And then "Large Language Models are Few Shot Learners" collided with Sam Altman's ambition/unscrupulousness and now TensorRT-LLM is dictating the shape of data centers in a self reinforcing loop.
LLMs are interesting and useful but the tail is wagging the dog because of path-dependent corruption arbitraging a fragile governance model. You can get a model trained on text corpora to balance nested delimiters via paged attention if you're willing to sell enough bonds, but you could also just do the parse with a PDA from the 60s and use the FLOPs for something useful.
We had it right: dial in an ever-growing set of tasks, opportunistically unify on durable generalities, put in the work.
Instead we asserted generality, lied about the numbers, and lit a trillion dollars on fire.
We've clearly got new capabilities, it's not a total write off, but God damn was this an expensive ways to spend five years making two years of progress.