Threads

AI for science

AI as an instrument of scientific discovery — AlphaFold solving protein structure, Olympiad-level mathematics, and by 2026 original results including a conjecture counterexample and formally-verified proofs.

This thread follows AI used not as a product but as a scientific instrument. Its landmark is AlphaFold. DeepMind’s AlphaFold 2 solved protein-structure prediction at the CASP14 assessment to a degree much of the field had thought a decade away, and its publication in Nature with open code and a database made it a standard tool across biology within months.

The programme widened. AlphaFold 3 extended prediction across proteins, DNA, RNA and small molecules; AlphaProof and AlphaGeometry 2 reached silver-medal standard at the International Mathematical Olympiad. The scientific establishment ratified the shift when Demis Hassabis and John Jumper shared the 2024 Nobel Prize in Chemistry for the protein work.

By 2026 the claim had moved from prediction to discovery. Anthropic reported that its Fable model had produced a counterexample to the Jacobian Conjecture, and OpenAI published ten formally-verified mathematical advances from an unreleased model. The open question the thread raises is where assistance ends and authorship begins — whether these systems are powerful instruments in human hands or are starting to do the science themselves.