Sriram Krishnan on Open Source AI's Biggest Week Yet
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What is the main topic discussed in this episode?
If you kind of bring it back to very business-first principles, if you're providing a product of value, capitalism will find a way to make the supply chain work for you. So if you have an open-weight model that is providing value, that means that every part of the stack underneath, whether it is a neocloud, the chip provider, somebody who provides gas turbines or fire suppression, is going to orient itself to provide value. If you're providing a product of value, capitalism will take care of all the rest. If you go look at how the rest of the ecosystem is doing, the growth is pretty strong and spectacular. And I think you're going to see that continue.
Open source AI is moving faster than ever, and the balance of power in the industry may be shifting. In this episode, Theo Jaffe and Sofia Puccini are joined by former White House AI policy advisor Sri Ramakrishnan to unpack what the latest wave of open models means for frontier labs, AI policy, pricing, cybersecurity, and America's position in the global AI race.
We are back. We are live with Sriram Krishnan, who just finished his tenure as the Senior White House Policy Advisor on Artificial Intelligence, previously as a general partner at Andreessen Horowitz, and held senior roles at Microsoft, Meta, Snap, and Twitter. So, Sriram, we're so glad to have you on. Welcome to MTS.
Thank you. I've been a fan of everything you folks have been doing for the last few months and excited to be here. I think this is the first time in about two years I've been able to do a video appearance without a suit and tie on. So I am so excited to be out of that.
Yeah.
Amazing. So there's so much going on in open source the last week. We just discussed we had Grok Build was open source, and then we had Thinking Machines, and then Kimmy K3, and then Quen 3.8. So you tweeted the other day, Kimmy K3 is a big moment with multiple implications for the entire industry. Could you go into a little more detail on that?
What are these implications? Yeah, so if you go back maybe four or five months, I think there was a moment in time when the only leading models were, I think, Opus 4.6 or 4.7 at the time, GPD 5.4 or 5.5 or wherever we were. And it felt like there was really no one else. And we were on this curve of self-improvement where the frontier labs were really going to draw really far away from everyone else. I think the last few weeks, if you are in the token consumption business, which I am, and I think many of you and your viewers are, it's been a great time. Because let's see, you had Elon and Michael at Cursor, the SpaceX XAI team come out with Glock 4.5, which I've been using. It's a fantastic model.
I think we forgot to mention this. We had Alex Wang and Meta come out with Muse Spark, which is also awesome. Last week, we had Meera Tinky come out with Inkling. I don't know their version number, but the first version of that model. which I think is nearly SOTA on many, many benchmarks. But I think the big news over the last three, four days was obviously Kimi K3 coming out, I think on Thursday or Friday. And then I think the last 24 hours, I haven't really played with it yet, but Quinn coming out. So there's a lot of choices and alternatives coming out. And what I was referring to with Kimi K3 is the following. One is that it's just great to have choice in the ecosystem and to be able to point your harness of choice or your agent of choice to multiple models.
Second, I think we are in this really weird moment now where some of the American frontier models are constrained. For example, on cyber and on security. And I was talking to a friend of mine where this person was actually starting to do security work using Kimmy K3 rather than Fable because with Fable, he would run into these refusals and safeguards. So that seems like a very weird spot to be, which we can talk about for a second. I think it's probably inevitable that if you are having choices from where you get your intelligence tokens from, that's going to put pricing pressure on the frontier models, which means I think you'll probably see the frontier labs have to
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