this post was submitted on 11 Feb 2024
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That's not really an accurate take of how machine learning typically works. Neural Networks (allegedly) learn in a way similar to how humans do, taking the data they are fed and building a weighted matrix of resolutions that seems most compatible. A historically interesting trait is that neural networks are often better pattern-discoverers than humans.
But note, the outcome of a neural network is NOT a "random combination of the information we feed them">
I feel like this is a hard question to answer since it is based off controversial takes about ML. I am not a brain-is-a-computer hypothesis adherent, but we're talking about specific learning mechanisms that are absolutely comparable to human learning. Is "the learning humans do" enough to replace "the learning humans do"? I would say obviously yes.
The implementation details of how they represent their information doesn't really matter.
It isn't random, it's selected (or "weighted", if you wanna be more precise, yes)
And don't confuse things. We're talking about intelligence here. Not learning. Learning can be done without intelligence (that's how insects can learn behavior) and intelligence can be done without learning.
My question was uniquely about information generation (since the validation part is fully rational, and can be very efficiently done by a machine).
Are we? Alright. Can you describe a definition test for intelligence that we could agree upon that humans pass and no NN or other ML is capable of passing? I suspect you're confusing things. Not an
intelligence,learningcomparison, but anintelligence,consciousnessconfusion.