The Open Source AI Model For The West - EP 44 Misha Laskin

**Misha Laskin** (0:00)
I think the mission of the company is far broader than that. It is to build a frontier open intelligence and make it accessible, meaning when we say frontier, there's no reason why open models should be any worse than closed models. Our intention is to build a new frontier lab that drives the frontier of knowledge in artificial intelligence, but doing it in an open way, in an open scientific way. So it's funny that we have to say open science, that's just science, but in an open scientific way, and release the models, enable the community of researchers and developers to engage in how they develop, and build a frontier lab with open intelligence at its core.

**Ashlee Vance** (0:58)
Misha Laskin, how are you?

**Misha Laskin** (1:00)
I'm doing well, Ashlee. Thanks for having me.

**Ashlee Vance** (1:02)
Thank you for coming. Well, you've been in the news, I guess, not immediate, but it's in the last month or two, isn't it, that you guys did your fundraising?

**Misha Laskin** (1:15)
Yes, so it was announced last week.

**Ashlee Vance** (1:19)
It was announced last week, yeah, okay. It is very recent. So you're co-founder and CEO of Reflection AI. You guys raised $2 billion. That's not shabby.

**Misha Laskin** (1:32)
Yeah, definitely.
This thing that's happening in the progress of AI, if you would have asked me five years ago, 10 years ago, I was a physics student, that this is where AI would be. I would not have believed it.

**Ashlee Vance** (1:49)
Yeah, well, I mean, we'll get in, we'll definitely get into all that. But I mean, just think like sets of context. I mean, you guys, the big, the big part of the big message here is that you guys have raised a ton of money. You have a team with an incredible pedigree, some folks from all over the place, but a lot from DeepMind. You were at DeepMind, your co-founder worked on AlphaGo quite intimately, crucially on that project. And so sort of have this all-star team. I figured that's why you were able to raise quite a lot of money. And then you have, you've got a bit of a different pitch, a different frame around what you're doing than, definitely than the OpenAI's of the world. You guys have come out and said, you want to make this open model sort of in the open source vein and to publish the weights of your models. And so, and you're kind of making the pitch that America needs.
We've had Chinese companies, DeepSeek got all this attention for doing an open model and that we need something that's competitive. Facebook's made open models, OpenAI kind of sort of is, and then I think does, and Mistral does-

**Misha Laskin** (3:03)
Yeah, Mistral is definitely an open model player.

**Ashlee Vance** (3:05)
Okay, okay, but this is, am I right in, this is some of the heart of what you guys are saying is it makes you makes you different?

**Misha Laskin** (3:15)
I think so. Certainly, it's become really important to produce great open models of American provenance that are competing or competitive with the Chinese ones. But I think the mission of the company is far broader than that. It is to build a frontier open intelligence and make it accessible. Meaning, when we say frontier, there's no reason why open models should be any worse than closed models. Our intention is to build a new frontier lab that drives the frontier of knowledge in artificial intelligence, but doing it in an open way, in an open scientific way. So it's funny that we have to say open science, it's just science, but in an open scientific way, and release the models, enable the community of researchers and developers to engage in how they develop, and build a frontier lab with open intelligence at its core.

**Ashlee Vance** (4:11)
And I want to nerd out, but I also want to make this accessible to as many people as possible. So even just some of these basics that we're talking about, when we're talking about an open model versus a closed model, when companies, when we talk about weights, I mean, it's almost like these mathematical calculations, these numbers that are attributed to the neural network, and how it will behave. And to some extent, this is like the secret sauce. You do all the training, and you come out with these weights that make your model hopefully behave the way you want it to behave and do incredible things. And so some companies keep those proprietary into themselves. And then you guys are talking about being able to be at the cutting edge of what these well-funded companies who have access to all this computer doing, but doing it in this more open way. Why is it even, you know, I come from, I covered open source software for years and it was this very like ideological thing, especially in the late 90s, early 2000s. Microsoft was rising and there was a whole faction of people that were, you know, they saw code like writing, like knowledge that should not be contained within a company. You should be able to alter your computers as you see fit. This knowledge should be shareable, you know, and they saw Microsoft as really like, it was almost a religious debate, right? Like they were evil for doing proprietary code. And man, I mean, I lived through that. It was like emotional and people really cared. I haven't felt that same level of like enthusiasm and rhetoric and everything around open models. You brought up science, you know, scientists tend to lean more in the open direction in my experience. All right, what do we do at Core Memory? We cover innovative, fast moving, forward thinking companies, which is why Core Memory is sponsored by Brex, because Brex is the intelligent finance platform for many of these companies. 30,000 companies from startups to the world's largest corporations rely on Brex's technology for their finances. They've got smart corporate cards, high yield business banking, and expense automation tools that are fantastic. I hate doing my expenses. And Brex's AIs and software run right through those expenses, figure out where we're spending money, and take care of so much stuff for you, so you don't have to waste your time on it yourself. Go to brex.com/corememory to learn more, and just get with the program. Let's get going. Let's get out of this archaic finance software and move toward the future, core memory and Brex. How do you come about it? Like, why is it intellectually, philosophically, technologically important to have these open weights?