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I don't know the history of it and am not an expert in the field, but it seems to me that it's valid to call the things ML can already do "intelligence" in a ge
by wilg 7y ago
I don't know the history of it and am not an expert in the field, but it seems to me that it's valid to call the things ML can already do "intelligence" in a generalized sense, and that there is nothing categorically different between that and human intelligence, it's just a matter of how complicated humans are.
That seems like a problem you can sort of throw hardware at for a while until it gets good enough to help you figure out how to make something smarter.
- jsinai 7y agoI think there is little evidence to suggest that neural networks and human minds behave in the same way modulo complexity. In science there is a tendency to come up with models of the world - simplifications which we can observe and quantify - and then fall into the trap thinking that these models explain the world. While neural networks are inspired by biological neural connections between synapses and neurons, the converse that neural networks are therefor intelligent does not hold.
- wilg 7y agoI'm not suggesting NNs should be considered intelligent because of their inspiration from biology. Just that they should be considered intelligent because of what they are currently capable of (though that is way less intelligent than humans or animals of course). But it seems like there is a plausible path to increasing their "intelligence" by dumping more data and hardware at them. Like GPT2 shows quite a surprising amount of structural complexity even though it's very dumb in other ways – it feels like if you could pump a million times more data into it you'd get something that seemed really quite intelligent.