Rant: everyone keeps saying bigger AI models are always smarter, and a paper from Stanford made me doubt it
I keep reading comments here saying we just need bigger models to solve everything, but a study I came across from Stanford says otherwise. They ran the same math and reading tests on smaller models tuned for one job, and those small ones beat the giant ones on 7 out of 10 tasks. The part that really got me was the cost: the big model needed about 40 times the compute to lose on the same questions. I am not saying scale does not matter, but I do not buy that it is the only thing that matters. Has anyone else tried a small focused model and gotten better results than a big one?