Bitter lesson is wrong. Large general models are outperformed by small specialized models.
That might mean that spending all that money on that giant master of none model might lose out to the much smaller specialist model, uh-oh…
The Bitter Lesson is that human-written rule models will always lose out to trained models in the end.