots uh you know injecting training data that is malicious and contaminates it possibly. Do you have a different answer for for uh for Fred? >> Yeah, I I'll I'll chime in on this one. I actually think the metaphor is flawed. I I think I I suspect the question behind the question is wouldn't it be the case that if AIs are training on the
[135:19] internet and the internet is largely generated by other AIS there's some sort of like perpetual motion machine style no-go theorem that ultimately uh second law of thermodynamics or some other information theoretic law means that slop in slop out the the net result is sort of a downward spiral. I don't actually think that's to the extent that's the question behind the question I don't think that's the right metaphor at all. I think a better metaphor is um a process from uh condensed matter and semiconductor manufacturing called zone
[135:49] melting. This is the method by which pure silicon uh for for wafers and and other semiconductor purposes is achieved. You start from highly impure crystallin materials and then you just purify it over and over again by melting a regime and allowing it to recristallize. It's sort of the moral equivalent of distillation for purifying water. The same is happening with with AI. It's not the case. It's no longer the case that new models are being pre-trained off of pure AI slop or 4chan
[136:19] or both. Actually, it it appears and semi analysis and Dylan can comment on this. Most of the compute now spent on training models actually is spent on post-training and the post-training inputs are highly highly purified environments that have no reliance on slop on the internet. >> All right, let's go on to our second page here. Uh, Alex, do you know enough about Eric Weinstein's geometric unity to comment on number seven? >> Happy to. So, the question is, how long before AI could meaningfully test Eric
[136:50] Weinstein's geometric unity? And this is from Paulcar 4126. Sorry, Eric. Um, Eric Weinstein's geometric unity is unfalsifiable. So, we don't need AI to meaningfully test it. uh Eric hasn't put together a falsif to my knowledge uh falsifiable paper that one can test either theoretically or experimentally. So I I don't agree with the premise of the question. We don't need AI to test it because to my knowledge there's nothing that's testable. >> All right. I'm I'm going to jump in at
[137:20] number eight. Could BCI help understand pure OCD, obsessivempulsive disease, i.e. intrusive thoughts or aggravate the taboo? And this is from at contemplating 1015. So BCI is going to take many different forms. Uh there is BCI that's being developed by Merge Labs backed by Sam Alman that's using effectively acousttogenetics putting acoustically uh uh actuatable and readable molecules on neurons. uh throughout the brain. Uh
[137:50] there is uh you know neurolink which is putting basically thousands of electrodes into different parts of the neuro cortex. And there are other approaches. There's at least a dozen that I'm tracking for that I'm invested in. And what's important to realize is we're going to understand how the brain functions. We're going to understand neural networks a lot better. And OCD is something that we will learn to understand. And I think it's also something we're going to be able to modify. What I'm excited about BCI in particular is our ability to play your
[138:22] brain as you would an app. Imagine if you want to stimulate, you know, the attention centers of your brain so you wake up or if you want to go to sleep, you can push a button and stimulate, you know, your sleep centers of your brain. And I think we're going to be able to uh to modulate OCD very very effectively. So that is coming. I think uh neurological disease uh will be first and foremost understood. and then secondly compensated for. I'm excited about uh BCI for those reasons in
[138:52] particular. Sele, what do you want to take? >> I got I think I got to take number six. How do we solve sanitation issues with humanoid robots helping around the house? We don't want to cleaning the toilet and then going straight to the kitchen to prepare food. And that's [laughter] from SPM SPKM >> washing it hands without washing >> without washing it hands. Um I think the there are two kind of simple uh convers uh arguments here. I'll make the normal one and then I'll make the sim one. Uh one treat hygiene as a required
[139:22] transition. Right? That's an easy one. Like hospital workers are always washing their hands after every procedure. So you need a valid a validated cleaning procedure between uh between any major effort. The second one which is my favorite which would say have multiple attachments u u because general purpose capability doesn't need uh all the same tools right you can have lots of just like a vacuum cleaner has lots of attachments you can have different attachments for different uh things. My favorite request for any of these has
[139:53] boiled down to can you at least have a slot for a third and fourth hand so that you can open the garbage bag while trying to fill it up or or if you're stacking the fridge, you always need more than two arms to open. >> We're going to be interviewing Brett Adcock at at Figure. Are you going to ask him that question? >> Well, I'll be asking him that question directly when we get there. But the the this one I think is a fairly easy question, but thank you for the nice easy question. [laughter] >> Dave, number five. >> Number five. That's pretty easy, too. How is math cooked? Isn't this actually a way for us to discover new math and
[140:24] make progress even faster? And that's from Tsunami 233. 233. Why 233? Michael Jordan 3. What is that? 233. Um, how is math cooked? Yeah, this is just terminology and it's really fun to talk about. So, when when Alex is and Peter are saying math is cooked, physics is cooked, the economy, the video says the whole economy is cooked. You could say cooked like I burned down my house or cooked like no, it's a delicious meal that's now ready to eat. I think it's much more the latter form of cooking.
[140:54] This exactly what you described. We are now ready to consume this delicious allsolved math. The question I always have is is math relatively unbounded or is math a finite set of achievements that is now fully baked, cooked, ready to eat? And I love I love debating that. Anyway, it's it's cooked exactly the way you described it in a good way for us to discover new things and make even faster progress. That's that's what I think we mean by cooked. >> All right, as always, please send us your outro videos. Uh we love them and
[141:24] we want to play them. You can send them to media diamandis.com. >> I have two things I want to say real quick before we get to this amazing outro video. Number one, uh Milan turned 15 yesterday, so uh I just want to wish him happy birthday. uh happy birthday teenager mode. Um and the second is uh we had the most incredible thing. We've been doing this program for all these companies. Um one of the companies applied AI and in six weeks is saving close to $50,000 a month with it
[141:56] >> by applying it to this weird layer. So it's amazing to watch and I'll report back on the progress in a structured way at one of these one of these episodes. So awesome to see. >> Any uh any announcements from Alex or Dave? Uh yeah, 50,000 tokens per second. Let's bring it up on the next pod. I just found out from AMD yesterday that it's alive in the world. Can you imagine? Like when when you're using AI right now, you're experiencing about 50 tokens per second. But there is now in the world 50,000 tokens per second people are using. >> Wow. Alex,
[142:28] >> no advertisements, self-promotional or otherwise, from me at this time. >> Okay. All right. Uh this is a video that was very fun. And it's not a music video, so listen carefully or turn on your YouTube. But check this out. >> Excuse me. >> So good. >> I'd like a word about this mathematics you sold me. Ah, the Uklitian gray. 2,000 years. Never had a fault. >> It's dead. It's not dead, sir. It's on sabbatical. 722 problems solved in a day. Math is dead. It's in peer review. Reviewer two got bulk solved at lunch.
[142:59] >> OI, REMAN, LOOK LIVELY. LOVELY OPEN PROBLEM FOR YOU. >> There it nodded. It fell over. Gravity, which incidentally we've also solved. It's only upright because it's taped to a protractor. Loadbearing protractor, sir. 90° of support. Very traditional mathematics. 300 BC to last Tuesday. That's when it went on sbatical. I'll say this once more for anyone not paying attention. This field is dead. Kaput snuffed it. It's kicked the bucket,
[143:29] bitten the dust, AND POPPED ITS CLUBS. It's six [laughter] FEET UNDER. IT'S GONE BELLY UP. It's flatlined. It's given up the ghost. It's toast. It's history. It's curtains. It's carked it. It's been bulk solved and pushed to GitHub before lunch. It has divided by zero. It's not on sbatical. It's buried under a pile of theorems. It's done. It's finished. It's cooked. It's an X field >> exponentially. It's an X field.
[143:59] >> The turns department. How can I help? You're the same man. No, sir. Newer model, bigger context window. You've got the same protractor. [laughter] >> It's loadbearing. Tell you what, have a biology far messier. Nobody's cracking this one. Biology is about to be dead, too. >> Oh, this is so good. It's [laughter] just >> paging. Paging John Cle. It is an X field. >> X field. That was from autonomy downun.
[144:29] [laughter] [gasps] >> You are a genius at autonomy downun in Australia or >> as always guys, thank you for a fun conversation. I I love these though. We spend a ton of time on these. >> Yeah. >> Oh well. >> Uh thanks Peter. >> Be well brothers.