Prof G Markets
00:48:46 · Misha Laskin
[00:48:46] S4: I think that the lack of open source period, wherever it comes from, will actually be more devastating for... Like, that will be the thing that's devastating for our economy. Because all of a sudden, our startups can't build their own intelligence and can't compete with large incumbents. Our researchers get locked out, and can't really understand how these systems are built unless you're in one of the big labs. The whole, I think, notion of America's success as a country is in its ability to foster very diverse competition and innovation across this country, and openness enables you to do that. So I actually think that these... What actually happened, right, is that when DeepSeek v3 came out, there was a market scare, and some stocks went down. But the reality is that even... It was an irrational reaction. Those stocks rebounded and started doing very well because of demand for various things like compute went up. Because now that you have an open model out there, do you have more buyers for compute? Have now anyone who... Again, it's an ownership market, and ownership means that I get the model, and I put it on my own compute. So by nature of having a good open model, there's just gonna be more diverse demand for compute. Startups and the various ones that are doing more scientific pursuits will just be able to explore a much wider set of ideas than any one company could. This is just kind of the way the innovation economy works, and it's extremely important that we preserve that. Now, right? So it's kind of, I think that there's a simple answer that I think would be sort of nice for us to believe that China is bad, therefore open models from China is bad, but it's actually more complicated. It's actually no, open models from China, very good, but we also need to have our own... It's really good for ecosystem, but we also need to have our own great open models. These are the two superpowers of the world, and America is the predominant superpower. And so, it's kind of like you're building a foundational technology, it's like if electricity existed in one place, but not in another, right? You have to be competitive. You have to ensure that the world builds on top of your stuff for your national security.
00:51:11 · Misha Laskin, Ed Elson
And while they kind of seem at odds, both things can be true, that it's great that Chinese open models are out there, but it's also something that is a matter of national security for this country. [00:51:24] S2: Do you think Anthropic and OpenAI will, at any point, switch to being open? Do you think that... I mean, I just... If this is the direction we're headed in where, you know, if we're basically giving the engines out for free and the idea being that if you give the engines out for free, then that's gonna spur a lot more activity and a lot more growth and a lot more innovation, which will result in a more prosperous and more productive ecosystem where the returns will eventually be seen in the future. If that's the direction we're headed, and it seems like maybe we are, especially if China's just deciding to do that, why would you not use cheaper open weight models? I mean, does that not mean that Anthropic and OpenAI are gonna have to get with the program? Like, what are they gonna do?
00:52:15 · Misha Laskin
[00:52:15] S4: I think they're gonna do just fine. These are incredible companies that have scaled at an unprecedented rate and keep discovering new breakthroughs in AI. So, I think that you can be in a world where... I mean, it's positive sum world where it's a this and that. There'll be open model companies, and kind of builders on top of open models, and distributors that are successful, right? And there will be closed model companies that are successful, and you have a rental and ownership market. And just because ownership is starting to grow in its demand, doesn't mean that everyone will then own a house. There'll be still people who are renting, still people who are owning. Think that... Mean, OpenAI has open sourced models in the past. I think that when something is not the core strategy of the company, you tend to not pay as much attention to it, and you tend to open source maybe like a lesser version of the thing that you're actually kind of monetizing. And that's kind of what we've seen from open source launches, Google has done a lot for the open source community with the Gemma launches, but it's a very different model class than the Gemini models, similar when OpenAI launched GPTOSS. So, right, it's very different from the class of actual internal models they're sitting on. So I don't see that strategy necessarily changing for them, because I think that they have so much opportunity ahead of them just chipping away at their current business that I don't think they might, but I think they're also gonna do just fine.
00:53:54 · Ed Elson, Misha Laskin
[00:53:54] S2: Reflection has been in the news recently. Reportedly, NVIDIA was in talks to acquire your company or at least deepen their relationship, deepen their investment. NVIDIA is already one of one of, Reflection's largest shareholders. If you can speak to that, that would be great. But more generally, what's next for Reflection? What is the plan over the next few years? [00:54:20] S4: The goal for the company is to continue building great open models, deploy them into customer segments, into enterprise, public sector sovereign, and build a generational company around this. And we hope that we're not kind of the only ones that... We hope to see an ecosystem of open model builders come out of The States this year, next year, that rivals... That that is comparable, right, in quality to the Chinese open model ecosystem. I think the thing that makes China so powerful in its open model build out is that it's not just one company. It's a handful of companies, and it's a whole ecosystem. And then fact that one keeps leapfrogging the other, ensures that kind of as a composite, there's always great models coming out from there. So we want Reflection to be a standalone leader in this ecosystem. But we wanna see a whole ecosystem of such companies emerge in the West. We don't really comment on media speculation, but the plan for the company is to continue building great models and basically distribute them into enterprise and public sector and sovereign accounts.
00:54:20 · Misha Laskin, Ed Elson
[00:54:20] S4: The goal for the company is to continue building great open models, deploy them into customer segments, into enterprise, public sector sovereign, and build a generational company around this. And we hope that we're not kind of the only ones that... We hope to see an ecosystem of open model builders come out of The States this year, next year, that rivals... That that is comparable, right, in quality to the Chinese open model ecosystem. I think the thing that makes China so powerful in its open model build out is that it's not just one company. It's a handful of companies, and it's a whole ecosystem. And then fact that one keeps leapfrogging the other, ensures that kind of as a composite, there's always great models coming out from there. So we want Reflection to be a standalone leader in this ecosystem. But we wanna see a whole ecosystem of such companies emerge in the West. We don't really comment on media speculation, but the plan for the company is to continue building great models and basically distribute them into enterprise and public sector and sovereign accounts. [00:55:36] S2: For anyone listening to this who is thinking about entrepreneurship, thinking about AI, you've built an incredibly valuable company, $25,000,000,000 as the most recent round. You've worked at Google. I mean, you have a lot of expertise in this area. Any advice for any younger people listening to this, thinking about entrepreneurship, and maybe starting a company themselves?
00:55:58 · Misha Laskin
[00:55:58] S4: The biggest learning that I've had, and it's pretty straightforward, is to have a deep sense of what it is that you're interested in, and it's okay if you don't know what that thing is now, and there's no rush to jump into building companies. Just building a company for the sake of building a company is not a good reason. Building a company for, I think, financial reason, there are plenty of way better, less risky ways to make money. So, it has to come from something that you're deeply interested in, that you're going to commit a lot of time to, and see through even when things are tough, and so for me, the journey of getting to this company was preceded by studying physics for a long time, for years, developing an interest in science there, discovering this interest in AI in the mid-2010s, as deep neural networks were starting to work, going in and working at the frontier, really understanding the frontier of something, right? And so understanding what is a problem set, finding a business partner that I trust fully, and that I was very kind of excited to build something with, because we already had worked together very closely on projects before that. So, right, I would say that if someone is considering starting a company, I'd advise it not to be rushed in the sense that, oh, I need to start a company for the sake of starting it. It should just come from a place of deep interest and commitment, and you'll kind of... People will feel when it's right. You can't kind of... We all have our own BS detectors, and maybe there's a quote by Feynman that the easiest person to fool is yourself. And so I think that maybe the advice is not to fool yourself into building a company, but only do it if it's coming from a place of deep interest in in that space and idea.