[jacknews]

Surely the roots, if we skip over the early preceptron work', are in backpropagation and Hinton, and the work going on at Edinburgh and elsewhere in the 80s.

Indeed I remember buying a set of three conference-papers-as-books around that time, titled Artificial Neural Networks .. proceedings of the whatever the conference was.

No doubt Schmidhuber made important contributions, but I see him pop up claiming to be the 'root' of it all every couple of years.

[h8hawk]

Hinton did not invent backpropagation.

related paragraph from Wikipedia:

Modern backpropagation was first published by Seppo Linnainmaa as "reverse mode of automatic differentiation" (1970)[26] for discrete connected networks of nested differentiable functions.[27][28][29]

In 1982, Paul Werbos applied backpropagation to MLPs in the way that has become standard.

[ogrisel]

Paul Werbos did not apply backprop to MLPs as cleanly described in Hinton's paper, but rather to some kind of autoregressive non-linear parametrized functions with a much more specific application scope.

Both papers are direct applications of the chain rule applied to estimate the gradient of a multivariate function.

[hyttioaoa]

That's what bugs me about him. So much work has gone into today's models that calling his contributions "the root" isn't really warranted. He's always complaining that Hinton, LeCun, and Bengio get more credit than they deserve, and now he's over-claiming himself.

[BoredPositron]

Both can be right.

[emil-lp]

Surely the roots go back to Turing, Gödel, Hilbert, Frege, Leibniz, Aristoteles.