Well shit, I didn't think everyone would get so bent out of shape for reiterating that this can only happen when a new model is released because these LLMs are not intelligent and do not learn. Folks and their precious matrices. Sheesh.
> Why did you drop the first half of the sentence in your quote?
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.
The models do not get better until a new one is released. And we are already at diminishing returns. So sorry. Also sorry you don't know the difference between a model and a context, harness, router, or cache.
None of what you mentioned changes the model. Because it's a fixed model. The weights are constant. It does not learn. It only knows what gets repeatedly fed to it and those fixed relationships represented by the weights. You can pretend like that's not true, but unfortunately for VCs it is true.
> Often yes. In this case, it's more like they get upset when someone says something factually wrong, and then defensively changes the goalposts.
Oh give me a break. Show me one example of 1) any knob twisting that makes the underlying model better. or 2) any example of the AI providers twisting those knobs to do anything other than degrade performance for their own bottom line or safety.
The current post says: "it would be expected for a better model to use different amounts of brevity if it gets better at determining the appropriate amount."
When no, the model cannot "get better". It doesn't determine any appropriateness of response realtime except for the weights baked into it from the beginning and whatever context it can muster. If you cram enough guidance that it doesn't decide to ignore maybe you can make it more brief. But it (the model) can do none of those things.
Right. They can do all those things. And none of that will make it smart or able to learn new things. The underlying model is just an llm. But judging from the downvotes, it seems AI folks get upset when someone talks honestly about their precious piles of matrix multiplication.
The models don't get better, except when a new one is released. Their performance depends solely on the model training before release and how well you curate the context you feed it. That's it. Contrary to popular belief these things are not intelligent.
Can we turn off the whining bitchy little comments like yours along with the political commentary? That would be great.
Did you honestly think the mechanazi / porn generator AI wouldn't receive negative comments? Even "hardcore nerds" recognize garbage. Sorry 'bout your luck.
Or, phrased another way: there's a reason why we consider basic availability in nines and 2 nines is still considered pretty bad. 99% uptime means being down over 7 hours each month.
See also "wind moved restlessly", "weather became angry". And raging storm? I mean come on... I won't even put that last one in quotes.
And like a sibling reply pointed out, personificiation is not the same as anthropomophism. Nor is plagiarized personification. It has no inner thoughts, and no fondness of anything. It's nothing but a cheap, superficial facsimile of human writing and nothing more. Great for form filling and boilerplate though. Not so great for anything else.
I am referring to the hype causing it to be adopted now instead of a decade ago, not the specific implementation. The hype causing people to adopt AI of all kinds hastily without proper validation.