I had the same thought: What were we all missing these past three years? And I think it's just that while everyone was staring at LLMs, the hardware has become a lot better and we now have 0.8B models that are extremely well-trained, so that allows us to look at the "old tech", such as classifiers, in a new light. It's also interesting because it decentralizes innovation: You don't need billions of hardware to do interesting experiments in this space.