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'Why' presupposes there is an answer that a human can understand. Why do self-driving cars work? Because there exists some function that maps raw inputs to outp
by natalyarostova 7y ago
'Why' presupposes there is an answer that a human can understand. Why do self-driving cars work? Because there exists some function that maps raw inputs to outputs that correctly interact with reality. Why? Because the neural network fit the right curves.
- Koshkin 7y agoI think Feynman’s was the best answer to the “why” question: https://www.lesswrong.com/posts/W9rJv26sxs4g2B9bL/transcript-richard-feynman-on-why-questions https://www.lesswrong.com/posts/W9rJv26sxs4g2B9bL/transcript....
- skybrian 7y agoI think that's different, first because the neural network has an indirect relationship with the physics, and second because Feynman was operating under a handicap: he was asked to give an explanation in terms the listener (who didn't know any physics) would understand. In the case of folding, when we ask "why" we might be asking why it folds one way and not the other. Causation has consequences, like for example we might want to know whether a small change to one part of the protein will significantly change how it folds. We might say some amino acids cause the fold and others don't. If you understand the mechanism behind something, you can control it better. Or, if you're interested in machine learning, you could ask what changes to the neural network make prediction better or worse and which parts of it matter the most, when it might make mistakes, and so on.
- ArnoVW 7y agoIt is true, we will never know in the ultimate detail how each weight of each neuron must be placed and why. But that is simply because it is too intricate to understand everything. Just like we try to understand human behaviour not by understanding individual neurons, we reason on an abstract level, called psychology. To take your example building a SDC will teach us which aspects are the most complex, and which solutions work better than other for those aspects. Comparing those solutions will allow us to see what working solutions have in common, and give us theories that we can then test.
- natalyarostova 7y agoThat's a fair response, but I don't think it's universal. Or at least I should say it presupposes all complex phenomena have a parsimonious abstraction layer a human brain can grok. Which, to be fair, does seem to hold true a surprising amount of the time. But I don't think it's required.
- commandlinefan 7y agoWell, you’re still not going to get to hand-wave away the “why” question. I’ve been working on recommender systems for the past 5 or so years, and I end up spending a lot of my time trying to work backwards to explain why the recommender recommended something that seemed counterintuitive (sometimes because of a bug, sometimes because of the model, sometimes for reasonable reasons). If you work on self driving cars, you’ll similarly be researching and explaining “why” this one drove into a lake this one time.
- natalyarostova 7y agoYeah that's a reasonable counter point to my example, you're right. I guess I used a poor example to try and make a more general point that there will and may already be a time when the black boxes we use exceed our ability to understand the causal mechanisms.
- jacquesm 7y ago> Why do self-driving cars work? Unless there has been some breakthrough that I'm not aware of this isn't true.
- MaulingMonkey 7y agoThey've worked conditionally for a long time now. It's not level 5 open world "works in all conditions" self-driving - but neither is it level 0 no automation whatsoever. Nor can humans drive unconditionally either.
- jacquesm 7y agoA three year old can 'conditionally' drive a car. That doesn't mean it works.