The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:09:28 · Arthur Mensch
[00:09:28] S0: Because customers want choice. And when you have infrastructure, you want to provide as much choice as possible to saturate the infrastructure. That is the reason why that brought us to actually serve more and more of open models. Because in different domains, you may want to pick a different model. You may want to pick smaller ones. You may want to pick bigger ones. So the more choice you have, the better usage you can make of the infrastructure, the lower your cost can be. And it's in a way, it's a commodity market, so you want the cost to be as low as possible. So that's the reason why we sell those models. But what you say is true. Models are compression of knowledge. If you don't control the data supply chain, if you don't know what goes into the models, you cannot guarantee anything on the output. And so when we serve our models, we can give further guarantees to our customers than when we serve third party models precisely because theoretically, you can make sure that in a certain environment, with a certain context, the model behaves in a certain way. There's no way of excluding that. There's no way of measuring that. We can monitor that online, that's what we do, but you can't exclude that it's being used as a vector of attack. I think it is very theoretical because I don't think it's the case today. But on the other hand, this is part of the threat model. And so our customers, they are asking us to be able to provide them with all of the open weight models that are available. We're helping them do it in a secured way where we can help them monitor what's going on. But in many cases, they are actually very keen to use our models because we're able to tell them that the data supply chain, everything we've trained them on, is something that we have validated before.
00:10:57 · Harry Stebbings, Arthur Mensch
[00:10:57] S1: What percent of token traffic is your own models versus other open source? [00:11:02] S0: I would say around 80% comes from our own models. [00:11:05] S1: Wow. That... That's a lot more than I thought. Okay. On the 20%, everyone tells me that, oh my god. American CIOs and CIOs would never use Chinese open source models, and, actually, that fear really is there. You have them as customers. You have amazing customers. Are they fearful of using Chinese open source models?
00:11:23 · Arthur Mensch
[00:11:23] S0: It depends how critical their industry is in general to governments. If you work with defense, for instance, we work with defense customers in Europe, they would never use Chinese technology. If you work on the finance sector, again, because it's critical infrastructure, they are very reluctant to do it. If you work in retail, if you work in certain domains of manufacturing, again, it depends where the reluctance is different. Again, think there is a common understanding that open weight models, if they are being deployed on sovereign infrastructure like ours, the only valid threat is that they go rogue and have weird behaviors in certain domains because you may have a supply chain attack on it. There is a common understanding that this is very theoretical and it's certainly not the case today. But indeed, it's part of the conversation. I'd say what is also part of the conversation is not this, is it a threat to deploy third party models that I don't fully understand. What is part of the conversation is, am I going to be able to get updates in six months from now? Because what's going on is models have gotten so strong that they're able to do cyber attacks, that they're... You can use that for pretty much advanced purposes, let's say. And so the consequence is that they are more and more being treated as defense systems. It's being treated de facto by The US as a defense system because at some point in May, they started to ban them from outside of The US. And if you look at what China is doing today, they're also looking at ways of restricting exports beyond a certain threshold. The reason for that is that effectively, this is a dual use technology. And so as any dual use technology, security of supply matters even more. And so the companies we work with realize that they need security of supply not only on the infrastructure side, but also on the model IP side.
00:13:03 · Harry Stebbings
[00:13:03] S1: With that in mind, do you think your OpenAI's and your Anthropics withholding their best models is good or bad for society? And is that just an inherent feature that will be prevalent within this industry?
00:13:14 · Arthur Mensch
[00:13:14] S0: Is it good or bad for society? I don't know. What is clear is that there is immense leverage to centralised AI providers in a world where there's no providers that is allowing decentralized deployment, that is allowing sovereign deployment. So what we are doing is extremely important for companies. If we end up in a world where all companies need to rely on two or three providers that are centralized AI providers, that give them enormous leverage. They will use the data that is being produced by the systems to make better systems and to go after the business of their customers because at the end, this is the end game. This is pretty clearly what is being priced in today. So the approach we are taking is to make sure that this world in which you have an oligopoly of AI providers that are leveraging all data being produced by enterprises to make better systems that can be intermediate with enterprises is not the world we live in. And we're very aligned in that with all of our customers that, of course, don't want to live in such a world. So I would say the fact that there are internal models that are being used to do certain research, for instance, is an early sign of what can happen in a world where you have massive concentration of power in artificial intelligence. Luckily, it's not that complex to build models. It's about deploying capital. It's about having the right team that is training the right thing. And so we've been able to do it. The open weight frontier is catching up with the closed frontier. In many domains, it's actually above. And so that means that I don't think we'll end up in a world where if you wanna do mathematics, you need to work at OpenAI. Luckily, the... There is enough people in the world that don't want this to occur.
00:14:41 · Harry Stebbings
[00:14:41] S1: You said the word energy a couple of times, and one of the core underlying tenants of being successful is having the energy and the infrastructure to power European AI. We have a very different energy system to The US, and we have a very different energy system to China. In China, they'll move 3,000,000 people to put some form of energy infrastructure. And in The UK, we won't move a a birdhouse. It's quite concerning despite the joke. How do you think about ruminate on the energy supply challenge?