🔬 RL with Verifiable Rewards, but the Verifier is a Lab — Lila Sciences
About this episode
From the show’s notesAndy Beam (CTO) and Rafa Gómez-Bombarelli (Co-founder & CSO of Physical Sciences) of Lila Sciences join us to talk about building scientific superintelligence.
Andy makes the case that the internet is a spent resource ("we have but one internet. It's the fossil fuel. We fracked"), and that the next internet-scale dataset comes from running the scientific method as reinforcement learning, with the wet lab as verifier. Science becomes an "infinite token generator" — the lab isn't the product, the model is. The counterintuitive result: one general model trained on ~10 trillion experimentally-verified reasoning tokens across biology, chemistry, and materials beats the domain-specific ones — "breadth gives us depth."
Read the show’s notes in full
Great blog post from Escalante Bio referenced in the episode: "Your Experiment has a Runtime" (blog.escalante.bio/your-experim…)
Highlights: - The lab as data center: instruments on "a PCI bus," humans "below the API line" - A CAR-T candidate designed in six months by two or three people - "Monster UTRs" hitting ~10x Moderna/Pfizer mRNA expression - The "zero-FTE startup" business model - "You can't have scientific superintelligence if you're just a good test taker" - Rafa's "bittersweet lesson": "only the things that you can scale matter" - Why there's still no AlphaFold for materials - RL pathologies: collapsed chains of thought, a model that "swears" - A vision-language model driving a Windows 95 instrument - "The world's largest collection of voided warranties in biology"
Links:
Andy Beam: linkedin.com/in/andrew-beam-01a…
Andy Beam (Lila):
lila.ai/team/andrew-beam
Rafa Gómez-Bombarelli:
linkedin.com/in/rgbombarelli
Rafa Gómez-Bombarelli (Lila):
Lila Sciences:
Lila Sciences (LinkedIn):
