The impactful innovations in AI these days aren't really from scaling models to be larger. It's more concrete to show higher benchmark scores, and this implies higher intelligence, but this higher intelligence doesn't necessarily translate to all users feeling like the model has significantly improved for their use case. Models sometimes still struggle with simple questions like counting letters in a word, and most people don't have a use case of a model needing phd level research ability.
Research now matters more than scaling when research can fix limitations that scaling alone can't. I'd also argue that we're in the age of product where the integration of product and models play a major role in what they can do combined.
Research now matters more than scaling when research can fix limitations that scaling alone can't. I'd also argue that we're in the age of product where the integration of product and models play a major role in what they can do combined.