3 ms·
With emphasis on the "semi-". They are very good at following prompts, and so overplaying the "random" part is dishonest. When you ask it for something, and it
by vidarh 3y ago
With emphasis on the "semi-". They are very good at following prompts, and so overplaying the "random" part is dishonest. When you ask it for something, and it follows your instructions except for injecting a bunch of biases for the things you haven't specified, it matters what those biases are.
- dartos 3y agoAre they good at following prompts? Unless I format my prompts very specifically, diffusion models are not good at following them. Even then I need to constantly tweak my prompts and negative prompts to zero in on what I want. That process is novel and pretty fun, but it doesn’t imply the model is good at following my prompt. LLMs are similar. Initially they seem good at following a prompt, but continue the conversation and they start showing recall issues, knowledge gaps, improper formatting, etc. It’s not dishonest to say semi-random. It’s accurate. The detokenizing step of inference, for example, is taking a sample from a probability distribution which the model generates. Literally stochastic.