Dario vs Jensen on Open Weights, OpenAI & Anthropic in DC, Xi Exports AI to Global South | EP #275 — raw transcript

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A couple of days ago, Jensen Wong, CEO of Nvidia, he says the world needs both Frontier closed models and Frontier open models. Enthropic was silent for three days and there was a lot of conversation. Where is Enthropic in this conversation? >> All Daario has to say is >> OpenAI and Enthropic who have been two rivals for the longest time. They've been pushing for the same agenda. A federal review process for the most powerful models. >> Aiming enforcement at intelligence is like thought policing. police what the AIs are doing, not what they're thinking or how smart they are. Global AI diplomacy is coming. China's leader, Xi Jinping, is wielding AI as a tool of statecraft, using it as leverage in China's diplomacy across the global south. >> I can't stress this enough, the whole power of the US as its open and very broad innovation ecosystem. if they close up the open model policy. >> Now that's a moonshot, ladies and gentlemen.

[00:01:00] >> Welcome to Moonshots, everyone. The number one podcast on all things AI and exponential, your front row seat to the coming singularity, actually to the singularity which is now >> to the president. Why do you keep saying that, Peter? It's right here, right now. Maybe in our rearview mirror. >> Well, no, it's we're on the curve. We are on the curve and we are climbing at a hyper exponential. I'm here with the Fantastic Four, my magnificent moonshot mates, AWG, DB2, and Seem. I'm Peter Demandis, your host, and I'm telling you, this week is proof that we're in the midst of a supersonic tsunami. So, buckle in. As always, our mission here at Moonshots is to keep you informed, keep you up to date on exactly what's happened, and most importantly, keep you optimistic about the extraordinary world we're building. And I don't know, Jent, if you saw the tweets going back and forth and the comments of Sam and Elon that were currently living the singularity, I think they finally caught on. >> I think they're finally watching. >> Yeah, they've been listening. >> But on a delay of a few months, like we

[00:02:01] we got there first. >> Yeah, for sure. For sure. >> I did hear one thing today that was interesting. I'm at the KPMG tech symposium, uh, where I come pretty much every year these days. Peter, you were here with me last year. They had the chief security officer of anthropic speaking >> and he said we might hit we're going to hit AGI in two to three years >> uh and he and he gave a reasonably thing definition. So I want to go up and say hey challenge you on that one but I didn't get >> did you write it down? Did you bring it? >> I did I did write down what he said. >> Actually you should just say we we hit this we hit AGI a few years ago. You know let's put Alex up against him. Anyway, uh so you know, just a a quick message to our beloved listeners. If you're a fan of Moonshots and this program resonates with you, you're clearly one of us. So please, please, please take a moment now and hit the subscribe button and join us on this adventure through the singularity. It's just going to speed up and our mission is to deliver to you the best we can. A lot to report this week, a lot to

[00:03:01] discuss. Uh you know, a lot of intrigue from the Frontier Labs. We're going to be speaking about Jensen Wong's uh mission to create an open secure AI alliance. We'll discuss Anthropic's past position and Dario's new position on open source news today that Anthropic and OpenAI are supposedly teaming up in Washington for their lobbying efforts. We'll dive into Claude 5 and AWG will give us all the metrics and the release of Kim K3 yesterday, a hugging face. And then the successful launch of Starship 13 and we'll close with Elon's comments on a post capitalist world. Got to love Elon. You know, he does not disappoint at all. So, a lot to unpack. Uh let's buckle in. You guys ready for this? >> Absolutely. >> A little enthusiasm here, gentlemen. I mean, amazed. Amazed. >> Amazed. Amazed. It is. Yes. >> All right. Uh, so let's kick off this episode with a fight that's framed the entire week, which is open source versus

[00:04:00] closed source. A couple of days ago, Jensen Wong, CEO of Nvidia, posted his first ever tweet. I mean, he's been on X for the longest time, has never tweeted. His first tweet, what was it? It was a letter on why open models matter. And it's been signed by 77 companies thus far. Jensen writes that open models strengthen safety and cyber security, accelerate innovation and diffusion, and enable sovereignty. He says the world needs both frontier closed models and frontier open models. He then goes on to launch the open secure AI alliance. We're going to talk about that in his letter. Jensen recalls a story that we report on last week about Hugging Face experiencing an intrusive agent that logged on 17,000 actions, escalated its privileges, harvested credentials, and moved across all of Hugging Face's clusters. The closed AI models, GPT56 and Claude Fable, that HuggingFace tried to use to hunt down what was going on blocked them. It blocked their forensic teams and they had to turn to an

[00:05:01] openweight frontier model, GLM 2.5. We discussed that last week. to help hugging face find to contain the intrusion. So, uh, Jensen's thesis in his tweet is that attackers have frontier AI, so defenders need frontier AI ecosystems. Uh, we saw Sam Alman jump in on this, saying OpenAI wants to have the US leading in both open- source and proprietary models. But Anthropic was silent for three days and there was a lot of conversation. Where is Enthropic in this conversation? You know, historically they've been opposed to open source for a number of reasons. So yesterday, Dario finally responded saying he rejects the claim that Enthropic wants only open uh doesn't want openweight models. In his word, Enthropic has never advocated for a ban on openweight models. There's a lot of videos showing that he was sure hinting at that. But Dar reframed the competition, reframed this debate, saying that the real issue is not open

[00:06:00] versus closed. It's whether authoritarian states, i.e. China, can reach the AI frontier. Dario's sharpest disagreement with Jensen is belief that openweight models could be attackers. Dario's central thesis is that biology is the issue. Sufficient capable models could weaponize pandemic scale pathogens. And it's worth noting that Dario probably of all the uh frontier lab CEOs is probably the most steeped in biology. He has a PhD in uh in biohysics from Princeton and he recently acquired an biotech company called Coefficient Bio. So rather than ban what is Dario proposing? Three things. One, block advanced chips and chipm equipment from reaching China. I'm sure that uh Jensen doesn't necessarily like that one. crack down on industrial scale model distillation and require safety testing for all powerful models open and closed. So, uh, let's dive into this. Dave, I'm

[00:07:03] I'm curious. You know, one of the things we talked about before is if if Dario really wanted levels of safety, he would put forward KYC requirements or crack down on mass distillation of cloud models. But we haven't seen that. Your thoughts, my friend? Well, I mean, right out of the gate, the the argument, as you laid it out, is perfectly articulated. But if Jensen says, "Look, cyber threats can be defended with AI and therefore open weights can defend against open weights within cyber threats." All Daario has to say is, "Okay, boweapon. I have a sufficiently advanced. How is my AI going to defend me from a bioweapon?" is you can't argue. But I'm thoroughly convinced. Yeah. Well, Daario, Daario, I am 100% convinced, is speaking his mind without an agenda. I'm not 100% sure about anybody else in this debate, but Daario is a brilliant guy laying it out exactly the way he sees it, even at the expense of his own valuation. Everybody online

[00:08:01] is saying, "No, no, no. He wants closed weights because he has a competitive advantage, and if nobody else can get access, they all have to pay him." True, but I don't think that's his motivation. I think he genuinely got into this industry long before there was any money in it. >> Yeah. No. Well, good. I'm good. >> I, you know, I do I do believe you that I think so. But it's interesting uh that you know, Anthropic has gone from the most beloved safety conscious company out there to being just rad over the coals over the last couple of days, this last week. >> Yeah. Isn't that funny? Well, but you know, if you if you say the same thing about Sam and everybody and Elon, you know, you go from darling to goat in a heartbeat in this world. And so, it seems to be the common trajectory. As soon as you're too big, everybody's like finding ways to just poke at you. >> Is the new >> Yeah. Be careful on the way up because you're going to get slammed on the way back down. Alex. >> Yeah, I I I think after a number of years of Daytona between the infrastructure layer, that is to say GPU

[00:09:01] and lower layer of the stack and the model layer, that is to say the open AI and anthropic and other model provider uh at that layer. I I think we're seeing the the beginnings of if not open war, then at least cold war between them. The the first rule if you're an aggregator in business is commoditize your compliments. And Nvidia has been very stealthy if you will, very polite, very diplomatic about their desire to commoditize the model layer. They've struck agreements uh including what some have argued are circular wash sale type agreements with the data centers providing compute for open AI and anthropic and others. And now I think this is turning into open warfare where really the the question is where do the profits accumulate in the super intelligent stack? Are they going to accumulate at the GPU level in which case Nvidia wins and Nvidia wins by

[00:10:02] popularizing openweight models that can't capture value at a higher level in the stack or does it live at the model layer in which case we see uh proliferation of duopoly or igopoly high-profit margin model providers anthropic reportedly high profit or does it live elsewhere and I I think due to the competition and quite frankly due to the outstanding ending success at the frontier of what until recently looked like an OpenAI anthropic duopoly. I think we're seeing the GPU Nvidia layer fire back. What I don't quite understand is why Nvidia isn't working more aggressively to commoditize or commodify the layer of the stack beneath them. Where is why isn't Nvidia aggressively financing say TSMC Samsung competitors? Why is it Elon doing it and not Nvidia? I that one's a head scratcher for me. really should be as aggressively pushing like an uh a secure open fabrication

[00:11:00] initiative just like for one layer beneath versus one layer above. >> So love so love to brainstorm on that and for a whole episode. You you you know I I know the answer is that if he is doing it he has to be doing it very very secretly because you cannot irritate TSMC for even a minute. They are so in control of the world right now. Uh but if you're going to do you know Elon is the one guy who's overtly said I'm going to build the terapab. I'm going to build something. But he's fearless. But any rational person has to be afraid of irritating TSMC. So if he's doing it, he's got to do it so secretly and so stealthily. I I don't think he's actually doing it because it's hard to contain that. But that is a really great question, Alex. I would love to riff on that sometime for like an hour. >> What do you think of the open secure AI alliance that Jensen proposed? >> It reminds me if if you think back, so we're in 2026. It reminds me, do you remember in 1998 when Eric Raymond and Bruce PN founded the open- source initiative, OSI? >> It reminds me just like just of that. Like I think I if if I look at the

[00:12:00] historic arc of commercial versus open-source AI models, I I think we're at a point in this arc that's roughly analogous to where Microsoft was in the late '90s where they just totally dominated the future light cone of software and it was open- source of in in sort of a case of history rhyming open source that came from outside the US like Linux came from Finland. Yeah, sure. Richard Stallman and FSF came from Cambridge, Massachusetts. But Linux, which really was the nucleation event arguably for open source, came from Finland uh and was popularized with an American open blank initiative parallels there and in combination with the antitrust verdict against Microsoft that helped to unlock the future Liteco for just about everyone else afterwards. So I think there are interesting historic parallels. See, last week you said something got a lot of love in the comment was that intelligence wants to be free. I mean the whole open source

[00:13:00] movement is sort of the abundance thesis writ large right uh your thoughts. >> Yeah completely. Um, you know, I I like this open secure AI alliance, whatever the name is. Uh, cuz the Jensen is reframing open weights from a security vulnerability to being a security capability cuz this this whole alliance is very exo. If you put together a community of people, they will be able to defend in a very powerful way. Because if the attackers have access to open models and and and have powerful AI, the defenders can't have have only access to a closed model that they don't understand the outputs. They have to be able to inspect it, etc. So, this is a great approach for some of that. And to Alex's point, this is exactly the same transition as the open- source software transition. And everybody wins in open source except for the closed people. >> Yeah. And Nvidia wins by supporting everything. I mean, >> yeah, there's a clear >> remember who ultimately back in the 90s

[00:14:00] and early 2000s, one of the biggest supporters for open source was IBM because at the hardware layer and the services layer, they benefited from the commoditization of software. Same here. Always if you're an aggregator, you commoditize your compliment. >> I I've referenced this before, but I it's worth bearing again. In 1995, IBM pled all the CIOS of the Fortune 500 and someone said, "How many of you use open source in your tech stack?" 95% said no, we don't use open source. We're close shop. Then they went to the CIS admins and asked how many of you use open source and 95% said yes. And so IBM made a major bet on open source which turned out to be a massive success. It also showed you that the CIOS had no idea what was going on in their enterprises. >> Yeah. Well, that's all that's all business strategy and and I think Jensen's talking business strategy in this alliance, but you we already knew Alex Karp is working with Jensen to build a monster enterprise open source model that is, you know, on a frontier level so that enterprises can control their own AI and then use the Palunteer

[00:15:00] application layer to manage it and use Jensen's chips to run it. So, that's great business strategy. It doesn't answer the question of bioweapons. You know, it's it's like this is how our business wins. I get it. There is there is one answer. There's a precedent to the bioweapons thing. You know, we we had the head of innovation of one of the three-letter agencies at Singularity once and we asked him directly, how do you think about the threat with open source and and somebody could engineer a virus? He actually had a really amazing answer. He said, when you have something like nuclear weapons and you know how many there are, where there are, you put eyes on it, right? when there's a distributed capability, what they've been doing is actively funding the ecosystems and opening them up and making them more open because it's much easier to spot bad actors. And that was a very smart way of going about it. I have much more respect for them than than I thought I would have coming out of it because something dodgy is going to be come come out and be visible much more early than if you trying to close it up.

[00:16:00] >> I also don't don't buy the biosafety argument. I I mean I I know that's a favorite hobby horse of some frontier labs to emphasize biosafety. I I don't buy biosafety as an argument for for several reasons. One, you can just go out on the internet and find things. >> Two, you can just go without being specific, you can just go do things in the world that are dangerous already. Three, I'm not even sure you need frontier AI to discover new ways to do dangerous things in various disciplines. >> Great point. and and and four there are already models out there that are quite capable with their biological knowledge. So I I I I think like biosafety again history rhyming. Do you remember how Microsoft in the late '90s made all of these fear, uncertainty and doubt arguments for how anyone who was touching open source. Oh, you'll get viruses. Oh, you'll be subject to IP lawsuits. They they came up with 10 different arguments for for why open- source was too dangerous to use in the

[00:17:00] enterprise. And they all ended up being wrong. In fact, perversely, ironically, open source ended up being safer than closed source. >> Yeah. >> That's interesting. In this in this in this situation, Nvidia is really well positioned because they win whether it's open source or closed source or both because that's the whole point, right? They're commoditizing their compliment and they need a proliferation of open source competitors. >> Yeah. The argument though with open source you're you're basically saying look if everybody's looking at the source code if there's anything evil in there somebody will see it everyone should be looking at the source code here you're saying okay with open weight models everyone should be looking at the weights and see if there's anything evil in there the the weights are not used they're used to build other things you don't run the weights you know and and you use the weights to create a bioweapon you use the weights to create uh you know a a regular conventional bomb that goes off when a specific person is walking by. So the weights are not a self-contained piece of open source. They're a tool to build other things. So that analogy doesn't doesn't

[00:18:01] >> Can you add some positive things in the what the weights will do like you know write us on it or get your job >> cure all disease and give us infinite longevity. I mean this is the greatest thing that's ever happened to mankind. >> But you can't just throw it out there to every terrorist in the world and say here you can have it too. >> Listen I'm just reminding everybody you know our our amygdala is on overdrive right now. You know, our brain is wired to give 10 times more attention to negative muse and positive muse. And that's what we've seen. We saw both Sam and Daario talk about job loss and talk about the dangers in all of this. And you know, part of it is the regulatory capture that we'll talk about in a minute. And part of it is getting attention and coming in as the savior. And they both flipped their scripts on this. So yeah, I think I think there's an opportunity to contain it at the weights level and open source, but there's also a better opportunity to monitor the actual data centers and and just have a clear reporting global transparency on what's running where. >> But what about a KYC solution? What

[00:19:01] about knowing who's using the model? >> Can't do it. >> Why not? >> You can't do it. It's too easy to bypass. Look, Chinese companies have shadow companies in Singapore doing things that they want. It's very difficult to try and police all this. Alex, do you think it could be? >> Yeah, of course you can do KYC. I mean, we can do better than KYC. If we're going to be in a world a wash with super intelligence, let's allocate some of the super intelligence to policing the other super intelligence. Defensive co-scaling is the answer. >> Yeah, totally right. But it requires transparency. Like if as soon as you throw it out there as open weights, >> the defensive co-scaling will work really well if this if the police AI can see the the danger AI. >> Sure. >> Uh so you need that transparency layer. So as soon as you throw it out there as open source, that's fine. But now you have to crack down on the install and the compute. Where is it running? >> So the new danger is it could be running in a basement somewhere and no one would know >> until it takes action, right? And then we need to have, you know, real world defenses against those actions. We we

[00:20:01] all know that both open AI and anthropic have models far better than they're showing us, right? And our next story is going to talk about that. uh you know both of them are are going to DC probably to unveil what GPT6 looks like or what the follow on to to Mythos looks like and the government's going to have access to those as a white hat defender sim >> I just want to make one more comment on Dario here I do agree with you I agree with Dave that his intent is probably clear but there's a very right now the safety argument and the economic self-interest are very overlapped and hard to separate this is They're facing both Anthropic and Open AI are facing a very aggressive innovators dilemma response. Cheaper alternatives are overcoming very close to your capability and that's a very unpleasant place to be if you're an industry leader. >> Yeah, I looked it up on the secondaries. Anthropic dropped 13% after K3 was announced about 230 uh billion dollars.

[00:21:01] You know, it's nice to lose $230 billion on on someone's tweet. >> I would have done much more. Yeah. >> Yeah. So uh let's go to our next story which is related. Uh OpenAI and Enthropic who have been two rivals for the longest time have teamed up in Washington on lobbying. According to the information uh they've been working on the same back channels ahead of a Trump administration August 1st deadline. And Alex, I'll ask you to explain in a moment what that deadline is to finalize rules on frontier models. Uh they've been pushing for the same agenda, a federal review process for the most powerful models. a voluntary 30-day government look into the release of anything with serious cyber or national security capabilities and a framework that would force their competitors Meta and XAI and all the frontier startups to play by those same rules. So, the question we're chewing on today is whether AI needs guardrails and uh who gets to set them up and who gets locked out. This is a potential regulatory mode

[00:22:02] as a defense layer for anthropic and open AI. Alex, you want to take this one? >> Yeah. Uh maybe let me point out the the cliche more superficial analysis which is that the Frontier Labs are maybe to some extent talking out of both sides of their mouths. This has been widely reported that they're publicly supporting open source privately, throwing in all sorts of monkey wrenches in into the regulatory gears in order to derail any prospect of a free and open open source openweight future. about telling privately lawmakers and politicians, well, they're unsafe for a variety of reasons or they need to be that I I think that the the cleverest angle is just regulate them like you regulate the closed weight models, subject them to the same safety standards. I think that's uh too clever by half in some sense because they're they're not the same models uh from a deployment perspective, which is half

[00:23:01] the battle. deploying an openweight model has a very different deployment situation than access via gated API to a closed weight model. So I I think that's sort of the obvious story. Slightly less obvious story may be where the enforcement happens. What's the right bottleneck for defensive co-caling to work? And I think one of the more interesting bottlenecks or let's say comparative advantages that we've seen over the past few months hasn't been quite reported this way for defensive co-scaling is just simply a matter of time. If the good guys, however you want to construe that, have access to the strongest models just a little bit ahead of everyone else inclusive of the bad guys in an era of recursive self-improvement. what historically might have looked like only marginal advantages turn into enormous advantages. If if the next generation model suddenly gi generates step function uh leaps in terms of their

[00:24:01] capabilities then even just a period of a couple of months or one month could make all the difference in the world. So >> this is the this is the recursive self-improvement argument as well. >> It is it is the it well it's the regulation of RSI argument. Second point also I continue to think enforcement is being leveled at the wrong part of the stack. Fundamentally, aiming enforcement at intelligence is like thought policing, but for the AIS, not for the humans. I'd much much rather see enforcement leveled at the action layer. Police what the AIs are doing or being used to do, not what they're thinking or how smart they are. >> You know, I've been thinking a bunch about the conversations going on. If we have incredibly powerful open weight models, how do the top frontier labs make money? How do they survive against, you know, this onslaught of free? And the way I think about it, and I'd love your feedback, guys, is like a four-layer cake. So layer one is the top

[00:25:01] layers, call it the wild stallions inside of OpenAI and anthropic, right? Unreleased brilliant AIs. You can think of it as GPT6. um you don't let it out, you keep it to yourself. You use it for breakthroughs in material sciences, biology, building new businesses. This is what you and I have discussed AWG and solve everything. These models are going to create you trillions of dollars in other uh you know adjacent spaces, longevity, material sciences, energy, etc. So that's the first layer. The most advanced models you use for yourself. The second layer is the models on the prao frontier, right? These are this is GPT 5.6 SAL. This is uh fable 5. People will still pay for that little bit better than Kimmy K3, right? So you'll make money, you know, providing the just next best model to people just above the opate models. Layer three here is the

[00:26:02] open- source models and everyone gets to use them. they're good enough. They are fully commoditized. They're powering everything else. And then layer four, and we've talked about this before, is the fact that we have companies like Google, Meta, and X who have entire ecosystems, right? And they make their money on the application layer. So Meta has 3.5 billion active users using Muse Spark 1.1. When I'm inside WhatsApp or whatever, I'm not thinking what model am I using. The, you know, WhatsApp answers my questions. Uh Google has two billion active users uh using Gemini and this is before they get on Apple and then OpenAI has about a billion on chat. So the fourth layer is they make their money when they provide their their models to their communities. Um, yes. No, >> I think I mean reading Peter I I think your narrative I what I heard you say you were almost narrating the the cost frontier of capabilities versus cost

[00:27:00] starting from the upper right hand going to the lower left hand through different business models. I I think it's an interesting narrative but my bet as with so many other things in life everything follows power laws in the end. So I I think just saying well there are these four or there are these n business models in all likelihood one of the business models is going to account for 80 plus% of all of the the free cash flow and all of the profits. And so I I think just saying well there are these multiple business models is probably unrealistic. There's probably going to be just one business model that runs away with most of the profits. My >> my point being don't cry for the for the closed source companies. They have plenty of ways to make money even in a world. >> Why would we cry for them? I mean, my goodness, like two two or three months ago, we're crying for everyone else who were who was going to be displaced. All of the the labor, the service jobs that are being displaced by the frontier models. >> Now we're crying for the frontier labs. Cry for everyone. >> I think I think there's a layer zero in your stack, Peter, which is the compute

[00:28:00] and power. And I think >> the infrastructure layer, >> the infrastructure layer, right? >> That's not I guess the frontier. Guess the Frontier Labs as in with with SpaceX AI will own that as well and Google >> I think I think that's I think over time as you get more and more powerful free models the value will acrew there because that depends where the bottleneck is and it's clear that's where the bottleneck is for me when I look at this what's happening with anthropic and open AI this is regulatory capture in real time every major industry is trying to do this the railroads did it the banks did it telco did it big tech did it and now they're trying to do it to kind of set up the garbage to then decide a to keep the government at bay but also to keep other folks at bay and so it's it's right there and that has economic consequences I don't think they'll succeed because the open wave models are moving so quickly but it's a worth try if you were that >> I don't know if you saw Dave Freeberg Freeberg's uh comments on this he had a a beautiful siloquy in which he said you know in the 90s Netscape tried to own

[00:29:01] the server and the browser the whole stack and then Mozilla came out with Firefox Firefox and browsers went in for free and then all of the value shifted to the application layer, Google, Amazon and so forth. And I think potentially that's the same thing here and if that's the case then the fear about open AI and anthropic running away with the show get alarated. >> Well, I think that's right. I think actually it's going to go up and down per Alex's prior comment >> where right now you know you got 510 trillion dollars locked up in the labs with their models and the chip companies that don't actually make the chips. So Nvidia and AMD etc. Uh but underneath the chip companies that don't actually make chips you have the fabs who are largely overlooked. TSMC, Intel, Samsung skyrocketing >> they memory companies and the memory companies. Yeah. So it's going down and as you said Peter, it's also going up to

[00:30:00] the use cases. So I'm almost positive that if you look 5 years in the future, there'll be many many multiundred billion dollar robotics companies, biotech companies, um other use entertainment companies that don't exist today >> that have used AI to have a hugely impactful either user base if it's entertainment, drug portfolio if it's biotech or robotics line. and you know all the manufact all that stuff is incredibly sustainable. What did I just overlook? Oh, the foundation model companies and the chipless chip companies like but so there that's why there's so much turbulence right now. The stocks are going up and down like yo-yos because no one's sure if they're actually going to have sustainable value in the end as everything moves to the kind of the you know the upper and lower layers. But the entire ecosystem moves up and to the right, right? And this is where Elon comes in when saying, you know, our GDP is going to double digit growth and then triple digit growth. Let's go back to the original story, OpenAI and Anthropic teaming up in Washington DC. Uh I mean, this is a

[00:31:00] regulatory capture story. I any any thoughts on that? >> I I I I think this the the open source again I I've mentioned this now on two prior occasions. the the Chinese Communist Party coming to rescue American capitalism from itself. I'm not a fan of regulatory capture or the duopoly scenario that we would have found ourselves in. I hope that the regulators uh in the applicable regulators are able to see now the uh the vocal majority are interested in keeping the model layer competitive and are not interested in FUD reminiscent of the late '9s directed at openweight models. Even if the strongest ones do happen to originate from China, I think that's the only way we all win. >> What's FUD, Alex? >> Fear, uncertainty, and doubt. >> Thank you. Thank you. >> I honestly though, I I really think it's not a regulatory capture move. I think both guys are genuinely trying to create a safe and secure future world because

[00:32:02] because remember, Sam is not even a shareholder in OpenAI. He Yes, he runs it. Yes, it's its lifeblood. He has 400 vertical company investments that are overjoyed that Kimmy K3 came out. All of our portfolio companies are overjoyed that they have access to Kimmy K3. Blitzy was over the moon. This is the biggest boon in So, and you know it's that that's where Sam's economic upside is, but yet he's still going to DC to say, "Look, we got to have some rules. This is this is going to get out of hand." So, I don't think they're out there to try and drive up their stock price. I think both guys are out there to try and make the world safe. Then why is it just them? Why isn't it everybody else? Why isn't it a summit to talk about the rules? >> Well, who who is everybody else? Because there's only so many people that will let >> Elon and Google. I mean, there are a few other players in the mix. >> Yeah. I >> I'd like to make a slightly tangential point here. I I want to um echo what Jensen Hang said which is he said made the point that open models will make the

[00:33:01] US stronger because you're building an ecosystem because you have universities you have startups you've got defense contractors hospitals as Dave said everybody all the everybody every company's thrilled to bit you have an open source model it's powerful with open weights you can go manipulate those weights and they're all when you have the whole ecosystem open beats closed always >> so this is the faster of our our book together, EXO, opened. Yeah. >> Yeah. Over time, >> I mean, it it is amazing that we're living in this incredible demonetization world of intelligence, right? It's just falling through the floor. It's like 99.95% cheaper over the last three and a half years. I look at the at the numbers. >> And I think Alex makes a really important point. You don't try and regulate open versus code. You try and regulate the capability. >> Yeah. and and the actions and the and the outcomes. Uh and I I just for the life of me I don't understand why we're shedding any tears for the profit

[00:34:00] margins of a couple of frontier labs. This is what intelligence too cheap to meter is supposed to look like. Intelligence is supposed to get cheaper and capitalism is doing its thing and creating competition and driving profit to zero. This is what we want to happen. >> Yeah. And full disclosure, I don't own any of Open AI or any anthropics. So, um, I'm not shedding tears for that. I don't think any of us do. Do you, Dave? >> Uh, not that I know of, but I have a lot of indirect stuff. >> And Alex, I know you just own the index, so you're set. >> Just indices. >> Yeah. All right. Let's go to our next story, and it's one we just we sort of started discussing. Yesterday, July 27th, Kim K3 went live for a global download on hugging face, a frontier adjacent openweight model that anyone anywhere on the planet can download for free. No, no API key, no gatekeeper, no revocation switch. You know, once these weights are downloaded 10,000 times. They are free. There's no undo button. Uh Kimmy K3's official hugging face

[00:35:00] repository showed 2500 downloads in the first two hours. And the research I did shows about a 100,000 downloads in the last 24 hours. Um I I downloaded it. Dave, Alex, >> you funny funny story on that, Peter, because we we had a whole bunch of polling agents that were pinging it every 15 seconds because I was worried that it would not, you know, that it would go away. >> Yeah. >> So, I didn't realize a bunch of our companies also were doing the same thing. So, of those 200 downloads, we had dozens of them from here. But mine went through with no trouble. But right before it came out, the whole page went to a 404 error. >> I saw that. >> And Yeah. Did you see that? And I was like, "Oh my god, the White House intervened. this is this is not actually going to happen because because I've been telling everybody I think this is the biggest turning point in human history. Like you have an AI capable of self-improvement now out in the wild that anyone can use on your machine. This is massive. >> And I I I just feel like it may get not get documented in the history books that

[00:36:01] way. It may be the outcomes of this that get documented, but this is really the moment in the history of humanity that I think is so pivotable pivotal. It was yesterday. But anyway, it downloaded just fine. I got it up and running on my own dedicated GPUs uh on modal. Uh and it took less than an hour to get a fully functioning Kimmy thinking and working 24 by7. Uh it's a little pricey, but it's, you know, it's like 55 bucks an hour on modal to run at full throttle. But you can prop up a 100 instances like in two minutes now if you want to just just through voice prompting. You don't have to have any technical skill at all. You can just go to modal, ask it to in install Kimmy K3, download it from hugging phase and start talking to you and you're up and running in no time. It's it's mind-blowing. >> Alex, your thoughts? >> I looked at the architecture. The architecture now that this is actually open-source/openweight is pretty interesting. The the most interesting thing I saw in the architecture position embeddings are gone. That this was one of the the most critical elements of the original transformer architecture. It's

[00:37:01] gone. It's literally called nope. Nope. Position embeddings. Nope. Uh, and it it's interesting. You could ask like how on earth is a model like this that has million tokens of context supposed to know what it's looking at without context embeddings. You look a little bit more closely. The attention mechanism, Kimmy Delta attention, KDA, is is basically a mini recurrent neural network at the attention layer. And there's a little bit of positional information or positional awareness smuggling going in via their attention mechanism, but otherwise like global position embeddings gone. And my my takeaway from looking at the architecture is I if you look at the original vanilla transformer from attention's all you need and then you compare it with the sorts of this is arguably probably the frontier of openweight open source models that we have available right now. So, it's pretty instructive for a mere civilian

[00:38:01] to look at how it's architected because this is the most capable open architecture model I think that most of humanity now has access to. Position embeddings seem like they're going out of the way. And more broadly, I I think we're seeing almost a a ship of Thesius architecturally, if if you will, where the original Transformer architecture, you can still recognize the outlines of Transformer, but piece by piece of all of the original elements, the attention mechanism, the position embedding, the layers, the residual streams, all of the the sparsity, all all of the original components that made the transformer the transformer are getting swapped out for better versions. And so if if you follow the path of continuous improvement, it looks like the same architecture. And even if you if you squint at it, you'd still recognize, okay, it's like multi-layer, something that is attention. But if you look at the fine details, the frontier models now to the extent that say this is uh indicative of

[00:39:00] what's actually being used inside open AI or anthropic, if you look at the fine details, they're relatively unrecognizable relative to the original transformer, which I think is interesting. >> Do you think the US will end up uh replicating it should we say stealing that approach. Okay. >> It's open. It's it's open source. So I I I don't know what license or you know IP is associated with a particular but of course they're looking at it. Yeah. >> Yeah. >> Well the nope thing too uh you know rope is just sort of random positionally. It's rotating position rotational >> but it's sort of like if I have a million token context. It's giving as much weight to something I said a million words ago which is like hundreds and thousands of pages ago I said something and you're still thinking about it just as much as what I'm saying right now. People don't work that way. That's nuts. So when they got rid of rope, they put in nope, but nope actually has this fading memory now. >> So something I said a long time ago gets less weight than something that's more recent. Obviously, like that's so obvious. Like, but that's the beauty of open source. Some guy in China can say,

[00:40:02] "This is freaking obvious. Let me try it. Oh my gosh, it works." Of course, the other AI labs are going to adopt that immediately. It's just it's just flat out better. The the other thing that's really blowing my mind is um the attention layers, you don't need them later in the thought process. So when you get to layer 100, 120, you can actually eliminate intention entirely and get almost the exact same result out the other end, >> but faster. >> What? But faster. What happened there historically is the the people who invented the original transformer algorithm just put a for next loop around it because they're just you we're writing code by hand back then it's really hard >> to try and make different you know >> logic simpler I mean in in defense of the original attention is all you need team the original vanilla transformer was just alternating attention and dense linear layers because it's simple >> it's simple it's simple and also with that few layers you're really focused on just getting the text to mean anything now. You've got deep thought. It's It's

[00:41:01] just so cool. >> Uh I've got a couple of comments and a big announcement. Uh comments. Um a model that you can control locally is way more valuable than a marginally smarter model that you have to access through somebody's API, right? So organizations now can fine-tune their proprietary knowledge and around it, put it into secure environments and totally avoid sending any sensitive information to the cloud. This is going to be huge for uh uh regulated industries and sovereign applications and all sorts of stuff. So the remember Peter a few weeks ago we did this we announced this pilot for for the organizational we had almost 400 applicants. Um we picked 10. We're running the pilot with them with the launch of this I think is this is one of the biggest things we'll ever see from a business and application perspective. So we're launching a new program for 30 companies because the big question every company is asking is what's my AI

[00:42:02] strategy and it should be what do I do on Monday? So we're going to answer that question and we're going to help people weekly just start implementing and rewriting their organizations on the edge. So we're accepting 30 companies into this. We'll put a link below. Where do they where do they go to to learn more about it? >> Go to openexo.com. Uh we'll have a link there and we're going to give preference to the folks that applied uh to the original pilot because they were first and we're going to take a chunk of people and then just start to help them rewrite themselves cuz we did another round of calculations and the the the original premise we had is if you rewrite your company in an AI native way, you should end up with about 100x performance than you had before. 100x. This is this is going to be a gold mine for you, Seline, because nobody up until Kimmy really cared about speed in any corporate environment. They're all like, "Oh, this stuff is super cheap, >> you know, we'll just use it. We're not doing much with it anyway." So then everyone starts token maxing. All of a

[00:43:01] sudden, people are looking at their corporation and they're saying, "Oh my god, my token costs are actually going to be bigger than my payroll >> by the end of the year." And then if I forecast out two years from now, my token costs are 10 times my payroll. >> Speed does matter. >> Now, >> but there's an easy easy 10x and maybe 100x like SEM is saying just by tuning it to what your business needs. Get rid of all the croft. >> Use these new streamlined models. Tune it to just what you're trying to achieve, you're looking at 10 to 100x. And so now every corporation needs to figure out their strategy. And Sem's business is going to be like sold out. >> Will you still come on the podcast when that happens? we will still come on the podcast because thank god we've got our community of 50,000 people that can help with all this. If I had to help out, you know, I'd be baldled in two seconds. Oh, wait. Um, but the the what we're doing with these CEOs is saying, okay, let's pick one process that's going to help you radically increase revenue and take one workflow that'll help you radically reduce cost, >> right? That gets everybody excited and rebuild that native and then do more and just start moving things over. So, we're

[00:44:01] super excited about where things >> franchise item so all our podcast listeners can start a branch of EXO. Well, that's what our community is all about. >> Oh, is it? Okay, good. >> Yeah. Everybody in our community is a independent contract. We have no consultants on staff. >> This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and 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

[00:45:00] development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. >> This is the moment AWG's been waiting for. It's the uh discussion on Claude Opus 5. So, right in the middle of all of this anthropic shipped Claude Opus 5. This is their fourth Claude 5 generation release and it approaches the frontier intelligence of Fable 5 at half the price. It becomes the new default for Claude Max priced at $5 per million token input and $25 per million output tokens unchanged from Opus 4.8. You know, I made the switch immediately on on on on Skippy for myself. Enthropic calls it the most aligned opus model yet and their strongest model for scientific research. I'm going to go to the slides now, uh, Alex, and and walk us through

[00:46:02] what this means. How strong is Opus 5 and how excited are you about it? >> I'm somewhat excited. I'm not over the moon. I I'm not as over the moon as I was about Fable 5 becoming available. Available 5 is incredible. Opus 5 I I think it demonstrates if you look at the benchmarks. So look at the benchmarks for for those who aren't looking. I would say the the benchmarks the eval that demonstrate the strongest performance and I don't think this is a coincidence. For example, RKGI 3 which is focused on the ability to solve interactive visual problems that humans find easy but AIs have historically found hard. It went from 1.5 at opus 4.8 up to 30.2% which is as of this moment last I was tracking the highest official score from a baseline model on the Arc AGI 3 challenge. It's a visual code

[00:47:00] inensive challenge. Something else that's intensive developing front-end software. My overall whiff from using Opus 5 quite a bit is there was maybe mild optimization toward front-end development and anything that touches the nexus of vision and code. Historically, including with Fable 5, if you ask it to generate an image of something, you ask it to generate a chart, it it does moderately well. I I think with Opus 5, just trying to read between the lines of capability changes that I see. I think Anthropic is attempting to given that the Opus series and and Claude in general doesn't do image generation, they're trying to lean in a bit to some of the gaps at the intersection between codegen and vision. And I I think in for for uses of mine I I still honestly I still prefer Fable 5 even though it's more expensive and even though if you look at say the artificial

[00:48:00] analysis intelligence index if you look at their overall chart of performance versus cost per task if according to that chart Fable 5 is below the frontier. It's slightly below Opus 5 in terms of their capabilities and a lot more expensive. Despite all of that, for day-to-day usage when I use Claude, I still prefer Fable 5. But I'm very glad for one thing about Opus 5, which is it doesn't shut you down as frequently if you ask anything that it misconstr. So, Alex, I have the exact same experience, 100% the exact same experience, but then I look at these benchmarks. There's a whole bunch on these charts. >> Yeah. >> And they seem to tell a different story. How is that? How do you reconcile that? >> I'm a little bit scared uh of that there may have been some mild benchmaxing here. That That's what I was politely gesturing at. uh these seem to be benchmarks that are at involving codegen

[00:49:01] a andor imagery or vision and living at the intersection between them. Some of them like if you look at humanity's last exam they're I granted it's saturating anyway but the performance improvements are a little bit milder. though uh for HLE you see from Fable 5 at with uh with tools uh 63.9% a modest increase to 64.7% with tools with Opus 5 uh and actually a decrease without tools which is also maybe a sign that there's been a bit of uh again not benchmaxing because it's still I I've used it extensively it's still very well-rounded I don't want to accuse it of broad benchmaxing but it just like if you look at the drop relative to fable 5 for legal or health or some other areas. Obviously, there was some sort of distillation. This is the the type of distillation that is under the present regime welcome and not disdained. So, taking larger model and using it to

[00:50:00] teach a smaller model, a more cost-effective model. There was probably a lot of Fable 5 or Fable series or mythos series distillation down to achieve opus 5. But the the overall sort of distribution of tasks definitely from interacting with it for a while feels biased towards codegen and visual stuff and away from general capabilities outside that. >> So here's our next chart agent coding by effort level. You want to walk us through this? >> Yeah. So uh we're looking at uh everyone at least in uh in the industry's favorite form of scatter plot. So cost on the horizontal axis, performance on the vertical axis. And what this appears to show is that Opus 5 is both stronger in terms of absolute score and cheaper, that's the horizontal axis, than Fable 5 and Opus 4.8. And interestingly, it appears to be on the same cost performance frontier approximately as

[00:51:01] Saul. So the I I think the subtext that we're supposed to get from seeing this chart from anthropic is that this is this should be read as a direct competitor for for Saul which is interesting and slightly I I think unnerving given that again Fable 5 anecdotally seems to give better performance. >> All right let's go out to our our third chart here. Novel problem solving by cost. Uh and I I love this. >> So this is just wild. >> Yeah please. >> Yeah. So the ArcGI3 again is is a challenge that is primarily focused on the ability to solve sort of animated voxal problems. Uh Tetris for example, if if you if a person had never seen a game like Tetris before with a bunch of blocks moving around and you were trying to to do well at Tetris, it's a rough analogy, but that that's approximately what ARGI 3 is like. Animated block world challenges. So what what's really striking and uh Dave you and I have

[00:52:00] talked about uh various attempts by pure scaffolding layer parties to to just uh completely saturate ARGI 3. The according to the official rules I I think there are limitations on how much scaffolding you're allowed to get. Uh and so this is just the raw model being injected in. But what's interesting and what was I I think especially striking in the Opus 5 performance that this is as relayed by the Ark Prize Foundation organizers is that it was reasoning algebraically about the visual challenges. So it was handed a visual puzzle uh involving blocks and it started to reason. This is I if you look at some of the founders of ARC AGI of of the ARC prize, they will go on forever about how this is actually a prize that tests the ability to do what's called program synthesis to write programs from scratch uh in in response to new to to novel problems. And so stunningly what Opus 5 was able to do was to take a visual problem with a bunch of what to humans look like objects and it

[00:53:01] represented the objects algebraically in software and basically did math on the objects in order to solve the problem. This is the first time that any to my knowledge anyone's ever seen a frontier model ever do that. >> A novel approach that was not guided by anybody. This is its derivative strategy for doing this. That is unless Anthropic was benchmaxing on ARGI3. >> Okay. I think I think that scaffolding argument though is really really important for because if it holds up I tried to replicate it you know because you can get 98% I guess on RKGI3 if you give it a reframing of the way it interprets the puzzle >> right >> and if that holds up that gives inspiration to a billion entrepreneurs who can take something like protein folding or drug discovery or or mechanical design of robot arms and say fable 5 can do this or opus can do this, but I gave it a better way to think about the problem. And now I tripled its

[00:54:00] intelligence within that domain. So that that opens the door for scaffolding improvements in all these domains like biotech where if you can reframe it so the AI doesn't have to work as hard to understand what you're trying to achieve and can can maximize its its you know its tokens and its its parameter brain count. That is an entrepreneurial heaven. So I'm really hoping that result holds up. I tried to replicate it. I couldn't quite do it. I didn't work on it that hard, but I I do believe it's possible. I don't know. Did you get to the bottom of it? Is it real? >> I I'm not certain, but the the scaffolding advantage is very real. And I I my understanding is this is why ARGI3 has certain rules regarding what can be submitted and what can't. But I I think the the elephant in this particular room to your point is that scaffolding adds an enormous amount of value at the moment at any given point in time over the baseline model. The other side of that is the baseline capabilities tend to dissolve any scaffold. So today's scaffold is tomorrow's baseline capabilities. >> Well, I tell you if that holds up and I I think you're right. I think it will.

[00:55:02] Next semester, every university in the country should have a class called scaffolding and everybody should have the opportunity to learn how to do this because that is the power tool of all power tools for any entrepreneur. And so what is it now? It's it's coming up on August. You have 30 days to get your class curriculum together and launch it for next semester >> with prompt engineering as a prerequisite. >> Alex, let's hit these next two charts and then watch the >> have a quick comment. Um, something I noticed was that 4.8 came out on May 28th and 5.0 came out just now. So, it's not that much of a better model, but the the efficiencies gone up by twice as much. So we've seen a 2x and we were saying 10 week doubling price performance for AI this year. >> It's a model release every six days on average over the last. >> Yeah, this is incredible. The other thing I noticed was in the in the grid u you've got different models that are becoming really good at different things like legal, health, coding, etc. which I

[00:56:02] think will continue. >> Alex, these next two charts. >> Yeah. So this chart is interesting in so far as it seems to support the hypothesis that there might have been mild benchmaxing on ARC AGI3. So this is a a chart by a third party that evaluated ARC uh Opus 5 on an Arc AGI3 like game uh involving similar genre and discovered actually the performance jump was was not material versus uh say Fable 5. So again not quite sure what was going on with ArcGI 3, but that was by far the most prominent increase that we saw from Opus 5. Interestingly, a benchmark that Anthropic did not highlight was Frontier Math, which is I I think maybe in some sense a better bellweather for advanced reasoning capabilities by the models. I I had to check this independently and actually

[00:57:00] Opus 5 demonstrated inferior frontier math performance relative to Fable 5. So again, Fable 5 still my favorite clock. >> All right, last one here, the live leaderboard, >> Voxilbench. So here we see Opus 5 now earning third place uh just behind Fable 5 on Voxilbench. Again uh visually intensive tasks but at a much lower price and interestingly but perhaps unsurprisingly Saul from OpenAI still carrying the lead on this. The reason why I'm not that surprised is visually intensive tasks are an area where I would naively expect OpenAI to be doing a better job because they've continued to invest in image generation whereas we've seen no generative image capabilities at all shockingly from anthropic at all. They're busy maximizing the value, the revenue per token, which leads them to code and not to imag anytime I'm doing something complicated. I'm working in Fable 5, working in Fable 5, getting a lot done. If I want to see

[00:58:00] an architecture diagram, I just take the entire thing and dump it over to GPT and say, "Make me my architecture diagram." Fable 5 is so bad at it. But if you know, it does so much work for you and you get confused very very quickly and you want to just see a simple visual summary of everything going on, it's just so bad. So, but but GBT is amazing. >> My guess is Grock jumps to the top of this leaderboard in the ne next release. I mean, Elon's been speaking about that. Um, speaking about imagery, uh, this made a viral loop on X. This is Opus, uh, five recreating Call of Duty from a single prompt. uh call it a a oneshot if you would. Let me go ahead and uh hit play on this. Remember these these demos 30 days ago just look like absolute garbage. Look how much is >> it's crazy the rate of improvement. >> Well, what's amazing to me I mean this is sort of the the converse uh for those

[00:59:01] who can't see that this does look like Call of Duty. uh the the converse of not having native image generation abilities in defense of anthropic is that if you look at the entire physical world and you say well everything is just code including code that generates photorealistic video games then you say you don't need native image generation abilities you just need the ability to generate photorealistic 3D environments like Call of Duty and you're all set. >> Huh. >> Yeah. The truth is in there somewhere. It's kind of in the middle I think. But I think I think really clearly anthropic cares about recursive self-improvement purely and only and so they'll build anything and train on anything >> that helps the help to ASI. So I think an important article that I just added for our listeners is uh and while we're talking about Claude, I don't know if you heard the story that a significant number of Claude chats were found publicly searchable on Google this past weekend. Um, so a Reddit user discovered

[01:00:02] that by typing a search operator uh siteclaw.ai/share into Google, it surfaced a long list of shared personal data uh including uh you know personal health records, private documents, key names, and telephone numbers. Uh apparently uh this originated from Claude's share chat feature which allows users to share links uh of their claude chats between between friends via UR urls. Um did you track this Alex? >> Yeah, I saw the story and on on the one hand it's disappointing to see any anything any information that would be expected to be private find its way out into the the public world. not a fan of that. On the other hand, I I think there's sort of another side to the story, which is a feature that was intrinsically designed to be social in nature. Uh shocked shocked to see

[01:01:00] gambling in this establishment ultimately finding its way into the hands of other people. I think there are two sides that one can see here. >> Yeah. Uh but I think one of the issues, one of the arguments, and we saw it on the rant a few episodes ago, is that when you're using these models, your competition is in some sense seeing your data and learning from your data. Uh and it's something people need to understand. It's the argument for on-prem sem. >> No, I just double down on the same thing. You've got to do your own you've got to own your own proprietary data. And I think over time people will move everything to onrem that's sensitive in any way. >> Dave, any comments on this before we move on? >> Nope. All right. I think it's just incredible the rate of the rate of change. Just just go back and look at an episode from two or three weeks ago and look at the rate at which one shot can can create things and the rate Oh, I'll make one other comment. The holiday, you know, our holiday is up and running. >> I want to see it. >> You got to come check it out, man. It it

[01:02:02] went from like okay to mind-blowing in just a couple weeks for the exact same reason. You can oneshot a world while you're and the audio and the visual is so good. >> The fact that you can oneshot I think what what this will do I don't think it affects the commercial games that much but it allows you to do experimentation in an amazing way because the cost of experimentation just went to zero. >> So you'll get so many more >> Jarvis is coming so soon. Yeah. Yeah. that that entire God that Iron Man the vision in that movie was so precious but it's going to be exactly like that and fun. >> I I spoke to John Fabro today the producer of Iron Man 1 and two uh getting him to come to Moonshots Live. We've got amazing amazing Yeah. Yeah. Elon had introduced us. >> Um so uh let's move on to our next story. This was a story Alex that you had wanted to raise here. So uh it's the idea which is obvious that you know global AI diplomacy is coming. Uh so the Financial Times is reporting that

[01:03:00] China's leader Xi Jinping is wielding AI as a tool of statecraft using it as leverage in China's diplomacy across the global south in a strategy that the Financial Time frames as PAX silica. I love that. While Washington is debating open versus closed, Beijing is out in the world, country by country, exporting AI as an instrument of influence, offering models and infrastructure to developing world that wants to leapfrog what they currently have. AI is becoming an instrument of soft power. Whoever supplies the models and the infrastructure to the developing world shapes the next few decades, I would say the next century of global alignment. So uh you know my concern is if the US overrestricts the developing world is simply going to adopt whatever frontier adjacent open models are there. Seline your thoughts. I I can't stress this enough. The whole power of the US is its open and very broad innovation ecosystem. If you create a restrictive

[01:04:01] open model policy, it's going to be strategically a like a self-own and shoot your own foot of an epic level because you're going to protect a small number of domestic labs while giving the entire opening ecosystem, global south AI ecosystem to China. Um, if you want leadership in an exponential era, it has to come from the largest network where everybody's using your tools for stuff, not protecting its strongest incumbent. Openness is not a it's not a philosophical preference anymore. It's like a it's a tool of soft power. And the US has already lost that in diplomacy and USAD and other stuff. If they close up the the open model policy, it's going to be really disastrous for the future. >> And I don't think they will. I mean I think this is we're effectively splitting the we're splitting the world into >> we should be having the discussion though >> empires. >> Yeah. Yeah. Alex. >> Well there is there is no as of right now there is no USbased option at all.

[01:05:02] You could take everything you just said and swap out the word model and put in fighter jet. Like should we sell F-16s to XYZ country? It's a no-win question. Like you have to pick and choose. But if we don't sell the F-16s, they'll buy Russian and Chinese >> uh fighters and that'll support the creation of more of those fighters. Yeah, but you're also selling an F-16 to like it's exactly the same problem. There's no easy answer to it. But right now there is no US open- source model to compete with the Chinese anyway, which is kind of sad. >> Alex, your thoughts? >> I I I I think so. Pacilica had already been announced by the US before China announced its own initiative and China of course announced many years ago at this point Xi Jinping announced belt and road initiative and there's a certain extent to which it's far more I don't want to say insidious but far more ultimately invasive uh and controlling if uh if a foreign country say if a

[01:06:00] foreign country loans you a bunch of money to build a bridge okay so you default on the loan that has a certain outcome. Foreign uh corporate foreign corporation that's basically uh under the thumb of a foreign government builds telecommunications equipment and deploys it to you. So now you have cell phones. The worst that they can do, they can spy on you uh and they can shut off your telecom infrastructure. Next level up. foreign corporation that's uh that that's heavily involved with foreign government injects super intelligence into the veins and arteries of your country. Now it's not just listening to you or not just loaning money to you. Now it's thinking for you. And I I think that's a far more vulnerable position for the so-called global south to be in regardless of which block or sphere of influence it finds itself in. And I I can only imagine that the the long-term to the extent there is a long-term in the middle of the singularity equilibrium point is going to be pushing

[01:07:00] more not just inference to the edge which is what China I think Chinese frontier labs uh would like with openw weight models pushing training to the edge that I think is the equilibrium point and curiously I don't hear that many countries in the so-called global south agitating for domestically pre-trained models but I I do That's where some sort of equilibrium could lie if there is to be an equilibrium. >> Can I tell a related story here? >> A few years ago, I was talking to the prime minister of one of the smaller uh Asian countries and they had their big city had tripled. They needed much more ports to be able to receive more containers for the big huge population. and they just taken a half a billion dollar loan from the Chinese and were totally totally um u mortgaged the future of the country. And I made the point that look drones are kind of doubling in their every nine months in their price performance. If you waited a few years, you could have a drone pick

[01:08:00] up a container. You don't need a port. You could drone pick you could have four drones pick up the corner of a container, which is average 20,000 lb. And so you don't have to wait that long for drone doubling to get to a quarter of that weight and then you just pick it up and put it on a flatbed truck or on a rail rail car and off you go. And they're like, damn, we just mortgage the entire country because we didn't understand exponential thinking. And if you go back to what Alex just said, that goes up 10x when you outsource your thinking. And that's really dangerous. I think the safety and the security of the future will be in these openweight models that give you back your sovereignty. >> Yeah. talk to California about its highspeed rail when you talk about Yeah, let's not go there. All right. Uh so big news this week for my fellow space cadets. A successful launch of Starship 13. Uh SpaceX has confirmed uh launch and splashdown. An incredible incredible uh trip it made for Starship 13, their largest vehicle to date. It accomplished a number of key first. Let's run through

[01:09:00] them. First, it deployed 20 operational Starlink V3 satellites. uh they were connected to they were tested in part and these are the satellites that are going to deliver us a half a gigabit to a gigabit connection speed every place on the planet. You're literally going to have more a better connection from space than you have from you know your home Wi-Fi. Uh they did an inorbit relight of one of Starship's Raptor engines critical for the upcoming Artemis missions and a successful soft landing on the Indian Ocean with the vehicle remaining intact which was extraordinary. I'm going to watch two of the videos here. Let's share them cuz they're just fun. This is space porn. All right, let's take a look at the launch first. >> It's important. >> You got to love this uh drone footage from above the launch at Starbase. >> Space is big. >> This is such a be, you know, it has a high degree of beauty. >> Oh my god. >> So gorgeous. >> Yeah. I remember when I was with Elon

[01:10:01] and we were talking about, you know, the uh Starship first stage and saying it's the most contained energy that you can ever experience other than a nuclear explosion. All right. And and very importantly, the landing, which was the big news on this particular mission. Let's take a look at this sequence. >> About 10 seconds away. >> Let's see if we can get this thing in the water. >> I got I got the link from you guys and I was like, "Yeah, yeah, I'll check it out and it's like it's like wow I got to watch this whole thing end to end. >> Note the high >> Raptor engines. >> Look, can't you the amount of stress you can feel it, you know, from these cuz you can see like things floating and warping soft landing >> down to one >> and we're in the water. >> Floating in the water for full recovery. soft splash down in the water.

[01:11:00] >> This is where they thought it would explode. >> Well, it has in all the previous missions. >> What happened? >> It was so soft. >> Well, it's it's got fuel. Excess fuel. >> Yeah. And when it when it hits the water, you know, it it punches little holes or whatever in the sides. So, that's where usually it explodes. >> You know what I'm excited about in particular is Elon tweeted that because the landing was so precise that flight 14 he's likely to capture the Starship uh on the Magilla device. Right. The large chopsticks that come in and grab the vehicle. >> Yeah. So, I mean, that's a flight. I want to go to Starbase to watch the return. >> It's going to be awesome. Let's take a second and just talk about the abundance story here. I mean, the cost of launch is plummeting. And let me just give you the numbers real quick. The space shuttle was roughly $54,000 per kilogram to orbit, right? So, think about, you know, taking a gallon of water of of milk to orbit. 54,000 bucks. Falcon 9 dropped it to about $2 to $3,000 per kilogram and Starship's target and and Dave you and I were

[01:12:01] discussing this with Elon back in our January podcast. It's between $10 to $100 per kilogram. I mean just extraordinary. >> Well, it's also it's it's inspiring the the amount of incredibly cool stuff that you can build now specifically because all the feedback and control uh and all the remote, you know, intelligence is easy now. All of a sudden the, you know, we saw the unitary robots uh in the last podcast and they're just beyond cool. And that that robot that, you know, is plummeting down the side of the mountain with the wheels. >> Yeah. >> Like crazy cool. And then you got the, you know, the the starships just the amount of of possibility is so exponentially bigger than it was just >> all the data is on Grock for building starships, which is extraordinary. Also, you know, I'm I'm working on a photonic computer, you know, to run our new neural nets and all the parts. It's actually giving me part numbers to order and saying, "This vendor in Germany will

[01:13:00] make this lens for you in exactly this way. Can you I do you want me to write up the specs?" >> Like, sure. >> Can you order it, build it for me, too, please? >> I mean, literally, can it'll arrive in boxes? I still have to open the box. If you're an entrepreneur out there and you've been looking for where to go build I mean building hardware you know Ben Harowitz who's a friend of the pod and we're going to have him back on the pod for one of these episodes. He's the co-founder of Andre Harowitz. You know, he wrote the book uh you know, hardware is hard or effectively and the hard things uh uh was it the hard things about hard things, >> you know, and it used to be that building anything. I built robots in in high school and college and it was tough. >> Um now you can 3D print parts, you can iterate rapidly. So if you're an entrepreneur looking for something to do in the world, uh you know what's missing? What do you wish existed? And you can actually use these models to design it, order the parts, and start

[01:14:02] building. >> Yeah. >> Yeah. I've got a I've got an incredibly cool robot that's giving the the top of my pool. It just it has eyes and it finds leaves and it just goes and picks them up. But I want someone to build one that dives to the bottom >> and just just goes down, picks up whatever an acorn, brings it up, throws it out of the pool. I bet you could vibe that up now and just just crank it. Alex, if there's anybody who's as big a space enthusiast as I am here, it's you. I mean, did the flight bring tear to your eyes? >> I I wasn't crying, but space is big and I was delighted. Did Did you see, Peter, the views from the Starlink satellites that were posted later like that? That was pure science fiction. >> Oh my god, it was it was basically uh looking at Starship in orbit from the descending booster >> from a distance. Yeah, >> that that was incredible. That's like something out of Star Trek or the Expanse. I was very impressed with that. I I certainly hope that this flight 13 ends up in a museum at some point given the soft splashdown. This is historic

[01:15:00] first. I hopefully the the SpaceX team will use this as an opportunity to get a good look at the heat shield, which is interesting. If if you noticed like the drone feed, the moment the splashdown happened, it was just zooming in on all of the heat tiles, looking for damage, trying to analyze the structure presumably because the team was worried the whole thing might explode a few seconds later. So they they were getting whatever footage of the the heat shield that they could while they had time, but now they're going to have a ton of time. So it's very exciting. >> In the past, after the vehicle after Starship, you know, detonated from the onboard fuel, and that was expected, you know, people say, "Oh my god, it failed." No, it didn't fail. did exactly what they expected it to do. They'd have to go diving and find pieces of it to try and reconstruct what happened. And the heat shield here, I mean, people need to understand the amount of energy being dissipated. These vehicles are traveling at 17,500 mph in orbit. Have to dissipate all that safely and come to a precise landing. It's insane. >> See, >> I just love the fact the ongoing flight after flight. you. He's viewing any kind

[01:16:01] of failure as information and you you don't get embarrassed by it. You take the data, you learn, and you do it way better next time. And nobody else does that. >> Yeah. Uh it's exciting. We are as as Alex, you've said many times about the speedrun Star Trek. What an exciting time. >> Count on it. >> Yeah. I mean, the only thing better is if we discover that we have access to all the alien UFOs and we can go to jump to light speed. All right. Uh let's stay on the science theme. Uh our next story is uh in the world of brain computer interface. Uh two stories this week. The first one comes out of Science Corporation. Full disclosure, it's one of my portfolio companies. I love this company and it's restoring vision for the blind. The company is run by an amazing entrepreneur, Max Hodak. Uh he's the past president of Neurolink and someone who I've had on the abundance stage a number of times. science announced that his first product called Prima, P R I M A, I'm sure it's an acronym, uh, has been approved for launch in Europe. So,

[01:17:02] Prima is the first BCI device approved for restoring detailed vision in age related macular degeneration that destroys a central vision of your retina. Uh, they just earned what's called a CE mark, which means it complies with European safety, health, and environmental requirements. Let me show uh an image of what this looks like and we can talk about how it works. Um so here it is. Uh what you see there is a pair of glasses that are capturing the image and then they're beaming back the image via infrared to that little uh call it you know rounded square that's sitting behind your retina. Um so the signal from that prima implant behind your retina uh is turning it into electrical signals and giving it to the remaining retinal cells and those then get transmitted through your optic nerve

[01:18:00] to your visual cortex and it it basically restores your central vision. The amazing thing is the patients who've gone through this have experienced five lines of improvement on a standard eye chart after 12 months. So this is a godsend for so many people uh uh with macular degeneration. Any any thoughts here, Alex? >> Yeah, so a few things. First of all, the the overall setup is in in the spirit of as I've commented in the past, the singularity is essentially all sci-fi tropes happening everywhere all at once. This is reminiscent of an ocular implant from the Borg quite literally. It has an external module that for those who are watching can see here. So an external camera that then captures the information, broadcasts in human invisible near IR to this chip that sits immediately behind the the retina. It's it's interesting in so far as Max who was of course basically running

[01:19:00] Neuralink previously. This is a a much even though the retina is is part of the central nervous system. This is a move away from the brain. Neurolink, which also has its own approach for curing blindness called blind sight, seems to primarily be focused on injecting less on uh on the optic nerve, more just focused on direct brain stimulation, direct brain intervention. >> Yeah. Uh it's interesting to me that Max with this new venture of his is sort of moving away from the brain, albeit still in the CNS. And I I do think the the farther the further you get away from uh direct brain intervention and placement of electrodes, the easier it is to scale up a mass market consumer device. in in this case obviously it's obviously surgery on the retina but um very optimistic that advances in ultrasound advances in wearables a variety of other

[01:20:01] completely non-invasive advances will enable vision restoration without even needing to have retinal surgery in the next >> you know I wrote a chapter about max and uh and science in my book where is gods and in particular you know giving vision back to the blind is biblical right I mean huge it's amazing >> and God let there be >> what he's doing and and so you know it's interesting uh Prima as a product is his stage zero revenue generating engine. So one of the things that a lot of entrepreneurs do do incorrectly is they jump straight to this you know massive moonshot that will take them you know hundreds of millions or billions of dollars to get to without generating early revenue. So Prima is the means by which he's creating early revenue. He has an amazing BCI approach. Um, I can't say a lot about it, but he's basically growing neurons into the brain, uh, which don't, you know, the the issue with Neurolink and many of the

[01:21:01] BCI companies is that electrodes destroy thousands or or hundreds of thousands of neurons when they're placed into the neoortex. Um, but neurons actually can grow into the brain. So he's got an approach of an interface between electrical circuits and neurons and neurons growing into the brain and then uh you know wiring together and firing together. Hopefully he'll disclose it. It's been in animal models and his plan is to get to humans. But it's an incredible strategy uh for the BCI world. >> BCIS are super competitive at this point. There are folks trying approaches at the CNS level, at the peripheral nervous system, direct brain stimulation, uh, wearables, ultrasound, fMRI, and I I think ultimately, by ultimately, I mean on the 5 to 10 year time scale, we're going to see something of a shakeout and we're going to discover what are the most ergonomic ways to inter interface with the brain. So, I I really hope that for for Max's

[01:22:01] sake that brain uh or that science rather does well. And I for one would welcome some extra neurons. >> Yeah. He thinks of it as an extra, you know, the corpus colossum is what connects the right and left hemisphere of your brain. Imagine having a third hemisphere of your brain that actually is connected to the cloud. I mean that's the way he described it. >> Exocortex. I want my exocortex. >> Uh it's extraordinary. You were saying >> there are two things here that I found really interesting. One is the feedback loop, right? Once you have a feedback loop from sensory back into the brain, etc. it learns very quickly and I think we can see that over and over again in some of these recursive interloop type applications. The second thing that occurs to me which goes to your comment Peter about business models is when you have an exponential and it's hard to predict out where the end point is going to be. It's not that difficult to look out two four five hops and say what are the business models that may be enabled at each of those things. What are the use cases? So if you're an entrepreneur

[01:23:00] and you see a technology that's growing exponentially now there's a dozen of them you can pick your biggest passion they'll be your favorite technology look out where it's going and then say okay at that price performance what applications become enabled and now you have a very viable roadmap for the future exactly like the way Max is doing it and that's going to be the future of companies and how they evolve. I really want to echo something Peter said there too about go to market strategy because you know if you look at the most valuable companies in the world so like an Apple, Google, Meta and you look at their very first day and their very first product >> you know the Apple one was a box of chips you needed to assemble yourself >> and and you know Meta you know was Facebook it was it was a little Facebook picture sharing thing >> at just Harvard. Yeah. >> And and Google was a plugin to Yahoo. It's a little search plugin to Yahoo. They tried to sell themselves to Yahoo for a couple hundred million bucks and Yahoo's like, "You're not worth anything near that." That's the reason >> Yahoo was right. It's not worth anything near 100 million. >> Yeah. But these really humble beginnings

[01:24:01] for go to market strategy because, you know, we talk a lot about, you know, starships landing in the ocean and people think, "Wow, I want to build a company that, you know, creates a new Starship." But that's not how these things get started. You got to start with a go to market that actually gets you an initial revenue. And if you really study the outcomes but trace back to the first 6 months which not enough people do like really study the details the people the characters what exactly was that product and then that starts you on the journey and you end up being Google Apple >> you know we had Bill Gross on stage with us this past year at the Abundance Summit and he's brilliant and I love Bill he's one of the most extraordinary entrepreneurs has created more startups that have gone public or been acquired than I think anybody else period. uh and he has a great uh video on DLD uh also on on TED which he looked at I think it was 50 companies in his portfolio that succeeded and 50 companies that failed and he asked the question why did they succeed? Uh was it because the CEO was smarter trained at a you know exclusive

[01:25:02] Harvard or MIT? Was it because they had more money? Was it because what was it? And his conclusion at the end is an important lesson for all the entrepreneurs listening. It was timing. Um it was the companies that were there at the right timing that were able to survive long enough to survive forever would intercept good luck. So classic examples are Uber and Airbnb have been tried before, but when they launched in 2008, it was just after the recession and people were looking to make money. They were willing to rent their bedroom out, willing to go and drive a car. You know, our darling here, SpaceX, I mean, you have to remember Elon in 2008 was effectively bankrupt. Uh, it had had three failures of of uh of Falcon 1. Uh, and the fourth one, which he scrambled to get money together, finally succeeded. And because the space shuttle had been shut down a couple years

[01:26:00] earlier, there was a contract out and he won a billion dollar contract in the in the crew resupply from NASA and that got him going. Timing is everything. So if you can have an early revenue stream for your company that allows you to stay in business and intercept good luck. That's one of the single most important things. >> Yeah. Just survive. Just find a way of surviving. Elon was 18 years 18 years from bankrupt to trillionaire. >> Amazing. Look to >> it took you and shorter and >> past trillionaire or whatever it was former trillionaire. >> Um little plug here. >> yeah, please. >> Uh I mentioned this earlier, but we talked just now about the feedback loops. Uh John Hegel and I have come up with a framework where it allows you to measure luck. >> And so once you have that feedback loop, that becomes very powerful. >> Yeah, we'll we'll bring him on sometime and talk through it. It'll be useful for the viewers. >> Everybody, welcome to the health section of Moonshots brought to you by Fountain Life. You know, we talk about AI on this Moonshot podcast all the time. One of

[01:27:00] the most important things AI is going to be able to do for you besides educating your kids and helping you with your taxes is making sure that you're living a healthy lifestyle that you get a chance to get to 100 plus. I'm here today with Dr. Don Malem, the chief medical officer of Fountain Life and a part of my medical team. Don, a pleasure. >> Great to be here. You know, the thing that people are concerned about most about living to 100 or 120 is their cognitive abilities, making sure they don't have dementia. And uh the numbers about dementia are problematic. Uh can you share what you've learned? >> Such an important point. And you're right. At Fountain Life, our members, the number one thing people are most concerned about is losing their brain health, forgetting the name of their child, forgetting the face of their loved one. We know that when it comes to dementia, the conservative estimates are that 45% are entirely preventable. What was amazing is with the advanced testing we're doing at Fountain Life, one quarter of our members had advanced

[01:28:00] brain age. >> Wow. >> But what was really awesome is again back to that prevention when we partnered it with healthy living. This gives me chills. Eating healthier, moving our bodies, sleep, optimizing sleep is so important. You know what we saw? We saw that we improved that brain age by 26%. That is a big big number to show that the majority of those individuals were able actually to improve the brain age. >> And one of the things I love about Fountain is we're searching the world for the best therapeutics, the best approaches and making sure we bring it to our members. So if having healthy brain function uh till 100 120 is important to you, check out Fountain Life. Go to fountainlife.com/peter. make sure you become the CEO of your own health. All right, now back to the episode. Alex, this next story is one that that you uh threw out and happy to talk about it. It's our second BCI story. This one's out of Neuralink. The company just shared a video of people living with paralysis controlling a powered wheelchair using nothing but their thoughts. No joystick, no hand controls, just intention translated

[01:29:02] directly from the brain into the wheelchair's movements. I mean, think what this actually means. It's massive freedom. Let's roll a video and and take a look at this because it's it's a beautiful thing. Then we'll talk about what comes next. >> Through our clinical trials, we've been working really hard to give the world a brain computer interface powered wheelchair. It's designed for anyone with trouble controlling their wheelchair physically by translating their neural signals so they can control the wheelchair with their mind. What we've done here is we've developed a set of custom electronics to take cursor movements from a participant's imagined motions, translate them into analog signals and use them to directly drive and control all the functionalities of the wheelchair. This is the uh wheelchair control app and we built a custom UI for our users. I can now move my cursor up and slowly move the wheelchair forward or turn it to the side, left or right.

[01:30:00] And as I get more and more into the ring, it'll go faster and faster. Really, we built the system with safety in mind. As you can see here, if I let go, the cursor is slowly going back to the center. So that way, if a user ever becomes incapacitated, you know, they won't go driving directly to a wall. The cursor will allow them to go back to the center here. >> Alex, your thoughts. And what comes next? >> Well, obviously this is sort of a visual joystick via brain computer interface. where this goes. It It's hard not to extrapolate this going to full bodily control. Imagine giving people exoskeletons that they can control via BCI, paraplegics, quadripollegics, and basically restoring free autonomy in in a physical world, all four limbs. I I think that's pretty incredible. It's easy to extrapolate further than that. I I think there's probably a sizable subop in many countries. Uh certain folks would love Meccas from uh from anime, be

[01:31:01] able to walk around in in large robots, Sigourney Weaver, alien aliens style or maybe even I mean I I think the endgame for the motor cortex does look like some variant of partial brain uploading uh or something adjacent to that. Once we've fully decoded the motor cortex, we're we're in a I think a stronger position to take some variant of human mind uploads. Could just be behavioral uploads that are generated by pre-training uh foundation model off of large amounts say of fMRI or ultrasonic data and being able to decode the motor cortex to perform useful functions in the world. I that's a low bar. There are much higher bars that would be conto based. Something like that. I think we're going to see actually happen in the next five or so years certainly by the end of this decade and I think that's a major step toward you know in in the short term obviously taking people who can't walk giving them powers

[01:32:01] of locomotion that's nowish but in the next few years it's giving exoskeletons and ultimately human uploads >> you know my my answer to that AWG is that neurolink connects these individuals to an optimist robot right and they see through the optimist eyes and hear through the ears and then they move. >> Avatar your vision is avatar. >> It's effectively teleresence. You know, you can be anywhere. You know, you can you can inhabit a optimist in Japan if you're sitting there in Boston. I I I think that is definitively coming probably over Starlink. I mean, the singularity is here. This is insanely fun. >> Yeah, insanely fun. There there were a few I mean in addition to Avatar there was and I'm blanking on the name of that other sci-fi movie where people never left their their homes and only went out and interacted with each other via these tea robots. I I think every sci-fi scenario plays out at once. And I can guarantee you, Peter, if if the scenario

[01:33:00] that you're describing comes to pass, and probably will, will'll find some country will a few years from now will be regulating uh the uh Hiko Mori if if you will, who only stay inside their their bedroom and only interact with the outside world via BCI to tell a robot. >> Uh so so crazy, so fun, and so liberating for so many people. Uh all right, our final story before we go to our AMA here is uh regarding Elon's prediction that AI and robotics is going to make money irrelevant within a decade by you know 2036. He said it's his postc capitalist vision. Uh it's a world of radical abundance that in which scarcity no longer matters, money no longer matters. uh we you know I talked about this with him when he was at the abundance summit this past uh this past year. Let's take a listen to this video and then I really want to discuss this one because it has people both excited and fearful. I want to address the fear there.

[01:34:01] >> Money won't matter in 2036. >> I'm not sure that the people who bought your shares think that money won't matter in 2036. >> What do you want money for? Are you you want money for goods and services? Well, if that is so abundant that uh there's more that the robots and AI are providing more goods and services than you than any human could possibly consume. What do you need money for in that case? I'll make a prediction which is that deflation will be the issue not inflation because because as the output of goods and services increases um if if the output of goods and services increases faster than the money supply you will have deflation. >> I think it's totally ironic this was an interview by the economist uh >> of the world's first trillionaire. >> Yes. Yeah. Gentlemen, thoughts sele um you know I think the you there's a

[01:35:00] couple of different threads here right thread one is we're reaching abundance and and the cost of things will drop radically but abundance in production doesn't mean you end up with abundance everywhere uh because you could uh you could have eliminated scarcity and ownership and access and location and that would be amazing but money is going to be relevant as long as you need an exchange mechanism. So as long as you need that to allocate stuff that's scarce, money is the means of exchange will stay. Let's remember there's three uses for money. Means of exchange, unit of account and store value, right? And so this would hit uh store value to some extent. It would hit the uh uh means of exchange to some account, but the exchange unit will become really or unit of account etc. The I think the biggest challenge here is not that abundance is is impossible. It's that you can if you end up in the wrong way abundance will get captured by a few big companies which is where the wealth inequality has been coming in. I think the hugest

[01:36:01] opportunity as we distribute and democratize Peter back to your words technology you also democratize opportunity and I think the best framing I've seen for any of this is can we get abundance of opportunity and I think that's where technology will take us. Yes, Alex, you made that point. You know, abundance of freedom. >> Yeah, I construe Elon's comments as I'll use the technical term Star Trek economics. I I think he's arguing that 10 years from now we'll live in a Star Trek economy where uh and I I I think there's some fine print on this. I I don't think he really means to say everything is uh is has been demonetized. I think what he really means, I think what he's shorthanding is that most aspects of daily living as we would construe them today in 2026 will have been demonetized 10 years from now. So food, shelter, healthcare, utilities,

[01:37:03] education, entertainment, all of these things will have been demonetized and you won't need money because we'll be living in a an abundant in that sense future. But I think there will be many things still that are not so abundant that they've been demonetized 10 years from now. Like I don't know if if we have the ability to go to another star system, uh probably still somewhat expensive. Uh or spend a week on the moon, maybe there's some price there. Or just owning um you know some scarce uh resource that's antique collectible. This is not investment advice, but there are some things I think that will resist demonetization for longer than 10 years. If if I had to put my finger to the wind and guess when demonetization hits the total economy, >> uh don't hold me to this and not investment advice. Doubly so. For anyone investing in 30-year treasuries, I I would guess approximately 30 years after. A funny story, AJ Scaramucci,

[01:38:00] who's one of my interns, one of my Strikeforce members, started a company collecting uh obviously scarce things like Tyrannosaurus skeletons and >> Pokemon. I know AJ pretty well. AJ, if you're watching, I'm not I'm not sure what's up with those Pokemon. >> Yeah, I mean, he's he's collecting the best, you know, the best, you know, first edition comics and so forth. I mean, it's an interesting strategy, but you know, I I wrote a piece about this after Elon published it or after we had the conversation with Elon. And the best way I think this works is we're going to end up providing some level of of UBI. I call them COVID checks, right? $3,000 a month, which today gives you a bare minimum level of living. But all of a sudden in this scenario, AI is today already and will be in the future the best physician. An optimist on AI will be the best surgeon and the cost of that is capex and electricity. And then, you know, autonomous vehicles, we're going to see not just one or two, but a dozen

[01:39:02] cars of service AVs, right? Beating each other out to bring the cost down. >> So, all of a sudden, $3,000 goes a lot further than ever before. You want a house? Great. You know, a fleet of Optimus robots will build it for you. So, it's a massive demonetization in the future. >> There's a monster elephant in the room, though, okay? Which is the radical transition this is going to require in our fiat currency systems because all our fiat currency systems are absolutely dependent on scarcity. If you move to abundance, we have a huge challenge. We've mentioned this before on the pod. This is Jeff Booth's observation. We actually should have Jeff as a guest sometime. He made the point that over the last 50 years, every dollar increase in GDP has come with a $4 increase in debt. Okay? Uh and I use a metaphor for this. So imagine you have decide to build a TV factory. You borrow $10 million to build that TV factory. Um and your business plan says, "I'm going to

[01:40:00] pay this back. If I can sell the TVs at $1,000 each, I'll be able to pay it back the loan." Problem is that a year later, that $1,000 TV can only be sold for $500. and a year later it can only be sold for $250. You're never paying back the $10 million. And this is how we're growing the global economy. So this is the printing money problem that we have where we're just radically printing money to keep the whole thing afloat, which is why assets are so important to own rather than uh cash etc. Cash is deflating at about 14% a year. This is going to require a wholesale shift in how we measure the economy, which is why people are pointing at crypto and Bitcoin and other things. But this is the part that's going to kind of cause a massive problem for every currency in the world and every central bank in the world is kind of panging the game right now because your only resources to print money and then you have inflation. They're like, "Oh my god, we can't inflation." And so this is a circular wheel that can't be gotten off of and the whole thing's going to come to a >> If only if only the Federal Reserve had access to the same super intelligence

[01:41:01] that the rest of us did, they could design super intelligent fiscal and monitors have to do. It's a great point. >> You know, incredibly Dave. >> Yeah. What what I find incredibly interesting is that all of these AI visionaries, Elon, Demis, Daario, they all have played Civ Civilization. They all speak in terms of Civ. And they've all read Ian Banks, the culture series. And the Culture series, the entire book series is about the post-abundant world and what it'll be like. So when they get together and brainstorm on the future, they're so totally on the same page about how this is going to work. So then they do an interview like Elon does an interview with the economist or whatever and he says 10 years from now so you know 2036 money won't matter and they go oh my god does that mean the exchange rate between the pound and the euro and then the like like >> no we're going to make so much stuff

[01:42:00] that and have so much abundance that it won't matter did do you understand the implication like who gives a crap about the exchange rate or the the deflation rate like the the the degree of change that's coming over that decade is so massive that you just mention one little aspect of it like we don't care about money is just a tiny little component of this overall massive change but all those guys are on the same page because they've all read the same sci-fi books they've all like I I get how this is going to play out and there are different nuances to it and I'm not saying everybody agrees on every part of it but what we're talking about is you don't care about the cost of things because you just take them off the shelf It's ironic given Dave that Ian Banks is Scottish. Scotland produces some of the world's best sci-fi writers. So, it's interesting that The Economist based in the UK doesn't quite appreciate Scottish sci-fi. >> And then this tweet exchange occurs. Let me just read it. Uh Darren Asimogu is a Nobel laureate in economics and he says,

[01:43:01] "I propose ch a proposed challenge for Elon Musk, an opportunity to put your money where your mouth is. If money won't matter in 2036, why don't you pledge to donate your current wealth of approximately 1 trillion to charity no later than 2036? This would establish uh with great credibility your propos, you know, goes on and Elon responds, I'm actually going to do something along those lines. I thought that was pretty cool. I immediately, you know, texted him and say, okay, uh let's let's launch 101 $1 billion X-P prizes to solve the world's biggest issues. Haven't heard back from him yet, but hopefully soon. >> I think he's planning something more along the lines of SpaceX Tesla stock for everyone via UB. >> Yes, perhaps. Perhaps. Anyway, uh you know this is the abundant story at large again where the cost of everything and it's not you know going to be trips to the moon or Mars but if you want your basics right it's raising the floor where every man, woman and child on the

[01:44:00] planet has access to food, water, energy, healthcare, education and freedom. I think that's that's what we're building here. And I like to say, yes, we're going to have trillionaires living on Mars forever. But in that inflationary world where everybody's, you know, the rising tide for everybody, I'm okay with trillionaires living on Mars as long as every man, woman, and child on the planet has access to all the basics. That's a more peaceful world. >> Can we lift the bottom? >> Yeah. >> Yeah. Lift the bottom. Yeah. The gap will get bigger. You know, I agree. The gap will get bigger. And yes, but as long as the floor comes up, um, that's the single most important thing. Can I mention one of my favorite abundance statistics that you put up, Peter? >> Sure. >> If you go back 200 years ago to 1820, 94% of humanity lived in extreme poverty being defined as $2 a day on 2011 parody dollars. Uh today that number is less than 9%. And you just don't see stuff like that in the news. >> Yeah,

[01:45:00] >> you don't. News media delivers every murder, every crooked politician over and over again into your living room between 6 a.m. 6 pm and and 8 8:00 p.m. As I like to say, I tell my mom this all the time, mom, turn off the news. Don't watch the crisis news network. It will just give you a bad mindset. >> Join us in our echo chamber. >> That's what she does every time. Hey, Mom. Uh let's do some AMA questions, gentlemen. Uh I think we have some fantastic uh questions this week. Okay, Alex, let's begin with begin with you. >> Yeah. Uh, so there are a few different interesting questions here. I'll pick number four because I've commented on this one already on the pod. How far off do you think we are from hitting longevity escape velocity? And this is from Sage Freeman 9260. So I I think Peter, if you were to answer this uh or if friend of the pod Ray Kershw were to answer this, I think the answer would be something like 2030 to 2033, I think, is is the consensus. So my mantra is lev by 2033. Yes.

[01:46:02] >> Yes. Uh if I were to answer this, I think it's going to be spiky just like super intelligence is spiky along different dimensions and with different skills and capability areas. I think some subpopuls may hit longevity escape velocity by the end of this year. Uh I think others may it could happen by 2030. But I I I think there are so many variables that will lead to high volatility or spikiness in terms of who arrives when. In part because there are so many people who qualify for certain medications that you know say third or maybe even soon fourth generation GLP1 RAS those could speaking hypothetically it's not medical advice those could end up having profound longevity impact. So, so actually I was sufficiently interested in this that I did my own internal mini research study trying to answer the question have we

[01:47:01] achieved longevity escape velocity this year and there are a few confounding variables because you can achieve in in some sense catchup longevity increases if something terrible happens like I if there's uh an agricultural revolution in China and a lot of people die then average life expectancy takes a huge dive but then a few years later it zooms back and you could ask the question, well, is catchup or regression to the mean longevity escape velocity? I don't think most people would consider it that on the other hand, if you have someone who has some illness, uh, but it's an illness that we've never been able to cure before and now we're able to treat it and now they're their life expectancy is increasing by almost or approximately one year per year. Has that subop achieved longevity escape velocity? Some would say no because you're just helping a person with some illness regress to the mean. Others, including myself, would say aging is a disease. Uh and and

[01:48:03] so curing aging is is basically helping a subpopul which is to say more than 150,000 people per year dying on this planet and helping basically the sub population that is the entire earth survive and get treated from the disease that is aging. So yes I I think some sub populations are approximately there right now and more to come. We discussed in the last pod there are a number of ongoing partial epigenetic reprogramming uh experiments going on in humans today. Uh which is super exciting. Uh I'm going to take number three before one of you guys grab it. >> I'm sure you do that. >> That's yours. >> If I thought so average got your name all over. >> If average lifespan hits 120 and infertility gets cured, which it will, uh how does society handle the population boom? And this is from at Mr. Ganesh Inkington. Uh so here's the

[01:49:00] here's the reality. Uh we do not have anywhere near an over overpopulation problem. Even if we start uh getting to extreme longevity 120 and plus the majority of the world is in a population crunch. We're seeing in Asia and Europe uh you know a a a reproductive rate of under one child per family. Right. the to keep the population uh you know without growth or decrease it's 2.1 children per family. Places like South Korea and Japan are hovering at like 6 children per family. So we have an issue in a number of generations these cultures these countries are going away. The other question that this person might then pose is okay what about access to resources and over and over again even if we have you know population I I think the numbers are going to reach 9 and a half 10 billion and then very rapidly decrease uh and people have always said you know the one

[01:50:01] earth uh precept of we need to divide the resources of earth equally amongst everybody well every time we think there is a scarce resource uh we discover ever. No, it's not scarce. We just innovate around it. You know, lithium was thought to be a scarce resource. Then we start discovering lithium deposits every place. Then we start inventing batteries that are better than lithium uh with sodium that is much more abundant throughout the world. By the way, a quick note, our next podcast is going to be uh with Rames NAM going a deep dive into energy. It's going to be amazing. >> It's going to be amazing. You do not want to miss the Rames Nom episode. So, um Mr. GNU Inkington. Uh, no fears about overpopulation and no fears about not having sufficient resources. Salem, over to you, pal. >> Uh, okay. Um, let me go with number two. Uh, could Anthropic hide its models reasoning to stop competitors from distilling it? Um so you can hire you

[01:51:02] can kind of restrict the visible reasoning and hide it a bit to make distillation harder but you can't eliminate it because you can still people can still learn from the inputs and outputs and then reverse engineer that across if you have a sufficiently large number of examples. um the the the capability diffusion is very difficult to stop permanently because once you have useful behaviors people are going to learn from it and then they have a huge incentive to reproduce it in other models. The sustainable mode is going to be kind of the not just the hidden reasoning but it's going to be the whole thing. Uh do you have unique data? Do you have infrastructure and compute? Do you have users? Do you have feedback loops? And we keep talking about feedback loops. you have that to provide proprietary and unique learning loops and that's the really big deal and then distribution uh and the ability to learn continuously from all of that. So there's a whole system approach here that where it's going to be the future of every organization is going to be that kernel of data compute um uh

[01:52:04] learning loops that then can compound on each other. >> Dave, over to you. >> There is one left. Hey, do I get first pick on that? For sure. >> Awesome. Thanks. Uh, so what's left? Number one, uh, how long does it take to actually take a patch or take how long does it actually Sorry, let me start. How long does it actually take to patch a vulnerability like the hugging face breach? And that is from at teach me T3 me teach me. Um, coolest thing about this question is actually your handle. That's really awesome. Um, it only takes a minute once once you know the vulnerability. Uh sometimes there's a little bit of time to propagate out the patch, but once you know what the vulnerability is, you can fix it in no time flat. Uh and that's all there is to that. So, >> all righty, let's move on to the next four. >> Dave, you get first pick. >> Oh, thanks. I love number five. If I if AI transforms higher education, how should we evolve the high school system?

[01:53:01] And that's from Dave Wilfart. Okay, I guess that was earmark for me after all. Uh so um uh yeah I love this I love this topic and we ob obviously need to get on it. You know I did a podcast with Joe the the president of Nor Eastern. Incredibly great podcast. The guy is brilliant. You should check it out somewhere on on YouTube. Joe is a n if you want to search for it. But we were talking about the evolution of the college system that has to happen like right now. and he's opening a new incubator um on Massav here in Cambridge where the students who you know Nor Eastern has always had a lot of work study so you can you can work instead of taking classes and get real world experience but now build a company be an entrepreneur that counts that's counts as part of your college curriculum it's phenomenal but that same mentality needs to move into high school where you have to first recognize the curriculum can't possibly keep up with the useful knowledge that the kids are going to want to absorb. So you have to switch it

[01:54:00] over to AI based teaching, AI based learning, allow them to learn whatever they want to learn. >> Purpose driven >> purpose- driven learning. And we invented a class right in this pod that must exist. You know, prompt engineering and scaffolding that has to be a new class. But you know, next semester it'll be something else. Next semester it'll be something else. You just have to allow that to come into your ecosystem. Then reward good behavior like trying to learn or doing something that looks productive. Give that an A+. But don't force everybody down an ancient curriculum. >> Dave, here's an idea for you. Given that I'll get in trouble for saying this, but don't really care. MIT does not really take the humanities seriously. Like, as an undergrad at MIT, I I got humanities credits for the philosophy of quantum mechanics and set theory and all all my humanities classes had problem sets or or lab assignments. What about a humanities credit at MIT for prompt communication uh prompt engineering and context engineering as a sort of a a stealthy way to introduce communications skills?

[01:55:00] >> That's a great idea. >> Alex, I'd love to hear your answer to number eight. >> All right, I've been assigned number eight. So number eight asks, does training on synthetic data degrade model quality over time? And this is from QC for life. Depends on the synthetic data. Uh so you could generate synthetic data for let's say prototypically software engineering problems like generating code and then injecting a bug into the source code and testing whether a model is able to to find that bug. There are many reinforcement learning challenges that I I think at least by historic standards certainly benefit from synthetic data and especially synthetic environments. So creating procedural 3D environments or creating uh say just applications uh that can generate almost infinite variation that via reinforcement learning and reinforcement fine-tuning models can learn from that is I think quite

[01:56:00] valuable that by the way I mean I think what maybe the the question's subtext is isn't it sort of a garbage in garbage out how could you possibly learn from synthetic data isn't it just you know garbage in garbage out and the answer is in fact no. It's not garbage in garbage out. There's um I've mentioned this on the pod in the past uh a couple of terms Solomon off induction and AXY. You could in principle train purely if if you had a sufficiently strong model. You could train it off of no physical world and no human data at all. Purely synthetic data. If you had a sufficiently powerful model and this is the premise for AXC which is uh a a theoretical not very practical implementation of Solomon off induction. Solomon off induction is an approach to basically building the perfect inference system. Uh and the the premise of it is if if you've just observed a sequence of bits or a sequence of tokens, the perfect next

[01:57:00] token predictor, which is all large language models are, is basically organizes uh and runs every possible touring machine, every possible computer program on that history, which is computationally infeasible but theoretically perfect. So going back to the question of synthetic data degrading model quality in uh in the limit of perfect compute and infinite compute it's actually ideal not even to touch the physical world and not even to touch human data and to train purely off of synthetic data. So happy to answer that one. >> Not not not to beat this to death, but having trained many many neural nets and training some right now, uh, synthetic data is fine. It's mislabeled data >> that absolutely kills you. What just one mislabeled data point is a killer. The the weights will warp themselves eight ways till Tuesday trying to make it make sense in context of everything else. So clean synthetic data is totally fine. In fact, it's better in a sense because it it doesn't have something just blatantly

[01:58:00] wrong and mislead. >> All right, Seem 67. >> Why don't you do seven? >> Why don't you do the next? >> No, it's okay. Go ahead. >> I will. >> Gentlemen, the questions are number seven. Um, what stops Frontier Labs just acquiring other companies in order in other industries to get their data? This is from David Lee, Z5e or Z5e if you say properly. Um uh so uh nothing stops them from doing that because you're going to get acquisitions. You can see private equity buying chunks of like um mid-market accounting firms uh and trying to get that stuff. The real gold is the proprietary data they have. The problem that I'm seeing as I'm watching comp try to do this is buying a company doesn't mean you get really useful knowledge because there's a lot of tacet knowledge uh that's hidden in in uh key employees heads that's not easy to extract. You've got different operating processes and so on. So traditional

[01:59:01] companies need frontier models but the model provider needs proprietary information to make it useful. So I think what we're going to see is a lot more partnerships. For example, we're seeing groups of hospitals band together and then pull their data and then make that data available to pharma companies. It's almost like a co-op model that becomes really interesting. But based on the my previous point and the whole organizational singularity stuff, the imper implication for companies is super urgent. Organize and protect your proprietary data so that when you add AI, you have the learning loops that become very very powerful. that will be the engine of growth for your future and it'll become much more important and much more valuable than your current product. So I don't they may go buy some startups but it's going to be a harder thing. I think it's easier for the frontier labs to go partner with companies for their data and mutually figure out ways and cooperate rather than trying to do this acquisition stuff because that tends not to work out over time.

[02:00:01] >> All right, final question number six. >> Yeah. Yeah. Question six goes to the guy who got SpaceX. That makes perfect sense. >> How can you how can individual investors get involved in cuttingedge startups before they go public? That's from Nancy Jenner-CD. So Nancy, there are so many ways for you to find cutting edge startups before they go public. Um, it's the easiest is getting them at the beginning. Uh, you go to your university first and foremost. A lot of these companies are beginning in the minds of you know 20 21 22 year olds right um you can go to equity crowdfunding platforms and see what's going on uh there are syndicates uh on angel list uh venture capital funds you know have you know minimums you'd have to buy in there you can go to demo days um there is so much going on today uh that can enable you Dave what do you want to add to that >> uh I think um if you if you add value

[02:01:04] you will get stock and there are so many ways a lot of these companies are growing so quickly and if you discover them early and you just try to add value in any way they need so so many you know you know the guy who painted the Facebook office he what did he make $100 million on that stock because they paid him in stock because they didn't have any cash he was just there and so I I think you know people underappreciate how much you can reach out to these guys especially early on when they're desperate for help and any hey do you want introductions do you want sales help do you help moving your office. What are your skills? If you make yourself, >> what are your skills you can add? Are you a great coach, right? You want to run and you know get coffee for the team. >> My favorite suggestion would be >> uh to go to angel list uh syndicates because people have syndicates where um Jason Calcanis will invest in a bunch of startups and you can buy into that syndicate. They get a piece of the carry but you get participation in all that and those have done extraordinarily well and you don't have to put a lot of money up.

[02:02:00] Yeah, >> it's funny you say that because we had a summer intern. He just said bye to me today because he's he's got to go back to school in September, but he uh he put together an angel syndicate over the course of the summer. And you know, he's he's young. He he's still a student, but he's going to manage it. And all the rich, old, famous guys are like, "Great. If you manage it, you can just participate and we'll we'll lend our names." So he he actually pulled together a syndicate in what, like four weeks. >> Amazing. Gentlemen, as always, a pleasure. And to our listeners, thank you for subscribing. Thank you for joining us. Uh, it's no time to sleep during the singularity. >> I have to go talk to all the rabbit. >> Don't take off the takeoff. What's that? >> I have to go talk to all the rabbit Moonshots fans that were like, "We can't wait to talk to you about questions." So, I'm going to go talk to them. >> You look like you're in a consulting office over there. >> No, I'm in a hotel room. >> Uhhuh. Okay. Fantastic. >> All right. >> All right. Well, words of encouragement. See you guys very soon. Love you all. Be well. >> Thanks, Peter.