Because this entire discussion is about the release of a new model, and models are fixed. Sure you can try to modify all the scaffolding around it, but the model is the model. It doesn't matter what you're trying to improve. You can only improve the peripheral aides. And the peripheral aides can't fundamentally fix the problems with llm models when they can't learn new relationships or facts.
You will always have to wait for a new model (like this one we are talking about) for improvements to the model.
Right. The sentence you quoted was about brevity improving with a new model. It did not suggest the model itself improving.
I’m confused why you’re stuck on this tangent. And confused why you are repeating the talking points about the model being fixed. The model is fixed - that’s true, I already agreed with you. But you don’t seem to be listening to anything else.
> It doesn’t matter what you’re trying to improve.
What do you mean? If we’re trying to improve LLM output, there are multiple ways to achieve it. A new model is one of them. Changing the inputs is another.
> You will always have to wait for a new model (like this one we are talking about) for improvements to the model.
This is true! Nobody here is disagreeing with that. The part that it seems you’ve argued incorrectly is the apparent claim that output can’t get better. Output can “improve” without improving the model.