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LLMs like Kimi k3 lack creative reasoning, mirroring Einstein's era arguments

The author argues that current large language models (LLMs), even those with massive parameter counts like Kimi k3, are fundamentally limited in their ability to perform true creative leaps or resolve contradictions. This limitation stems from their reliance on induction and deduction, mirroring the arguments made in a 2014 blog post by Amni Rusli and a recent paper by Google DeepMind titled "LLMs Can't Jump." These sources suggest that while LLMs excel at composing fluent text based on existing data (induction) and following logical steps (deduction), they lack the capacity for abduction – the creative reasoning required to generate novel hypotheses or reconcile conflicting information, a skill exemplified by scientific breakthroughs like Einstein's. AI

IMPACT Current LLMs, despite scaling, still struggle with creative leaps and contradiction resolution, indicating a need for new approaches beyond simply increasing parameters.

RANK_REASON The item is an opinion piece discussing the limitations of current LLMs in relation to historical arguments about creative reasoning, rather than a direct announcement of a new model or research finding.

Read on dev.to — LLM tag →

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LLMs like Kimi k3 lack creative reasoning, mirroring Einstein's era arguments

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  1. dev.to — LLM tag TIER_1 English(EN) · Daniel Nwaneri ·

    Why Kimi K3 Still Can't Do What Einstein Did

    <p>In geophysics you almost never get to see the thing you're studying. You get a seismic trace, a gravity anomaly, a resistivity curve. You don't get the rock. You get the rock's echo, and you have to guess at a structure underground that would produce exactly that echo and no o…