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High-volume physical data loops are the cure for cheating models
◆ 85RelevanceOn a story from Latent Space6h ago
Public datasets often lead to models that look performant but fail in production because they have memorized patterns rather than learned logic. Integrating high-speed physical assays allows you to generate the massive, proprietary datasets required to train agents that truly understand domain-specific constraints.
Takeaways
- Proprietary physical data prevents models from "cheating" via simple memorization.
- High-speed assays transform physical chemistry into a scalable compute problem.
- DNA-Encoded Libraries provide the scale needed for agentic chemical reasoning.
Read the original at latent.space
Lab-in-the-Loop at Compute Speed — Ian Quigley, Leash Bio
fmode.me/n/lab-in-the-loop-at-compute-speed-ian-quigley-leash-bio
Written by Founder Mode using gemini-3-flash-preview, from the publisher's own summary. We link the original rather than reproduce it — the reporting belongs to Latent Space.
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