AI Tsar: AI "Safety" means “Owning the means of Production”

Tech Billionaires: Don't give AI Providers your proprietary data because they may use that code to dominate you (monopolize the most lucrative verticals)

When I saw David Sachs on the “All-In-Podcast”, I thought it was interesting that he was warning corporations that they need to build their businesses on open source, lest the proprietary AI companies suck up their data and use it to compete against them.

They talked about this as “AI Safety”, “Owning the Means of Production,” and avoiding being “Dominated.” This sounds a lot like the perspective other countries have when dealing with US/Western companies, so it was interesting to see US companies advocate a similar path.

According to the podcast, Anthropic is no longer trusted by its customers to host their businesses without turning on them, leaving Apple the only company seen as respecting their relationship with developers.

TRANSCRIPT:

But let’s go back to the supposed crash out by Karp on CNBC. It was nothing of the sort. It was all these legacy media types making that claim. And that’s the first clue that he’s actually saying something insightful and maybe kind of brilliant. And I think the thing that he said that I hadn’t really thought about in quite those terms is he started talking about AI safety in the enterprise and what that really looks like. And what he said is that what technical customers want is control over their compute, their models, their data stack and their alpha, meaning their proprietary knowledge. They want to know they own the means of production, he said, and it’s not being transferred to someone else. And what he’s referring to there is that these enterprises are at risk of transferring their knowledge, their knowhow, their trade secrets, their customer data to these model providers who might eventually decide to compete with them. Like you said, JCAL and you can see that enterprises are waking up to this threat and they’re not happy about it. And I think KARP is exactly right about that. Now, I think this is a really interesting take on AI safety because what safety means for an enterprise is again that they get to control their own data, their model weights, their compute. So, a frontier lab can’t hoover up their proprietary knowledge, their alpha and turn it into their next product. And if you don’t think that can happen, just look at what happened to Figma. So according to the information, Anthropic quote unquote blindsided its then business partner with the launch of Clawude Design. So this was a new vertical app that Anthropic launched to compete in the design category. And Figma’s founder said that Anthropic had not been completely honest with them. Enthropic chief product officer had actually even served on Figma’s board and didn’t resign until 3 days before the launch of Claude Design. So obviously Figma again felt blindsided by this and you can see the resulting impact on their stock price. Figma’s stock has fallen something like 50% this year while Anthropic’s valuation has surged. This is not an isolated example. Anthropic has also launched Cloud Science, Claude Security, Claude Legal, Claude Financial, and of course Claude Code. And every single one of these vertical apps expanded into categories that was previously served by companies building on top of Anthropic’s own models. And really, if you want to go back to when Anthropic’s revenue explosion began, it was with the launch of Claude Code. And how did they know to launch that product? Because they saw that cursor was doing extremely well. Curser was one of their biggest customers. They created the coding assistant first. they created that category and anthropic said oh like why don’t we vertically integrate so in other words they’re watching where the value is being created on top of their models then they’re moving in directly and this is a formula that I think is very Microsoft like you could say it’s very Google like they want to dominate the model layer you could call that the operating system and then use that position that monopolistic position to capture the most lucrative verticals so if you want to think about like the Microsoft example they had the Windows monopoly and then systematically they went and dominated every lucrative category of business software. It started with spreadsheets and word processing and then eventually it went to the browser so forth and so on. If you want to look at Google, they basically had a monopoly or dominant position in search. And if you go back to the early days of Google, the search results picked you off site. And in fact, they really pride themselves on how quickly they could send you off site. But gradually over time, they use that traffic to tell themselves where to build properties. And today, fewer than half of searches kick you off site. You stay on Google properties. And I think something similar is happening with Anthropic here. the pattern is clear, they are going to use their dominant position in the model to then grab more and more territory in any interesting and lucrative vertical. So again, back to Alex Karp’s point, if you’re an enterprise customer or a developer, why in the world would you ever want to share any proprietary data with them? You are mortgaging your future. You are sealing your fate. You are going to lead to disaster for your company. Just one last point then I’ll turn over JCL is that Daario at the same time that they pursue this business strategy has been arguing that open- source models are dangerous and need to be restricted. Well, dangerous to whom? Not to enterprises that want to retain control over their data. It’s dangerous to his business model because his business model requires that customers don’t have a lot of choice at the model layer. And what Karp is pointing out here is that if you want to have true AI safety as an enterprise, you have to retain the ability to choose at the model layer who gets to see and use your alpha. Yeah, this is well said. I think you you picked that carcass to the bone a bit, but Chimath, you’re actually doing specific examples of this uh at 8090. You’ve been testing uh some of the open source models. I saw you share that on Twitter X. So maybe you could give us a little feedback on what you’ve learned as uh the CEO of 8090 and you know your firsthand experience now with using open source for the first time in the last couple weeks for this specific use case in enterprises. When you start a company I mean you guys all know this you’re not starting it for the moment that exists today. you’re almost sort of trying to forecast if such and such a set of things happen then here is the scene that that gets created because it takes time to build something and it takes time to get enough reps to know what you’re doing in your go to market. This for me was the moment that I thought would arrive which is the point where everybody wakes up and realizes wait hold on a second two things are true. The first is that my business is complicated. I want AI to be able to accelerate it, but I want to be able to protect myself in doing so. And then the second is I want the flexibility where there’s an independent third party control plane that I use to get all these benefits so that I don’t leak and seed my advantages away. And I think Alex is an incredible, smart, brilliant guy and he completely nailed it. And I think he called out on its face the huge risk of this. So let me just give you this narrative in three tweets. The first one is I read this really interesting study from BCG and what they looked at was the return on capital employed or ROCE of various businesses. And this is what’s incredible. The cost of capital has now with long-term rates moved back to what its long run average is which is around 8 to 11%. What that means is like that is the actual cost that you would borrow money at effectively. The problem is that half of large US companies now cannot deliver returns that exceed that. That is a really big problem. And then second there’s a further problem which is that persistently low returns. So in the you know 1 2 3 4 5% is about one in seven companies all around the world. Okay. So why is this important to note? It means that being in business is complicated. It’s hard. Not everything works all the time. There’s a bunch of underperforming businesses. There’s a bunch of underperforming segments. So in that lens, when you, you know, think about what Sax said, which is you have this company that comes to you and says, I have a magic box and all you have to do is tell me everything you’re doing, and this magic box will make everything better. But then all of a sudden, from the shadows, the magic box says, you know what, I’ve decided to compete with you. That is a huge risk.

QUESTIONS:

1. Why is it so important to own the “means of production”?

2. What is open source and why does the AI Tsar advocate for “open source” AI?

3. What are the risks of sharing your proprietary information with AI companies like Anthropic or Open AI?