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by brutusborn
1202 days ago
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I mixed up my terms. (I think) supervised learning refers to the use of labelled datasets, I meant fine-tuning (like in RLHF). In either case human input is necessary (and the humans definitely need to know what they want). In terms of generating novel ideas, I think chatGPT has shown this ability [0]. Human effort will be needed to sort the "good" ideas from the "bad", but I don't think this causes the value of the model to be "negated." If you want to understand gradient descent and have some math background, this [1] article is a good explainer. [0] https://forum.effectivealtruism.org/posts/63pYakESGrQpfNw25/...
[1] https://towardsdatascience.com/gradient-descent-algorithm-a-... |
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It’s like a weird parrot. But I think a parrot “understands” more because of the shared embedded evolutionary context it has.
That evolutionary history has the key to true intelligence somewhere, but personally I think it’s inevitably hidden/I don’t think we’ll ever understand how intuition and truly non-derivative, non propositional human thought works.
I also don’t think any of what I’m saying negates the value of these models. These models are fantastic autofill generators for a huge swath of different applications and can vastly improve productivity. I’m saying all this in a lot of threads where it comes up because it seems clear there’s going to be too much enthusiastic adoption, which is going to effectively destroy a lot of value of the internet.
The internet is the best tool for finding genuinely creative and novel ideas you were unexposed to that has ever existed. But it is increasingly dominated by derivative unoriginal content that drowns out what I would argue it was designed to help you find. I have no problem with derivative unoriginal content when it’s properly understood as such. I have a problem with how good these things seem to be at tricking people into following something derivative and blind, which seems very very dangerous.