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Not sure that's relevant. Obviously an LLM has to learn from something, but it's not a database. I could also program this myself and I don't think that it's an argument against my coding abilities that I have read the source code to many existing interpreters. I can only do it because I not only read but also understood and internalised.

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It’s not a database, it’s a prediction engine. It’s going to be very good at predicting things it was trained on.

But it's almost a database. See the full glass of wine conundrum.

That seems to only have affected standalone diffusion models. E.g. gpt-4o native image generation is easily able to generate a full glass of wine.

not a satisfactory version, from what I saw posted here yesterday.

https://news.ycombinator.com/item?id=43475314

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