Munich 1991: The Roots of the Current AI Boom
190 points - last Friday at 3:54 PM
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More specifically, it was really AlexNet, the 2012 ImageNet entry, running on two NVIDIA GTX 580's, that highlighted the practicality and utility of running large scale neural nets on affordable hardware. CUDA had been released in 2006, but cuDNN (the CUDA library for neural nets) didn't come out until 2014 - after AlexNet had already kickstarted the demand.
What followed from AlexNet was a few years of intense competition on the ImageNet benchmark, and larger and larger/deeper neural nets (CNNs), which gave rise to a lot of the algorithms and concepts still used today such as residual connections (originally from ResNet), ADAM (training algorithm), ReLU/etc, normalization, dropout, etc... all the fundamentals that made building large neural nets possible.
Schmidhuber's continual reminding everyone that he was working on neural nets back in the 1990s is beyond tiresome. Yes, he should have been recognized alongside Hinton/Bengio/LeCun as one of the pioneers, but time for him to get over it.
And while it is very true that often the research coming out of Academia is useless, what is always neglected are the roots of the research done in private labs.
When JĂĽrgen Schmidhuber and team published their work on Neural Nets back in 1991 it was also useless. Unless you had a supercomputer and very, very deep pockets you were not going to do anything with what came out of their lab.
But still, 30 years later here we are, standing on top of the shoulders of this useless research.
Yes is very easy to forget, cause the trillion is not being made in Europe. If it was really conceived in Munich (like the maps that got stolen also), it show how incompetent is Europe to keep it´s technology and protect European companies.
It is painful to read this article.
In the Schmidhuber case their is 20 years and a chain of countless other works in between the two.
The real root of the current AI boom is a master thesis from university of Toronto.
The thesis demonstrated that neural networks much longer than before could be trained by simply having a random fraction of the neurons excluded during forward and back propagation.
That's how we got practical deep neural networks. Without that we would still be in AI winter.
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.
It's nauseating how all the researchers who happened to work for big tech got tons of media coverage but Schmidhuber and his team were getting zero coverage yet they made massive contributions. I bet there are many others not mentioned.
Nobody even knows about Frank Rosenblatt. It's insane how distorted our perception of innovation is.
Even science has been corrupted. It makes one doubt every story we're told about who invented what.