The MAD Podcast: How AI Gets Built — with Matt Turck
00:36:14 · Matt Turck, Nathan Benaich
[00:36:14] S1: It's an interesting fruit and slip or whatever, right? Because the irony of all of this is that DeepMind is a UK company. [00:36:20] S0: Yeah, you're right. Yeah. And I think part of the problem with actually like The UK AI ecosystem and its success in actually leading the world is that for too long the UK government kept saying that DeepMind is a British company. And I think it's only started to unwind that like very, very recently. [00:36:37] S1: Why is that a problem? [00:36:38] S0: Well it's a problem because then it believes that it's already number one. The UK is the best place to do AI and we are the best at AI because we have DeepMind. And so therefore we don't... [00:36:47] S1: The attitude behind the claim, which is a problem. [00:36:49] S0: Yeah. Because then in like, you know, in policy rooms then, you know, individuals for advocating for more investment in AI or we need more, you know, we need to procure more systems from AI companies or we need to make our country more appealing for AI companies to start, get answered with like, but we have DeepMind. [00:37:06] S1: What about defense AI? You're an investor in defense companies. I mean, that feels like an area where, the need for sovereign AI since obviously warfare of the future is going to be very driven by AI. That feels like a place where...
00:37:24 · Nathan Benaich
[00:37:24] S0: Yeah. I think it's Yes. Pretty Yeah. Yeah. So, yeah. So that push really started. I mean, like post like the Ukraine war, like almost five years ago at this point, but more importantly, think it was like two years ago when JD Vance went to the Munich Security Conference and effectively said like, you need to invest in your own defense and get serious about this, you being, you know, NATO and Europe. And so ever since then, there's been, you know, a variety of different initiatives to give more capital to the new defense companies, to encourage governments to be providing loans to businesses to improve their supply chain. And that's, you know, created a set of like neo primes, like, defense companies that are trying to compete with prime contractors. So companies like Stark or Helsing being... Quantum Systems being like the the main ones in Europe. And then, you know, as as like warfare has changed, like it's gone from... I don't know, you know, developing strike systems over the... Over sort of mid range to, you know, hit tank, you know, battalions to now being like, well, getting pummeled like every day with hundreds and hundreds of FPV drones or various other kinds of aerial systems that are autonomous and, you know, now can no longer be stopped with jamming because they use computer vision or they're guided by these like fiber optic cables, which by the way have gotten much more expensive because of data centers. And so we need more, you know, novel like air defense systems. And so that's where companies like Alta Ares in France and others have really been pushing. And and as you said, like the supply chain is super important because, for example, like, you know, NATO wouldn't procure systems in in Europe that don't have at least 70% of the parts from from, you know, non China basically. And countries are really queasy about taking US protection or US guarantees at face value because they're shifting on a weekly basis. So, yeah, I think that's an example of a market which is sort of has to be domestic by by design and can breed new companies that are much more competitive than their US peers.
00:39:41 · Matt Turck, Nathan Benaich
[00:39:41] S1: So then if Frontier AI cannot be built, outside of The US, then, let's let's go back to The US, a part of your report on on research effectively calls, Anthropic OpenAI and Google as as as winners, as like the definite winners, which obviously, you know, has been, years in the making, but, there was a moment where it felt like there was a plurality of labs. Effectively, what you're saying is that no, like those three are the winners. And does that include, I guess nobody knows what they actually do, like SSI and thinking machines and like there seems to be like hundreds of neo labs. [00:40:17] S0: Yeah. Yeah. Maybe meta on the margin. Yes. Super intelligence lab. Yeah. Especially as now they're pushing towards like serving their models through API, but also having an enterprise business. So that one, you know, that might change over the next like six to twelve months depending on how their go to market works. But yeah, would say it's probably those three plus meta. [00:40:33] S1: So your view is that the the advantage is gonna keep compounding and that's gonna be the state of the market
00:40:33 · Matt Turck, Nathan Benaich
[00:40:33] S1: So your view is that the the advantage is gonna keep compounding and that's gonna be the state of the market [00:40:39] S0: versus I think so for like the general purpose frontier. Now there's there's like examples of perhaps like a really focused bet on a on a particular capability, which has like... Where you can make certain trade offs to the model in order to get much better performance at a task. Like I'm referring to, for example, these classification models effectively, like JEV, which can grow really, really quickly and become popular. Again, TBD, how long it lasts. But I think it's I think it's an encouraging sign for entrepreneurs that shows that, you know, you can take a focused resource bet and it can pay off. But over time, it's again like TBD if there are like these kind of gaps and capabilities that are sufficiently exploitable. [00:41:17] S1: So what do you think happens to the dozens of neo labs? I mean, not to keep talking about Europe, like just in London, there's three of them. Right? There's, the David Silver thing and, like, another two the... You know, in The US every few weeks. There's one, you know, Jeff Dean's new lab and so on and so forth. So what happens to those?
00:41:36 · Nathan Benaich
[00:41:36] S0: Well, I think it depends on the... Their kind of focus and modality. Like for example, on robotics and embodied AI, I think you can... I can see how an independent lab would still have a chance of competing and winning like because of the immense focus on, you know, enterprise AI, basically, that OpenAI and Anthropic has. Like, I have a slide in the report where I basically just, like, show all the different product lines that OpenAI and Anthropic had, or admittedly, OpenAI had lots and how they progressively just cut all of them. And there was a quote like, you know, this this moment is like too important to be distracted by side quests or some version of that, I'm paraphrasing, which meant that they broadly don't do dedicated robotics. Although maybe there's some of that kind of data in the in the Astra training recipe. Science is a little bit unclear. Anthropic is clearly leaning a lot into biology and drug discovery. OpenAI, maybe more on the model side, less on like we wanna own more of the stack. There's like kind of related to embodied AI, this whole like category of world models, whether that's, you know, a video model with some action in it or like some other definition of world model. But but in general, like Anthropic doesn't really do any of that or at least like from what we can see publicly. I mean, they don't even have an image generation model, for example. I think audio, pretty clearly, labs do have some of those capabilities, but, you know, if 11 labs can, like, keep accelerating the way it does, then clearly there's there's a need for a dedicated capability. I think those are probably the areas where I can see an independent lab, like, working out, but but ones that broadly say we're gonna do frontier intelligence for knowledge work, but just, make it better, faster, cheaper. I think that's tough. I think for me, like, I'll I'll believe it when I see it. But yeah, this idea of like you open your computer or the app looks exactly the same, but it's just better. I don't know if that Yep.
00:43:26 · Matt Turck
[00:43:26] S1: And in world model labs, are you seeing anything exciting? I mean, obviously, he's a Lee's lab was acquired for a lot of money and that's unclear what happens from there, given that the buyer is AMD. Because Yann LeCun started his company AMI in Paris since the