4 ms·

If you work at a computer, it will increase your productivity. Revolutionary is not the word I'd use, but finding use cases isn't hard.

• rsynnott 4y ago
  I can buy that it's a better/worse search engine (better in that it's easier to formulate a query and you get the response right there without having to parse the results; worse in that there's a decent chance the response is nonsense, and it's very confident when it's being wrong about things). I can't really imagine asking it a question about anything I cared about and not verifying via a second source, though, given its accuracy issues. This makes it feel a lot less useful.
• deleted 4y ago
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• EVa5I7bHFq9mnYK 4y ago
  But will it? After accounting for the time needed to fix all the bugs it introduces?
  • Timwi 4y ago
    Humans introduce bugs too. ChatGPT is still new, so it probably makes more mistakes than a human at the moment, but it's only a matter of time until someone creates the first language model that will measurably outperform humans in this regard (and several other important regards).
    • EVa5I7bHFq9mnYK 4y ago
      >> it's only a matter of time That reminds me how in my youth many were planning on vacations to Mars resorts and unlimited fusion energy) Stars looked so close, only a matter of time!
    • rsynnott 4y ago
      > it's only a matter of time until someone creates the first language model that will measurably outperform humans in this regard This seems to have been the rallying cry of AI-ish stuff for the past 30 years, tho. At a certain point you have to ask "but how much time"? Like, a lot of people were confidently predicting speech recognition as good as a human's from the 90s on, for instance. It's 2023, and the state of the art in speech recognition is a fair bit better than Dragon Dictate in the 90s, but you still wouldn't trust it for anything important. That's not to say AI is useless, but historically there's been a strong tendency to say, of AI-ish things "it's 95% of the way there, how hard could the last 5% be?" The answer appears to be "quite hard, actually", based on the last few decades. As this AI hype cycle ramps up, we're actually simultaneously in the down ramp of _another_ AI hype cycle; the 5% for self-driving cars is going _very slowly indeed_, and people seem to have largely accepted that, while still predicting that the 5% for generative language models will be easy. It's odd. (Though, also, I'm not convinced that it _is_ just a case of making a better ChatGPT; you could argue that if you want correct results, a generative language model just isn't the way to go at all, and that the future of these things mostly lies in being more convincingly wrong...)
      • EVa5I7bHFq9mnYK 4y ago
        Anyone still remembers the self-driving hype?
• rchaud 4y ago
  How will it do that? One of major problems of modern computer-based work is that there are too many people already in those roles, doing work that isn't needed. Case in point: the culling of tens of thousands of software engineers, people who would consider themselves to be doing 'bullshit jobs'.