Radical Numerics says its genome model can continue an aptamer optimization trajectory
The company's self-reported claim that its GLM reproduced held-out high scores from low-scoring RNA sequences only; no independent verification yet.
重要度局所的証拠E2 未複製執筆簡易
Radical Numerics CEO Eric Nguyen said in the show notes of the September 23 Latent Space episode that his genomic language model, in an aptamer experiment, recapitulated some held-out high-scoring samples after seeing only low-scoring RNA sequences.
Per the episode's show notes, the experiment held out the best-performing aptamers, showed the model only lower-scoring sequences in a rising series, and the model continued the trajectory on its own. Nguyen calls this chain-of-thought "thinking in DNA."
This is a first-party claim: the dataset size, scoring method and full results are not published with the notes, and it should not be read as independently verified performance. Watch for a checkable paper or benchmark.