LLMs Diverge, Humans Converge — LLMs Can't Come Up With Ideas (opens in new tab)

LLMs can't come up with ideas. The output of an LLM (Large Language Model) tends to be divergent. It moves in the direction of deriving combinations from its training data. Good ideas, on the other hand, are convergent. They solve multiple problems at once with a single mechanism. When using LLMs, I think it's important to keep this difference in mind as you proceed. In this article, I want to describe why it's difficult for LLMs to design databases, how this may accumulate as small effects e...