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Comment by Perseids

I'm of two minds about this. On the one hand, you get miraculous results with AI, and that is what you are referring to with "be able to {my-field}". On the other hand you regularly get useless, if not toxic, crap out of the miracle machine. If you work with AI, you know these moments: "no that is not what I meant at all!" [1] or "how could you have already forgotten the central motivation I laid out just ten back-and-forths ago?". We're calling this the jagged frontier, but the jaggedness itself is not the problem, it's how deep these cuts go into aspects that are important. These are, why AI is still not "obviously superior" in its abilities, can't replace mathematicians and software developers and lawyers and everyone else who is primarily working with text. (It's also why people say it is ruining their fields, instead of replacing them in their fields, because it only replaces some part of the work, and what's left is not tenable or pleasant (e.g. doing reviews all the time).)

Over all, I'm not quite sure whether I see these deep cuts occurring less and less with progressing AI. It might just be, that I'm giving them progressively harder tasks as well. But the fact of the matter still is that they aren't there yet and it needs proof they will get there ("there" being able to do competent work that is not strongly limited in their scale by human review and correction). So I'm still not convinced about the point you want to make, even though I see AI disrupting about every part of society, and am hoping for the benevolent super AI to lead us to utopia (and afraid of the cliff of human dictatorship on one side and extinction on the other).

[1] I've started to use these moment to reflect on whether a human in a comparable situation would fare better. Having only a few text inputs and small glimpses into a code base and knowing next to nothing about you or your project personally. Quite a few times I've concluded: No, they would not. But more than 50% they would, and also, these limitations are technological limitations of LLM, so you should probably not excuse them for that.

parent Perseids 13 days ago

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