32 ms·
I don't know if I'd agree that unsupervised learning is the "cake" here, to paraphrase Yann LeCun. How do we know that the human brain is an unsupervised learn
by fallingfrog 11y ago
I don't know if I'd agree that unsupervised learning is the "cake" here, to paraphrase Yann LeCun. How do we know that the human brain is an unsupervised learner? The supervisor in our brains comes in the form of the dopamine feedback loop, and exactly what kinds of things it rewards aren't totally mapped out but pleasure and novelty seem to be high on the list. That counts as a "supervisor" from a machine learning point of view. It's not necessary to anthropomorphize the supervisor into some kind of external boss figure; any kind of value function will do the trick.
- emodendroket 11y agoWell, a really interesting AI could tell us things about questions where we don't even know where to start, rather than needing to be primed with tons of data.
- stormbuilder 11y agoWouldn't that be a self-supervised learning? Yes, as the brain lears, it gets rewarded or not, but not by any external organism - rather by itself (or a part of itself). The "learning instruction manual" is in there somewhere. So if you are able to code an AI so that it can run experiments over itself and gradually build this "learning instruction manual" eventually it will become able to do things you never though of in the first place.
- fallingfrog 11y agoI think that's what the AlphaGo team did - they trained their agent against itself, and it learned new moves not explicitly programmed in! With an evaluation function just saying ahead / not ahead.
- astazangasta 11y agoThat IS unsupervised learning - you are maximizing an optimization function, you are not training using a set of "truth" values.
- fallingfrog 11y agoHmm, I don't think so. From wikipedia: "Unsupervised learning is the machine learning task of inferring a function to describe hidden structure from unlabeled data. Since the examples given to the learner are unlabeled, there is no error or reward signal to evaluate a potential solution." (emphasis mine)
- astazangasta 11y agoYes, "unlabeled" means that the examples are not marked as "true" or "false", and the "inferring" you are doing is making your function fit the data (e.g. minimizing some error term). Life doesn't come with pre-packaged answers; humans use unsupervised learning.
- fallingfrog 11y agoRight, but we do have a reward function that says pleasurable/painful and novel/boring and probably other stuff too. So that can be viewed as a labeling on the data. Earlier data can be associated with the reward labeling through induction; that's how a recurrent neural net works. Doubtless that's an oversimplification though.