TBH an open source multiple ledger system for financial transactions was an amazing idea which has helped stabilize a lot of economies around the world whose currencies became undervalued to extremes.

NFTs was fucking dumb tho, lol, basically a way to print a receipt for traded goods without any legal enforcement on tying the property to the receipt.

Schedules reinforcement. Destined to cause addiction. Like vegas gambling casinos. Or drugs. Or the economy.

Yeah, I agree with that. And their solution instead of actually fixing the problem is throwing money and computing power at it in the hope that brute force will make it "better." When in reality it hasn't even changed that much in the past year besides more eloquently saying complete bullshit. Call it a conspiracy, but I think with nobody ever telling the truth on the internet, LLM's have only taught themselves to bullshit everyone into believing them.

Most people have no issue with what we were calling AI before the LLM fad hellscape we're currently in.

No one sane is going to object to using machine learning to optimize the performance of an antenna, or crash safety of a car frame. People aren't against the existence of AI opponents in video games. No one was ranting about fuzzy search algorithms, or neural nets on their own. Beyond that, data science has been a thing for ages with no contreversy.

The issue is generative AI and how it is being used. The best case use scenarios are just supplanting tech that already exists at higher cost and delivering worse results. The worst case use scenarios are attempting to cannibalize multiple creative pursuits to remove the need for humans and maximize profits.

and using WP to improve WP is... not a good idea.

That is not inherently true. For example, there was an instance when I read a Wikipedia article, and a chart was simply incomplete, there were entries in the chart left blank, when I knew that data existed. All I had to do was look up those exact items in Wikipedia and the correct numbers were there, readily available.

I think that was when I first created a Wikipedia account for editing. There was an article clearly missing information and I knew it would be both non controversial and quite easy to fill in that information.

My point is, that first article could definitely be meaningfully improved, using only information already available on Wikipedia.

You're probably assuming that someone would just go to an LLM and say "write a Wikipedia article about subject X"? That wouldn't work well, but that's very far from the only way to use LLMs for Wikipedia work.

For starters, it doesn't have to actually write content at all. You could paste an existing article into an LLM and ask it "What facts in this article lack references to back them up? Are there any weasel-worded statements, or statements that don't appear to follow a neutral point of view?" And get lists of things that require attention.

Or you could paste a poorly-worded article in and tell it to rewrite it with all the same information but better phrasing or structure. You could put a bunch of research materials you've gathered into the LLM's context and tell it to write a summary in the style of a Wikipedia article, with references to the sources for each fact mentioned. Obviously you'd check the LLM's work afterward and probably do some manual editing, but this would be a great time and effort saver to get a first draft written. You could take an existing article and tell the LLM that some particular fact had changed or been discovered to be incorrect and ask it to rewrite the relevant parts to account for that.

Wikipedia is in many, many languages. You could have a multilingual LLM automatically compare the contents of different language versions of a Wikipedia article and ask it to spot differences in content or tone. You could have an LLM translate an article from one language to another as a starting point for creating an article in that new language.

You could have the LLM check the references of an existing article - look up each referenced work on the web and see whether it genuinely says what the article that's using it as a reference says. It could flag all manner of subtle problems that way. Perhaps the reference sounds biased, or whoever used it as a reference misinterpreted it, or the link was simply incorrect and points to unrelated material. Being able to have an AI do a first-pass check of all that in a completely automated way would save huge amounts of time.

This is all just brainstorming off the top of my head, so I'm sure there's plenty of other good uses that aren't coming to mind.

Compelling argument.

They dont have brooms, they only have bulldozers. I would prefer my living room un-bulldozed.