LLMs Can't Jump: Research Highlights Lack of Abductive Reasoning for Scientific Invention
JoshuaJBouw · x · 2026-08-01
A developer reflects on their edge computing projects, agreeing with Google's paper "LLMs can't jump" that current models often hard-pivot to older technologies when facing novel problems.
The position paper argues that while modern Generative AI excels at pattern recognition (induction) and logical proofs (deduction), it fundamentally lacks "abduction"—the intuitive leap required to generate novel explanatory hypotheses. Using Einstein's General Relativity as a case study, the paper demonstrates that LLMs are structurally incapable of creating new foundational axioms. The authors propose that integrating physically consistent, multimodal world models is key to bridging this divide.
Related event: DeepMind Paper: LLMs Can Derive Relativity but Not Invent It(5 posts)→
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