this post was submitted on 31 Aug 2023
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For the AI heads here: is this another problem caused by the "black box" style of LLM creation where they don't really know how it actually works, so they don't really know how to take out the data?
They know how it works. It's a statistical model. Given a sequence of words, there's a set of probabilities for what the next word will be. That's the problem, an LLM doesn't "know" anything. It's not a collection of facts. It's like a pachinko machine where each peg in the machine is a word. The prompt you give it determines where/how the ball gets dropped in and all the pins it hits on the way down corresponds to the output. How those pins get labeled is the learning process. Once that's done there really isn't any going back. You can't unscramble that egg to pick out one piece of the training data.
I really like that pachinko analogy. It gets the basic concept across without having to wade into technical descriptions.