Periodic Labs' Neon, RL'd on lab data with 1,300 H200s, beats GPT-6 Astra on materials analysis
vwxyzjn · x · 2026-09-16
Liam Fedus announced that Periodic Labs built high-throughput materials labs in Menlo Park creating a loop between experiments and models: labs generate fresh data, models learn from it, then help decide what to try next.
- Using only 1,300 H200s plus months of proprietary experimental data, they mid-trained and RL'd an open-source model into "Neon," which surpasses GPT-6 Astra on their analysis benchmark
- Initial focus: hard materials science problems including superconductors, magnets, and semiconductor materials
- Real lab footage was shared; the team argues AI must interact with and learn from the real world for AI-accelerated scientific discovery to succeed
Related event: Periodic Labs beats GPT-6 on materials science with just 1,300 H200s(41 posts)→
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