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LLMs are interpolation machines unable to extrapolate, limiting their answers to training data.

A user on Mastodon expressed agreement with the idea that Large Language Models (LLMs) function primarily as interpolation machines. They argued that LLMs are inherently incapable of extrapolation, meaning they struggle to generate answers not present in their training data. Consequently, responses to novel questions have a very low probability of being produced. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Suggests fundamental limitations in LLM reasoning capabilities, potentially impacting their use in novel problem-solving scenarios.

RANK_REASON Opinion piece by a user on a social media platform.

Read on Mastodon — fosstodon.org →

COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 · [email protected] ·

    @ hweimer agree. LLMs are interpolation machines. They can't, by design, extrapolate. An answer that was never given is unlikely to be in the training set and h

    @ hweimer agree. LLMs are interpolation machines. They can't, by design, extrapolate. An answer that was never given is unlikely to be in the training set and hence has a very low probability. # ai # llms # science # math # physics