Jürgen Schmidhuber is recipient of the 2016 IEEE CIS Neural Networks Pioneer Award, for "pioneering contributions to deep learning and neural networks."

The list of all awardees since 1991 can be found here.

The award ceremony took place on the 27th of July 2016 in Vancouver at the Award Banquet of IJCNN 2016.

Transcript of the 3 min acceptance speech:

Dear IEEE,

it is a great honor to be listed among previous awardees such as K. Fukushima, who is present at this conference, the father of the deep convolutional neural architecture everybody is using now for computer vision.

The only thing that makes me a bit sad at this otherwise happy moment is that the Ukrainian mathematician A. G. Ivakhnenko, the father of deep learning himself, never got this award. His team had deep multilayer perceptrons with 8 layers or so back in the 1960s when I was a baby, at a time when others still focused on the limitations of shallow nets with a single layer. Apparently he was so far ahead of his time that even the not so young members of the award committees failed to appreciate the depth of his work.

So what was it that we did that Ivakhnenko's team hadn't already done decades ago? Essentially, we figured out ways of making deep learning neural networks (NNs) much deeper and more powerful, with not only ten or so but hundreds or thousands of subsequent computational stages, first in the early 1990s with recurrent NNs (RNNs), the most general and deepest NNs which can run arbitrary algorithms, then with feedforward NNs in the 2000s.

In hindsight it is funny that for a long time, even well-known NN experts here in North America and other places did not realize the power of the very deep and recurrent NNs developed in our little pre-Alpine labs since the early 1990s. They have come around though. So has industry. Today we are proud that the world's most valuable public companies are heavily using our NNs and RNNs for speech and vision and many other applications.

Of course, all of this would not have been possible without the wonderful and brilliant PhD students and postdocs I had the pleasure to advise and work with. I am gladly accepting this award on behalf of the entire team.
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