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There is a limit to how much you can learn about science by reading about science. @exnx's wager is that most frontier models have hit exactly that limit. They are trained on papers, journals, and human accounts of discovery after the fact. What they are not trained on is the raw data itself, and Nguyen is certain more knowledge lives there than has ever made it into print. At some point, training has to move directly to the source. That is the shift he is betting on: language models not as…

Mario Gabriele@mariogabrieleAug 4

What happens when AI can write the genetic code for life itself? Eric Nguyen (@exnx) is the co-founder of @RadicalNumerics, the lab behind the models that generated the first genome ever created entirely by AI, a bacteriophage that had never existed in nature until it wrote one. He believes DNA should be treated the way language is treated: something a model can read, then write. With more DNA sitting in public databases than there is text on the entire internet, he sees an almost unmined field, one where the models built to make sense of it remain, by his own admission, no more sophisticated than linear regression. Thank you to the partners who make this possible @ahrefs Brand Radar: Find your brand in AI results: https://ahrefs.com/generalist @brexHQ: The intelligent finance platform: https://www.brex.com/mario @Guru_HQ: The AI source of truth for work: (3:35) An overview of Radical Numerics (11:08) Why they started with DNA (26:24) The limits of language models in biology (31:15) Eric’s free-range upbringing and path to his PhD program (41:20) Applying long-context models to DNA and meeting his co-founders (55:30) How better general LLMs benefit Radical Numerics (1:02:05) Making biology more concrete (1:18:09) Final meditations

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