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Facebook has a neural network that can do advanced math
- plutonorm 7y agoQuick, someone stick the navier-stokes equations in.
- perl4ever 7y agoI'd rather see if it can infer anything about the input from a SHA-256 hash.
- abc_lisper 7y agoWhat about the confidence in the result? Math is never done willy nilly, and without the ability to show how it is done, this will go no where. That said, this is a exciting result
- colejohnson66 7y agoThat reminds me of a joke that goes something like this: > Me: What is 2+2? > AI: It’s 42. > Me: Wrong, it’s 4. What’s 2+3? > AI: It’s 4.
- julienreszka 7y agoCan someone explain me the joke
- ct0 7y agoThe ai was trained that the answer is 4, so the second time around it went with 4.
- colejohnson66 7y agoAI (or more accurately, machine learning (ML)) learns by being told when it’s wrong and right (like a child). The AI makes a mistake on what 2+2 is, so it’s corrected. However, when it’s asked 2+3, it doesn’t know that 3 is one more than 2, and the only answer it’s learned is 4, so it says 4.
- perl4ever 7y agoAs is well known, a child learning language will often initially assume that rules/patterns are more regular that they actually are.
- Someone 7y agoIn general, differentiating a function is a lot easier than integrating one. Because functions can be written in multiple ways (simple example: ‘x+1’ vs ‘1+x’. For harder examples, see for example https://en.wikipedia.org/wiki/List_of_trigonometric_identities https://en.wikipedia.org/wiki/List_of_trigonometric_identiti...), it may still be difficult to prove that the derivative of a proposed integral of some function f is equal to f, but most of the time, checking a proposed solution to ".
- forgotpwd16 7y agoIs there anything machine learning is bad for?
- serf 7y agounique or novel untrained situations. that said ,we're not great at those, either. (untrained meaning that the dataset is a poor match with regards to the expected outcome)
- savanaly 7y agoUn-differentiable output. Take, for instance, writing a program. Change the input by the smallest possible amount, one character, and generally the output changes by a rather large amount (it could, say, go from working to failing to compile). Rarely would changing one character get us X% closer to a solution, or produce a change in a working solution that is X% faster.
- mturmon 7y agoOTOH, the example in the OP has somewhat the flavor of the hard problem you just sketched. The tree-based (RPN-esque) notation itself gets around much of the "perturbed program fails to compile" problem.
- zepto 7y agoemployment
- deleted 7y ago[deleted]
- siegelzero 7y agoThis paper was posted earlier with Anonymous authors: https://news.ycombinator.com/item?id=21084748 https://news.ycombinator.com/item?id=21084748
- shmageggy 7y ago> Other neural nets haven’t progressed beyond simple addition and multiplication, but this one calculates integrals and solves differential equations. And this one can't solve addition or multiplication. Turns out they are different problem spaces that require different approaches.
- Havoc 7y agoHeadline reminds me of cold war era "the Soviets have a x that can do y"