> it’s just BERT with more data
Let's take that as a given. Is BERT with more data not useful?
> I can see why people would want ready made one shot classifier, and I can see the value of sending multiple classifier in one call, but I wouldn’t call it breakthrough
Are those things that people want less useful because of what someone else calls it?
> I see it as a wake up call for the tech community to go back to basics for most tasks instead of relying solely on generic LLMs.
Maybe, or maybe to use Jev, which is useful?
Whether something is overmarketed or undermarketed, novel or derivative, it does not change its function.
I made it clear that it is useful and I can see many people using it including myself. My point is it’s not a breakthrough.
Fine tuning small models is not novel. The novelty is large model generalization without fine tuning, at small models cost/latency.
The OP acknowledged they needed to fine tune their model to the training data of the task vs. zero-shot Jev
If nothing else, it's a popularity breakthrough to have people excited about it.