I find that LLMs went much further than I initially thought 3-4 years ago. My impression is that pretraining enables many non trivial things to work, that would never otherwise (test-time "thinking", rlhf, fine-tuning on non trivial targets, interaction with tools etc). Am I the
If you pass a sequence of constant tokens to a transformer with rotary encodings, it will return a constant output distribution, because the attention values are constant. Idk if someone spotted this "bug" before?
