Kinda sounds like most tools. If I try to fry an egg using a screwdriver its going to go very poorly for the egg and my cookware.
That’s the main issue with AI. It’s use cases have not been properly identified by the population. Unfortunately what it does wrong is not as obvious as my example. We built the tool and started using it before we knew how to use it.
irate944@piefed.social 1 week ago
Respectfully disagree. It’s because of the systematic insistence that we need to build data centers to support a demand that doesn’t exist.
Same thing would happen if corporations lost their minds over hammers and insisted we had to build hammer factories everywhere and sell hammers to stirr your coffee.
porous_grey_matter@lemmy.ml 1 week ago
It’s rare that “not always accurate” and “expensive” are both acceptable in a tool. They fail on two axes of the fast/good/cheap spectrum so I still think it’s an extremely niche tool, unlike a hammer which still fulfills an extremely common need for relatively little money.
irate944@piefed.social 1 week ago
Being common or niche has nothing to do with the quality of the tool. In fact LLMs should be a niche tool, because there’s only a few use cases where they are genuinely useful.
Thus what I said before, the problem is the companies trying to shove it everywhere without thought or care.
On being accurate or expensive, it depends heavily on what model we’re talking about and what exactly you’re using it for.
Put a light model summarising your web search, yeah, it’s an accident waiting to happen. Put a coding model helping you out building a small function while you focus on the main algorithm, it will save you a lot of time.