A Neural Turing machine (NTM) is a
recurrent neural network
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic ...
model of a
Turing machine
A Turing machine is a mathematical model of computation describing an abstract machine that manipulates symbols on a strip of tape according to a table of rules. Despite the model's simplicity, it is capable of implementing any computer algori ...
. The approach was published by
Alex Graves
Alexander John Graves (born July 23, 1965) is an American film director, television director, television producer and screenwriter.
Early life
Alex Graves was born in Kansas City, Missouri. His father, William Graves, was a reporter for ''Th ...
et al. in 2014.
NTMs combine the fuzzy
pattern matching
In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact: "either it will or will not be ...
capabilities of
neural networks with the
algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...
ic power of
programmable computers.
An NTM has a neural network controller coupled to
external memory resources, which it interacts with through attentional mechanisms. The memory interactions are differentiable end-to-end, making it possible to optimize them using
gradient descent
In mathematics, gradient descent (also often called steepest descent) is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. The idea is to take repeated steps in the opposite direction of the ...
.
An NTM with a
long short-term memory
Long short-term memory (LSTM) is an artificial neural network used in the fields of artificial intelligence and deep learning. Unlike standard feedforward neural networks, LSTM has feedback connections. Such a recurrent neural network (RNN) ...
(LSTM) network controller can infer simple algorithms such as copying, sorting, and associative recall from examples alone.
The authors of the original NTM paper did not publish their
source code
In computing, source code, or simply code, is any collection of code, with or without comments, written using a human-readable programming language, usually as plain text. The source code of a program is specially designed to facilitate the w ...
.
The first stable open-source implementation was published in 2018 at the 27th International Conference on Artificial Neural Networks, receiving a best-paper award. Other open source implementations of NTMs exist but as of 2018 they are not sufficiently stable for production use.
The developers either report that the
gradients
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the grad ...
of their implementation sometimes become
NaN
Nan or NAN may refer to:
Places China
* Nan County, Yiyang, Hunan, China
* Nan Commandery, historical commandery in Hubei, China
Thailand
* Nan Province
** Nan, Thailand, the administrative capital of Nan Province
* Nan River
People Given name
...
during training for unknown reasons and cause training to fail;
report slow convergence;
or do not report the speed of learning of their implementation.
s are an outgrowth of Neural Turing machines, with
attention mechanisms that control where the memory is active, and improve performance.
References
{{Differentiable computing
Neural network architectures