• 1 Post
  • 24 Comments
Joined 2 months ago
cake
Cake day: February 5th, 2025

help-circle











  • We shouldn’t be using it to replace artists, writers, musicians, teachers, programmers, and actors.

    That’s an opinion - one I share in the vast majority of cases, but there’s a lot of art work that AI really can do “good enough” for the purpose that we really should be freeing up the human artists to do the more creative work. Writers, if AI is turning out acceptable copy (which in my experience is: almost never so far, but hypothetically - eventually) why use human writers to do that? And so on down the line.

    The problem is that capitalism and greedy CEOs are hyping the technology as the next big thing, looking for a big boost in their share price this quarter, not being realistic about how long it’s really going to take to achieve the things they’re hyping.

    “Artificial Intelligence” has been 5-10 years off for 40 years. We have seen amazing progress in the past 5 years as compared to the previous 35, but it’s likely to be 35 more before half the things that are being touted as “here today” are actually working at a positive value ROI. There are going to be more than a few more examples like the “smart grocery store” where you just put things in your basket and walk out and you get charged “appropriately” supposedly based on AI surveillance, but really mostly powered by low cost labor somewhere else on the planet.


  • I’m about 50/50 between helpful results and “nope, that’s not it, either” out of the various AI tools I have used.

    I think it very much depends on what you’re trying to do with it. As a student, or fresh-grad employee in a typical field, it’s probably much more helpful because you are working well trod ground.

    As a PhD or other leading edge researcher, possibly in a field without a lot of publications, you’re screwed as far as the really inventive stuff goes, but… if you’ve read “Surely you’re joking, Mr. Feynman!” there’s a bit in there where the Manhattan project researchers (definitely breaking new ground at the time) needed basic stuff, like gears, for what they were doing. The gear catalogs of the day told them a lot about what they needed to know - per the text: if you’re making something that needs gears, pick your gears from the catalog but just avoid the largest and smallest of each family/table - they are there because the next size up or down is getting into some kind of problems engineering wise, so just stay away from the edges and you should have much more reliable results. That’s an engineer’s shortcut for how to use thousands, maybe millions, of man-years of prior gear research, development and engineering and get the desired results just by referencing a catalog.


  • I think a lot depends on where “on the curve” you are working, too. If you’re out past the bleeding edge doing new stuff, ChatGPT is (obviously) going to be pretty useless. But, if you just want a particular method or tool that has been done (and published) many times before, yeah, it can help you find that pretty quickly.

    I remember doing my Masters’ thesis in 1989, it took me months of research and journals delivered via inter-library loan before I found mention of other projects doing essentially what I was doing. With today’s research landscape that multi-month delay should be compressed to a couple of hours, frequently less.

    If you haven’t read Melancholy Elephants, it’s a great reference point for what we’re getting into with modern access to everything:

    https://www.spiderrobinson.com/melancholyelephants.html



  • AI search is occasionally faster and easier than slogging through the source material that the AI was trained on. The source material for programming is pretty weak itself, so there’s an issue.

    I think AI has a lot of untapped potential, and it’s going to be a VERY long time before people who don’t know how to ask it for what they want will be able to communicate what they want to an AI.

    A lot of programming today gets value from the programmers guessing (correctly) what their employers really want, while ignoring the asks that are impractical / counterproductive.