DeepMind Paper: LLMs Can Derive Relativity but Not Invent It

A Google DeepMind paper (by Tom Zaharay) explores the structural limitations of large language models in scientific discovery, arguing that current AI cannot achieve true scientific invention. The paper breaks down scientific discovery into induction, deduction, and abduction, using Einstein's development of general relativity as a case: with Newtonian mechanics matching observations to within 10⁻⁹, LLMs can derive from known premises but structurally cannot perform the 'abductive leap' needed to propose new scientific premises. Developer JoshuaJBouw corroborates this with his edge computing experience: current models often fall back rigidly to old known techniques when facing unknown problems, lacking creative leaps.

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2026-07-30 ~ 2026-08-01 · 5 related posts

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