Technology

I mean...looms actually seem useful. My experience with large language models is that they're only useful when the output doesn't really matter. Like...they're fine if you're "searching" for things that aren't really defined and you don't really care about the answer (i.e. "what are the five trendiest coffeeshops in Barcelona that are likely to have english speaking staff?" it can't actually know any of that...what's "trendy" even mean? Whatever, who cares, go to a coffee shop on your vacation, have a nice time).

But when it matters you just cannot rely on them...They can't be relied on to use the correct words when precision of language matters, they can't do "research" or "analysis" in any meaningful sense...like maybe better than a sharp middle-schooler? But not as well as a dumb undergrad.

And I don't see any reason, understanding what the technology is to think they'll get better at those things. It's predictive in nature. You know...like maybe it'll go from 60% reliable to 90% reliable over the next hundred years because they'll find some way to focus on high-quality and relevant training data, while still using gigantic training data to get the model up and running...? But since it's fundamentally a predictive model (trying to predict what a good answer would look like), it's never going to be able to actually be relied upon for answers to questions when it matters.

And idk what the cost would be when factoring in all the externalities...environmental destruction, energy consumption...hell, even the infrasound from data centers fucking up everyone's brain...like...there's just no way this makes any economic sense. Right now it's all mega-subsidized, but when that comes to an end...is it gonna cost $10 per prompt on average? $50? Idk, but I know everyone using it now will not want to pay for it.