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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.

Drawn from what Jeff Dean said

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What Jeff Dean actually said

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  1. Jeff Dean

    Chief Scientist at Google DeepMind and Google Research

    And the nice thing about that is that information is really clear to the model, unlike the training data the model was trained on where it's all kind of like trillions of tokens stirred together into a soup of of hundreds of billions or trillions of parameters, but it's all less clear than the actual context uh that the model sees directly for this particular problem or uses use case.

Added to korrents 30 Jul 2026 · How quotes work · Something wrong? Tell us

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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.

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