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Yeah, terms like "machine learning" and "AI" have basically become buzz words which, to most laymen, probably encourage the idea that we're on the cusp of creat
by charles-salvia 10y ago
Yeah, terms like "machine learning" and "AI" have basically become buzz words which, to most laymen, probably encourage the idea that we're on the cusp of creating Data from Star Trek.
Unfortunately, the reality is that.... sorry... it's mostly just statistical algorithms based around regression and intermediate calculus. State-of-the-art "deep" neural networks are not really anything like the absurdly parallel, asynchronous biological networks that power our neo-cortex - rather, they're basically an application of matrix multiplication designed to "learn" a function by iteratively minimizing an error value using gradient descent. It's still very unclear what, if anything, this algorithm has in common with how a human brain actually operates. It turns out that these kind of statistical algorithms can work pretty well when you have petabytes of data to learn from. But we're still not anywhere near the unsupervised learning capabilities demonstrated by a human infant.
- eli_gottlieb 10y ago> It's still very unclear what, if anything, this algorithm has in common with how a human brain actually operates. Not very much at all. Most psychological evidence shows that human beings seem to operate off composable, hierarchical generative models and probabilistic inference. Deep neural networks are basically just huge continuous circuit approximators.
- akyu 10y ago>composable, hierarchical generative models and probabilistic inference. Deep neural networks are basically just huge continuous circuit approximators. These two things are not mutually exclusive.
- eli_gottlieb 10y agoWhat sort of neural network implements human-style learning and inference?
- shahbaby 10y agonumenta's HTM
- uwiiuvvwu 10y agoyep, call function-fitting/optimization "learning" and it's suddenly a form of intelligence!
- prvnsmpth 10y agoWhat is human intelligence, if not the result of a colossal, distributed function optimisation process driven by evolutionary forces over millions of years?
- uwiiuvvwu 10y agotrue, it's the result of an optimization process, but intelligence itself (whatever it is...it's a suitcase-term) isn't as simple as that. Or maybe it is, I don't know!
- pekk 10y ago"Optimization" describes the result, not the implementation. Unless you consider intelligence to be average-suboptimal, it's entirely reasonable to say that it's about optimization without committing you to any claim about how intelligence is implemented.
- Twisell 10y agoThe fact that this pretty accurate comment (written in layman terms) is so downwoted tend to actually reinforce it's accuracy.
- tim333 10y agoThe unsupervised learning capabilities demonstrated by a human infant are a pretty lofty target. Give it time.
- zackchase 10y agoWhile I don't take exception with the word machine learning (it's reasonably well defined), I agree with most of the points here. Some are grossly exaggerated (e.g. needing petabytes of data to do machine learning). In my research on medical time series, we get strong results with a few thousand examples (megabytes). Same for natural language datasets which are modestly sized. But yes, absolutely agree that function approximation for supervised learning and some kind of artificial consciousness as portrayed in the media are very far apart.
- unprepare 10y agoLets say an infant is 3 years old, thats 26,280 hours, lets say a baby sleeps about 2/3 of the time - lets call it 8600 hours of awake time. 8600 hours of 4k video at 60fps (i would say this is lower quality then the human eye) is 2.657 petabytes. Thats not including the sense of touch or smell, which i am sure are comparable in the amount of data processed by a human. We're looking at 5+ petabytes of data that a human has to learn from by age 3 - Whats wrong with taking petabytes of data in order to learn meaningful things?