Beyond Navier-Stokes: who controls scientific discovery in the age of AI?
hugobowne · x · 2026-09-11
Hugo Bowne-Anderson argues AI's math breakthroughs are the canary in the coalmine for experimental science and knowledge work. Drawing on Michael Bronstein's MPI keynote, the piece describes a vision where biological experiments generate ML-optimized, human-uninterpretable data at scale, producing black-box models with hundreds of parameters instead of Newton-style insight — understanding deferred, not guaranteed. He asks what this means for human understanding, corporate power, and who controls discovery.
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