<p>Neural networks can arbitrarily approximate any computable function; see
<a href="http://en.wikipedia.org/wiki/Artificial_neural_network" rel="nofollow">http://en.wikipedia.org/wiki/Artificial_neural_network</a>
or
<a href="http://en.wikipedia.org/wiki/Cybenko_theorem" rel="nofollow">http://en.wikipedia.org/wiki/Cybenko_theorem</a></p>

<p>Constructing a NN for a given function -- or worse yet, learning it from examples -- is a hard problem.</p>

CC BY-SA 3.0
2014-08-08T16:56:32.793Z
2014-08-08T16:56:32.793Z
Aryeh
<p>RNN Turing Completeness is proven by Siegelmann while back(search for 'On the Computational Power of Neural Nets'). If you are question is to ask whether NN based computer can be TC, the answer is yes. </p>

CC BY-SA 3.0
2016-07-04T09:22:53.067Z
2016-07-04T09:22:53.067Z
user40673
<p>MIT Review recently published this article about a chip from IBM, which is more or less a Artificial neural network. <a href="http://www.technologyreview.com/news/529691/ibm-chip-processes-data-similar-to-the-way-your-brain-does/?utm_campaign=socialsync&amp;utm_medium=social-post&amp;utm_source=facebook" rel="nofollow">Why IBM’s New Brainlike Chip May Be “Historic” | MIT Technology Review</a></p>

<p>The article suggests that the chip might have borrowed a page from the future. It might be the beginning of an era of new and evolved computation power. And also talks about programming for the chip. </p>

<blockquote>
  <p>One downside is that IBM’s chip requires an entirely new approach to
  programming. Although the company announced a suite of tools geared
  toward writing code for its forthcoming chip last year (see “IBM
  Scientists Show Blueprints for Brainlike Computing”), even the best
  programmers find learning to work with the chip bruising, says Modha:
  “It’s almost always a frustrating experience.” His team is working to
  create a library of ready-made blocks of code to make the process
  easier.</p>
</blockquote>

<p>Which brings me to the question, can everyday computing tasks be broken down into ones solvable by a neural network (theoretically and/or practically)?</p>

<ne.neural-evol>
Theoretically, can everyday computing tasks be broken down into ones solvable by a neural network?
tmj
# Theoretically, can everyday computing tasks be broken down into ones solvable by a neural network?

(Asked by: username_0 on 2014-08-08)

MIT Review recently published this article about a chip from IBM, which is more or less a Artificial neural network. [Why IBM’s New Brainlike Chip May Be “Historic” | MIT Technology Review](http://www.technologyreview.com/news/529691/ibm-chip-processes-data-similar-to-the-way-your-brain-does/?utm_campaign=socialsync&utm_medium=social-post&utm_source=facebook)

The article suggests that the chip might have borrowed a page from the future. It might be the beginning of an era of new and evolved computation power. And also talks about programming for the chip.

> One downside is that IBM’s chip requires an entirely new approach to
> programming. Although the company announced a suite of tools geared
> toward writing code for its forthcoming chip last year (see “IBM
> Scientists Show Blueprints for Brainlike Computing”), even the best
> programmers find learning to work with the chip bruising, says Modha:
> “It’s almost always a frustrating experience.” His team is working to
> create a library of ready-made blocks of code to make the process
> easier.

Which brings me to the question, can everyday computing tasks be broken down into ones solvable by a neural network (theoretically and/or practically)?

**Tags:** ne.neural-evol

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## 2 answers

### Answer by username_1 on 2014-08-08. Score: 2 | Accepted answer

Neural networks can arbitrarily approximate any computable function; see
<http://en.wikipedia.org/wiki/Artificial_neural_network>
or
<http://en.wikipedia.org/wiki/Cybenko_theorem>

Constructing a NN for a given function -- or worse yet, learning it from examples -- is a hard problem.


---

### Answer by username_2 on 2016-07-04. Score: 0

RNN Turing Completeness is proven by Siegelmann while back(search for 'On the Computational Power of Neural Nets'). If you are question is to ask whether NN based computer can be TC, the answer is yes.


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