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I really liked Reflection CEO @MishaLaskin's framing on the state of closed vs. open AI models: "Closed models are the equivalent in real estate to renting an apartment... As AI adoption has increased, an ownership market is basically coming in.. The only way to own intelligence, by definition, is if it's open"
Reflection’s founders on building a DeepSeek of the West 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 @MishaLaskin, who led reward modeling for Google’s Gemini, and CTO @real_ioannis, 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. Timestamps: 00:00 Why open models are surging 01:06 Renting vs. owning intelligence 03:40 Open models catch up 05:53 Why China led open AI 08:03 Introducing Beam 10:05 Scaling reinforcement learning 14:09 Training from scratch 16:04 Safety, alignment and openness 32:29 The Reflection origin story 37:32 Making money on open models 42:33 Vertical integration and compute 48:45 Partnerships and distribution 56:46 What’s next for Reflection Links: https://podcast.sources.news/ Spotify: https://open.spotify.com/show/3p1KZvkbdx96VgFh8dP8Ao YouTube: https://youtu.be/BKnAeVej0dc Substack: https://sources.news/p/reflection-founders-open-weight-beam-release Thanks to the show’s premier sponsors: @Atlassian, @meetgranola, and @mercury.