
Facebook has a neural network that can do advanced math - lelf
https://www.technologyreview.com/s/614929/facebook-has-a-neural-network-that-can-do-advanced-math/
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abc_lisper
What 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

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colejohnson66
That 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.

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julienreszka
Can someone explain me the joke

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colejohnson66
AI (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.

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perl4ever
As is well known, a child learning language will often initially assume that
rules/patterns are more regular that they actually are.

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siegelzero
This paper was posted earlier with Anonymous authors:
[https://news.ycombinator.com/item?id=21084748](https://news.ycombinator.com/item?id=21084748)

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Havoc
Headline reminds me of cold war era "the Soviets have a x that can do y"

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shmageggy
> _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.

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plutonorm
Quick, someone stick the navier-stokes equations in.

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perl4ever
I'd rather see if it can infer anything about the input from a SHA-256 hash.

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forgotpwd16
Is there anything machine learning is bad for?

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savanaly
Un-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.

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mturmon
OTOH, 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.

