Comment by jdiff
6 hours ago
I don't think the word "amplification" is accurate. I don't know why, but while engineering techbro circles love "multipliers," but those very very rarely exist in real life.
You do need a baseline of knowledge to be able to prompt the AI in a domain successfully. But beyond that baseline there are rapidly diminishing returns. Someone with skill far beyond a certain line won't get amplified the same way someone who just clears that line will.
This is patently false, see Tao’s recent use of ChatGPT regarding the Jacobian conjecture.
Depends on the context.
In this case he is right : https://news.ycombinator.com/item?id=49239999
Your quote shows someone BELOW the line being able to do something. That could not be considered amplification because multiplying a skill of 0 doesn’t get you anywhere. But if you want to see it that way, it doesn’t bother me.
The Tao reference is someone far ABOVE the line getting excellent results from the LLM.
So in this case the Tao example refutes the GGP claim.
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Kinda talking about pretty squishy things here, saying something is "patently false" in the context feels pretty stifling, or at least uncharitable.
Like, what, we are all supposed to close the book on this abstract, very new question. Something that by any approximation is extremely nuanced and also pretty meaningful? Like, "oh OK, well I guess that's that then!"
They are talking about breadth, not depth, multipliers in almost every circumstance.
A great X will be able to do far more great X stuff (breadth), and perhaps also be a greater X (depth).
But it's most certainly weighted in favor of the former than the latter.
What is the baseline, roughly? Let's say I want to be useful in a given domain(one with rich machine feedback), with the help of the AI, what should I study ?
AI security.
Ask the AI