It may or may not be smoke and mirrors, but there's a clear structure to the essay, as well as a logical structure to the arguments in the essay. For example, "humans think they're intelligent", "humans are wrong about everything", and therefore "intelligence isn't about being right".
It even concludes with reasonably good advice: to pass a Turing test, AIs should say things that are true, and tap into human emotions. To me, this disproves the idea that it's "not saying anything". It's definitely saying something, and that something is both true and not commonly understood by the general public. It is therefore capable of "teaching a basic skill".
I find that very impressive, and I'm surprised that so many others here don't.
As I stated elsewhere, the essay is almost certainly constructed by the human writing the article, out of cherry-picked output by GPT-3 stitched together (I'm guessing at the paragraph level).
Also, again almost certainly, the information about what it takes to pass the Turing test is taken from some text in the corpus it was trained on. What GPT-3 did do is recognize that that is relevant to the topic of AI vs human intelligence, but not much more.
Comments
It may or may not be smoke and mirrors, but there's a clear structure to the essay, as well as a logical structure to the arguments in the essay. For example, "humans think they're intelligent", "humans are wrong about everything", and therefore "intelligence isn't about being right".
It even concludes with reasonably good advice: to pass a Turing test, AIs should say things that are true, and tap into human emotions. To me, this disproves the idea that it's "not saying anything". It's definitely saying something, and that something is both true and not commonly understood by the general public. It is therefore capable of "teaching a basic skill".
I find that very impressive, and I'm surprised that so many others here don't.
As I stated elsewhere, the essay is almost certainly constructed by the human writing the article, out of cherry-picked output by GPT-3 stitched together (I'm guessing at the paragraph level).
Also, again almost certainly, the information about what it takes to pass the Turing test is taken from some text in the corpus it was trained on. What GPT-3 did do is recognize that that is relevant to the topic of AI vs human intelligence, but not much more.