Nobody knows what is going on inside a large model, and the interpretability pictures we can draw do not answer the only question that matters.

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Our reading — they may agree, disagree or merely touch the same thing. Closest first: a shared subject counts for most, then how near the wording is.

• Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it. DLDerek Lowe19 Sept 2024similar wording
• Large language models are a bad way to do science, because they have been fed so much that nobody knows what they already knew. RSRichard Sutton26 Sept 2025similar wording
• Models are enormous only because the internet is bad: most of that capacity does memory work, and a better dataset would need far less of it. AKAndrej Karpathy17 Oct 2025similar wording
• What sits in a model's context is far clearer to it than its training data, which is trillions of tokens stirred into a soup of parameters. JDJeff Dean30 Jul 2026similar wording
• Large language models are bad at chess: pattern recognition is not the same capability as searching one position very deeply. ACAlbert Cheng5 Oct 2025similar wording

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