“Reinforcement learning as a problem was solved actually faster than we anticipated. We thought it would take years. It took less than a year, both within external labs, but even within our own experiments.”

Prof G Markets · Money & Markets · November 2026

Context

Asked why he started Reflection in 2024, Laskin describes how his bet on reinforcement learning for agents and coding was overtaken as the big labs got there faster, which is why the company shifted to open models.

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Transcript

Prof G Markets Around 05:03 into the episode

Misha Laskin

…of technological advances coming into the 21st century. And it kind of seemed like, you know, some big discoveries are made in AI that make it kind of the physics of our time. It's kind of the physics of the 21st century. And that's kind of what got me into AI as a field in around the mid-2010s.

Ed Elson

So you're working at Google, and then my understanding is that you start reflection in 2024. Why did you start this company? What did you think was happening in AI or what wasn't happening in AI that you could contribute to?

Misha Laskin

The world, when we, it's funny, it's 2024. This is only a bit more than two years ago, but it seems a lot longer on AI Models. And the field looked very different then. So I'll kind of rewind of what did the field look like in early 2024? GBT-4 had shipped, right? And ChatGPT had taken off. The first Gemini models were shipped, Gemini 1 and 1.5. These are models that my co-founder Janice and I contributed to, especially on the reinforcement learning side. But at the time, intelligence was really only good at chat. The notion of coding, agents, all this stuff, reasoning, none of that existed and it didn't work. Like these models were just good as chatbots. They were not really good at any sort of cognitive work that needed to be done autonomously. And our bet at the time was actually twofold. We saw the beginnings of an open source ecosystem. So some open models had started coming out that were pretty good, you know, like the models for meta and others. And so we thought that those models…

Ed Elson

Can I just interrupt for one moment? What actually is what does open source mean? What does it mean to be an open model? When you describe Linux, which is open source, what is the difference between open source versus closed source?

Misha Laskin

The high-level distinction, closed, you cannot own. You can only rent. Open, you can own entirely. So it's kind of like the difference between the rental and the ownership real estate market. When you are renting an apartment, you don't actually own it, right? You are subject to the whims of your…

Ed Elson

My understanding, which I don't think fully aligns with the analogy, is that an element of open source and the open models is that they're free. It's, I mean, when you buy a home and you own a home, you've got to pay money to buy the home. But with open source models, my understanding is anyone can…

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More from Prof G Markets

“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, you know, 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 from Google… similar when OpenAI launched GPT-OSS.” — Misha Laskin, Prof G Markets

“Compute is scarce because the amount of intelligence you can pack sort of per watt, let's say, keeps growing. So these models get smarter faster than our ability to stand up compute. And when you're in the intelligence market, that's kind of like the market of artificial labor.” — Misha Laskin, Prof G Markets