Podcast Episode

Reflection’s founders on building a DeepSeek of the West

ACCESS
Oct 5, 20261 hr 2 minEN
Host
AHAlex Heath

Who’s talking

4 speakers
Misha Laskin32 min · 52%
Ioannis Antonoglou16 min · 26%
Alex Heath13 min · 22%
Speaker 40 sec · 0%

Transcript

75 turns · 1 hr 2 min
AH
Alex Heath0:00

i've been thinking a lot about timing as we were preparing to have this conversation because what you guys are doing with reflection feels very apt to the moment we're in i was looking and mentions of open models on earnings calls 6x in q3 and open model tokens are now the majority of what's flowing through versell and open router So there's this real shift that's been underway. And you guys have been in stealth and have big news that we're going to talk about on the open model front. But first, before we get there, I'd be curious to hear you both comment on what you think is driving this moment right now in terms of the surging interest in open tokens. There's multiple things here I think we can peel back at. But if you were to kind of look at it big picture, what do you make of the moment we're in? Misha, we could start with you.

ML
Misha Laskin0:45

You know, we decided to really push for building great open models at this company about a year ago. And at the time, I think that there are some things that we saw that would be kind of happening that have happened faster than we expected. And maybe one way to think about why open models are so top of mind and so important right now is using a real estate analogy. which is we have to remember that in the AI market, this market commercially has only existed for maybe three years. The market effectively started as a rental market. Closed models are the equivalent in real estate to renting an apartment. You're renting your intelligence and that makes a lot of sense, especially when you're earlier in your life, you're a student or you just graduated college, you might go and rent an apartment. But as a consumer, you get older, you have a family, you have more finances. Ownership starts mattering a lot more in the real estate market. And so that's why there's rental and ownership in real estate. AI timelines are compressed. And so we've been in this commercial market for three years, where effectively in the West, there's only been a rental alternative. And now what we're seeing is that as AI adoption has increased and the small startups that were tiny a few years ago are now giant enterprises and large enterprises have adopted AI, an ownership market is basically coming in. And the only way to own intelligence is, by definition, if it's open. Because if it's open, you can run it on your stuff, you can own it, you can control it, you can customize it. And what we're seeing is that the reason this has happened so quickly is because AI as a market has grown so quickly. And you're right, I think that 12 months ago, not that many enterprises at all were using open models and not even startups really were using open models all that much. Six months ago, a lot of startups that had grown at the application level started switching to open models and have continued growing very quickly. And I think that's where maybe six months ago, there was 30% of token consumption on open router oversell was going to open models, 70% to close. And now six months later, it's flipped where it's maybe more 70% on open models and 30% to close. And so we've just seen a very fast movement in the maturing of the AI market.

AH
Alex Heath3:15

And I

ML
Misha Laskin3:15

think that is one

Episode notes

Reflection is soon releasing Beam, its first open-weight AI model, in a bid to become the DeepSeek of the West. Trained from scratch, Beam is designed for coding, reasoning, and AI agents. Reflection's benchmarks put it alongside the strongest open models, with substantially more efficient token economics.

To mark Beam’s debut, I'm joined by Reflection's co-founders: CEO Misha Laskin, who led reward modeling for Google’s Gemini, and CTO Ioannis Antonoglou, who helped create AlphaGo and AlphaZero before leading Gemini’s RLHF effort. Reflection has raised $4.6 billion from investors that include Nvidia, Sequoia, and Lightspeed.

We discuss why Chinese labs pulled ahead in open AI models, how Reflection built Beam, and why the founders think companies and countries will increasingly want to control their own models. I ask how they plan to make money from open-weight AI, whether openness can make these systems safer, and what comes next for Reflection.

Thanks to the show’s premier sponsors: Atlassian, Granola, and Mercury.

Showing a preview — retrieve the full transcript via the Exa API.

Powered by the Exa API