Neural Turing Machine - Revision history

BPeat at 03:40, 2 March 2024

2024-03-02T03:40:40Z

BPeat at 14:59, 3 February 2019

2019-02-03T14:59:51Z

BPeat at 03:14, 13 May 2018

2018-05-13T03:14:47Z

BPeat: Created page with "=== Neural Turing Machine (NTM) === [http://www.youtube.com/results?search_query=Explainable+Artificial+Intelligence+tutorial Youtube search...] * [http://www.asimovinstitute..."

2018-05-13T02:09:48Z

Created page with "=== Neural Turing Machine (NTM) === [http://www.youtube.com/results?search_query=Explainable+Artificial+Intelligence+tutorial Youtube search...] * [http://www.asimovinstitute..."

New page

=== Neural Turing Machine (NTM) ===
[http://www.youtube.com/results?search_query=Explainable+Artificial+Intelligence+tutorial Youtube search...]

* [http://www.asimovinstitute.org/author/fjodorvanveen/ Neural Network Zoo | Fjodor Van Veen]

An abstraction of LSTMs and an attempt to un-black-box neural networks (and give us some insight in what is going on in there). Instead of coding a memory cell directly into a neuron, the memory is separated. It’s an attempt to combine the efficiency and permanency of regular digital storage and the efficiency and expressive power of neural networks. The idea is to have a content-addressable memory bank and a neural network that can read and write from it. The “Turing” in Neural Turing Machines comes from them being Turing complete: the ability to read and write and change state based on what it reads means it can represent anything a Universal Turing Machine can represent. Graves, Alex, Greg Wayne, and Ivo Danihelka. “Neural turing machines.” arXiv preprint arXiv:1410.5401 (2014).

<youtube>cc1G2F6VsjA</youtube>
<youtube>XwqWTX1pW4s</youtube>

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 * [http://www.asimovinstitute.org/author/fjodorvanveen/ Neural Network Zoo | Fjodor Van Veen]
-An abstraction of LSTMs and an attempt to un-black-box neural networks (and give us some insight in what is going on in there). Instead of coding a memory cell directly into a neuron, the memory is separated. It’s an attempt to combine the efficiency and permanency of regular digital storage and the efficiency and expressive power of neural networks. The idea is to have a content-addressable memory bank and a neural network that can read and write from it. The “Turing” in Neural Turing Machines comes from them being Turing complete: the ability to read and write and change state based on what it reads means it can represent anything a Universal Turing Machine can represent.  Graves, Alex, Greg Wayne, and Ivo Danihelka. “Neural turing machines.” arXiv preprint arXiv:1410.5401 (2014).
+An abstraction of LSTMs and an attempt to un-black-box neural networks (and give us some insight in what is going on in there). Instead of coding a [[memory]] cell directly into a neuron, the [[memory]] is separated. It’s an attempt to combine the efficiency and permanency of regular digital storage and the efficiency and expressive power of neural networks. The idea is to have a content-addressable [[memory]] bank and a neural network that can read and write from it. The “Turing” in Neural Turing Machines comes from them being Turing complete: the ability to read and write and change state based on what it reads means it can represent anything a Universal Turing Machine can represent.  Graves, Alex, Greg Wayne, and Ivo Danihelka. “Neural turing machines.” arXiv preprint arXiv:1410.5401 (2014).
 http://www.asimovinstitute.org/wp-content/uploads/2016/09/ntm.png

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-=== Neural Turing Machine (NTM) ===
+{{#seo:
-[http://www.youtube.com/results?search_query=Explainable+Artificial+Intelligence+tutorial Youtube search...]
+|title=PRIMO.ai
 * [http://www.asimovinstitute.org/author/fjodorvanveen/ Neural Network Zoo | Fjodor Van Veen]

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 An abstraction of LSTMs and an attempt to un-black-box neural networks (and give us some insight in what is going on in there). Instead of coding a memory cell directly into a neuron, the memory is separated. It’s an attempt to combine the efficiency and permanency of regular digital storage and the efficiency and expressive power of neural networks. The idea is to have a content-addressable memory bank and a neural network that can read and write from it. The “Turing” in Neural Turing Machines comes from them being Turing complete: the ability to read and write and change state based on what it reads means it can represent anything a Universal Turing Machine can represent.  Graves, Alex, Greg Wayne, and Ivo Danihelka. “Neural turing machines.” arXiv preprint arXiv:1410.5401 (2014).
 <youtube>cc1G2F6VsjA</youtube>
 <youtube>XwqWTX1pW4s</youtube>