Scinetics

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1. 2d
   Scinetics unveils Chain of Structures, a science-token reasoning chain for enzyme design

   Scinetics, with researchers from MIT, Harvard, Cambridge, HKUST and the company (Zai-Xi Zhang as corresponding author), proposes a "Chain of Science Tokens" that treats sequences, structures, images, omics and measurements as scientific units the model can read and write alongside language, and implements it as Chain of Structures (COS) for enzyme design in four rounds: fixing the catalytic core, completing the active site, building the global backbone, and adding sequence and side chains. In the team's enzyme-design benchmark COS leads five of six metrics, with EC3 (three-level enzyme classification consistency) of 57.0% versus CodeFP's 55.3%, pLDDT of 79.3 and TM-score of 0.729; ablations drop EC3 to 53.4% without the reasoning chain and to 51.8% with the chain but without the continuous interface. A companion Perspective outlines ScienceRSI (scientific recursive self-improvement) and a Scientific Super Intelligence goal, floating a 100B–300B parameter, 10T–30T training-token exploration window; code, weights and an online demo are public, but real enzyme activity, selectivity and stability still require wet-lab validation.

   36氪 人工智能 · 🔥 0

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