@theadhocracy @Noisecolor @xvf17 @emilymbender "machine learning" isn't a marketing term. It's a research term that's been around for a couple decades now. It originated as a linguistic way to describe compute systems incorporating self-adaptive functionality. A better term might have been training, but learning was what they picked.
@SomeVeganCheeseIsOk @Noisecolor @xvf17 @emilymbender To be clear: not entirely what I meant. I have no issues with the umbrella term "machine learning"; I actually think it works pretty well.
I am specifically talking about GenAI models/LLMs. Again, I think this is a case of linguistic drift. Are they born of ML models? Yes. Do they themselves **learn**. I think that's arguable.
They reincorporate additional data over time. But the core rules don't adapt (caveat incoming)...
@SomeVeganCheeseIsOk @Noisecolor @xvf17 @emilymbender ... unless they're in some kind of feedback loop, running via multiple layers of models, some of which then manipulate those they have greater write level over. The "shepherd and sheep" model stuff.
But that isn't, again, what most people are talking about. An Agent "learning" your habits isn't the same thing. The input/output model isn't adapting, it's just getting more input.
I think we broadly agree anyway 😅