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Jeremy Howard: LLMs 'cosplay' understanding, not truly comprehending

Jeremy Howard argues that Large Language Models (LLMs) do not possess genuine understanding, but rather excel at mimicking comprehension. He suggests that their impressive performance is akin to cosplay, where they convincingly imitate human-like responses without true internal reasoning. This perspective challenges the notion of emergent consciousness or understanding in current AI systems. AI

IMPACT Challenges the perception of AI understanding, suggesting current LLMs mimic rather than comprehend.

RANK_REASON Opinion piece by a named credible voice (Jeremy Howard) on AI capabilities.

Read on Machine Learning Street Talk →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Jeremy Howard: LLMs 'cosplay' understanding, not truly comprehending

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3 / 100
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Newsworthiness bucket
Commentary
Opinion piece by a named credible voice (Jeremy Howard) on AI capabilities.
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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opinion
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
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Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Machine Learning Street Talk TIER_1 English(EN) · Machine Learning Street Talk ·

    LLMs Cosplay Understanding (Jeremy Howard)

    Jeremy Howard, co-founder of fast.ai and Answer.AI, on the endless online argument over whether LLMs "really" understand. His answer is that both sides are right: LLMs cosplay understanding, much like the man in Searle's Chinese room. For a great many tasks the difference doesn't…