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OP never said that serious downsides = perform terribly, he said that in situations where the consequences are severe you don’t want to use LLMs. > Most unfixa

OP never said that serious downsides = perform terribly, he said that in situations where the consequences are severe you don’t want to use LLMs. > Most unfixable flaws can be worked around with enough effort and skill. Such a ridiculous example of delusional LLM hype, comments like this are downright offensive to me. “Your therapy bot is telling vulnerable people to kill themselves, they probably should have applied more skill and effort to being in therapy”

Dylan16807 1y ago
> Such a ridiculous example of delusional LLM hype, comments like this are downright offensive to me. Sorry you got offended at a thing I didn't say. That was a generic comment about designers/engineers/experts, not untrained users. Also you swapping "can be" with "should" strongly changes the meaning all by itself. Very often you can force a design to work but you should not.
- subjectsigma 1y ago
  I have no idea how you think “ they probably could have” sounds any better, or how it makes your argument stronger at all. If we can apply AI to these situations but shouldn’t, why even bother with your first comments?
  - Dylan16807 1y ago
    > I have no idea how you think “they probably could have” sounds any better, or how it makes your argument stronger at all. When I talk about "can" I'm talking about in the medium future or further, not what anyone is using or developing right now. It's "can someday" not "could have". > If we can apply AI to these situations but shouldn’t, why even bother with your first comments? Because I dislike it when people conflate "this technology has flaws that make it hard to apply to x task" with "it is impossible for this category of technology to ever be useful at x task" And to be clear, I'm not saying "should" but I'm not saying "shouldn't" either, when it comes to unknown future versions of LLM technology. I'll make that decision later. The point is that the range of "can" is much wider than the range of "should", so when someone says "can't" about all future versions of a technology they need extra strong evidence.

Dylan16807 1y ago

> Such a ridiculous example of delusional LLM hype, comments like this are downright offensive to me. Sorry you got offended at a thing I didn't say. That was a generic comment about designers/engineers/experts, not untrained users. Also you swapping "can be" with "should" strongly changes the meaning all by itself. Very often you can force a design to work but you should not.

subjectsigma 1y ago
I have no idea how you think “ they probably could have” sounds any better, or how it makes your argument stronger at all. If we can apply AI to these situations but shouldn’t, why even bother with your first comments?
- Dylan16807 1y ago
  > I have no idea how you think “they probably could have” sounds any better, or how it makes your argument stronger at all. When I talk about "can" I'm talking about in the medium future or further, not what anyone is using or developing right now. It's "can someday" not "could have". > If we can apply AI to these situations but shouldn’t, why even bother with your first comments? Because I dislike it when people conflate "this technology has flaws that make it hard to apply to x task" with "it is impossible for this category of technology to ever be useful at x task" And to be clear, I'm not saying "should" but I'm not saying "shouldn't" either, when it comes to unknown future versions of LLM technology. I'll make that decision later. The point is that the range of "can" is much wider than the range of "should", so when someone says "can't" about all future versions of a technology they need extra strong evidence.