Raw LLM Responses

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@user-ur8co1yn5l I thought later that compression might be a simpler analogy to convey the point. But take your example - That wouldn't be the translation, that would be the reference to draw upon the index of data. Like, the models don't soak in images of tigers and store them as the text "big orange cat", using that prompt the model then translates it's stored data - the relationships between pixels and shapes and tagged words all clustered into the neural network, into a comprehensible (hopefully) output. Anyhow that's my understanding of the process, which definitely seems like a collage-by-abstraction process.
youtube 2023-02-07T11:0…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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