00:00:00 · Aaron Levie, Guillaume Moubeche
[00:00:00] S0: AI is too important for the rest of the world to say, we're only going to use the API calls from three companies in The US. There's a bunch of people secretly cheering that this is exactly what you'd wanna have happen to design the regulatory review process for AI model releases. Intelligence is going to be multifaceted. It's not gonna be one or two models doing everything. [00:00:21] S1: Today on BILLIONS, I'm sitting down with Aaron Levie. He is the leader who rapidly transformed Box from a pure SaaS business into a cutting edge platform for AI agents. We dive into the high stakes battle for sovereign AI, government regulations, and why the narrative that SaaS is dead might be completely wrong. Aaron, super excited to have you on. [00:00:42] S0: Super excited [00:00:44] S1: to to have you on. Like, I know you are, like... You have very interesting take about AI. I'm curious to, like, get your your last take, you know, on what happened with with Anthropic recently, because I think you said it was like a a big win for for open and lightweight models. So can you maybe elaborate and your thoughts on the on the topic?
00:01:10 · Aaron Levie
[00:01:10] S0: Yeah. So so so I think what... First of the fabled model is is, you know, kind of an unprecedented level of of intelligence and and capability. So so so the... Clearly, Anthropic, you know, designed an incredible... And and trained an incredible model. But the US government effectively, you know, enacting an export control, what meant... Which meant that non US, you know, citizens aren't able to use the model is really kind of a completely new precedent and moment in AI regulation where we've never seen that before for any kind of frontier model being held back legally from being available in the market. And the implications are, first of all, it's it's almost entirely impractical for any AI any a a... AI lab to be fully responsible for, you know, the the nationality of the of the customers that are using it. At a minimum, it would completely obliterate the API business of Anthropic because, you know, the idea that you would be able to control the end customer, you know, through your partner ecosystem is very, very difficult. So so it it effectively has the impact of of not... Of making the model unavailable to to the world. And so the risk is if you were either an... A major app developer and you wanna be able to make this technology available to your customers or you're a, you know, you're a country anywhere around the world that wants to, you know, continue to to ensure that your that your ecosystem is able to to build on top of leading, you know, frontier AI, this poses an all new risk, which is at any moment, you know, can that AI model get pulled back from one government or due to one government? And we just never had that precedent before. You know, AI has been this sort of very fast moving, very market based ecosystem over the past couple of years. And so, you know, I think, first of all, the US government probably very quickly needs to to improve the situation with Anthropic. I think Anthropic is quite motivated to, you know, resolve whatever the the particular issues are. But even even when that happens, it's easy to kinda think in a year from now or three years from now or five years from now, how many more versions of this might we see in in in in in this landscape that that will play out?
00:03:24 · Aaron Levie
And so it sort of makes you wonder, well, if you're, you know, a country, Germany, France, Japan, you know, UK, and you have the capability to to, you know, be at at, you know, frontier or near frontier AI from a a talent and an infrastructure standpoint, do you need to be, you know, you know, building these these kinds of models yourself and make sure that you have them available to, you know, businesses and and users within your country? I think it it really kind of introduces that question in a much bigger way. And we've already seen obviously examples of this China obviously developing, you know, kind of great open source models, Mistral, you know, doing the same. But I think this highlights the increased importance in that dynamic and the idea that you can have sovereign AI or AI that you control. Now there's one... There's sort of one caveat to all of this, though, which is which is, you know, you're not going to you're not going to take that big of a of a sacrifice or a discount on your... On the model's intelligence for that benefit. So if Frontier from US in a in a kind of a closed model environment stays 10, 20, 30, 50% better than than the next best model that you could, you know, make sovereign, I think, you know, people will take that risk, and they will use the frontier model at at all times. So this only works if open weights models or, you know, sovereign AI can remain close to the frontier and much closer than it has historically. And I think we're seeing some examples with with Kimi and DeepSeek and and and and, you a few of these new models coming out of China and Nemotron. It's it's... You know, these models are doing a great job kinda staying at the forefront, but they're still not fable level. And that's gonna be the big question for the ecosystem over the over the coming kind of months and years.
00:05:16 · Guillaume Moubeche
[00:05:16] S1: Do you feel like it's only gonna be a matter of performance, like staying, let's say, as you said, 20, 30%, like, behind or also a matter of timing? Because what we're seeing right now is, like, when the first model went out, you know, like, the the first lab to catch up maybe took like twelve months or or like, yeah, a bit more than a year, but now I I feel like models are catching up like within a couple of months. So do you think it's only a matter of difference or also a matter of how fast can other models catch up on the best models? Well, I
00:05:51 · Aaron Levie
[00:05:51] S0: think, you know, there's there's a big debate, you know, and and if you watch, you know, Dwarkesh talk to Dario or Jensen, you know, you you sort of see examples in contours of this debate, which is is the frontier and the open... And the and the sort of, let's say, the best in class open weights model, how close are these tracking versus are we seeing a divergence? Are they six months behind? Are they three months behind? Are they one month behind? Or how much is it really just a factor of how much compute you have for inference and and kind of test time compute as an example? Because there's different ways to to kind of really drive the the workloads in these models to get better results. I am generally actually optimistic that that that that the frontier open weights models will be able to to stay relatively caught up. I think it's it's of such economic and and strategic importance for, you know, countries like China, you know you know, maybe individual companies like like Mistral or even NVIDIA to make sure that that that that is sort of maintained. And we have not yet seen a breakthrough that is so either proprietary or kind of undiscovered by the rest of the ecosystem that that keeps us completely closed off. You know, I think there's obviously a conversation around, you know, RSI and and and what, you know, what what does self improvement look like, and does that kinda lead to a kind of an accelerating takeoff? Like, whoever whoever is able to design these systems that that self improve first, then obviously there's a compounding dynamic to that. At the same time, it's hard to imagine China not wanting to to stay in the race in a very big way. Like, it... It's unlikely that China says, you know what? We're totally fine with Anthropic at OpenAI being the only vendors of AI in the world, and, you know, we'll be closed off from this ecosystem. So at some point, you know, you can just throw enough money at this problem. You know, you can... China could just say we're gonna spend $50,000,000,000 and just and just make sure that this is this is of such critical national security importance that we have to make sure that we're throwing compute at this problem. We're gonna kind of, you know, sequester the the top, you know, researchers and scientists and and and and make it happen.
00:08:11 · Aaron Levie, Guillaume Moubeche
I I think it's unlikely that that wouldn't work, and I haven't seen any evidence that suggests otherwise. [00:08:19] S1: So your view, like, when it comes to China is is what you're regarding, like, the the chips because for so long, like, you know, there's been kind of an embargo on chips and it was not possible for them to get them and they were getting it through like Singapore or like all these kind of things. Like, what... What's kind of your view? Because it's like... It it feels like eventually, like... I mean, in The US, it has always been a very pro open market, and now it feels like things are moving away from it. So I'm curious to get your take like...