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This isn't how you encourage people to use their abilities to contribute to society in a positive way.
as a non-specialist, it seems like several important and distinct areas of inquiry are just lumped together in the celebration of a "winner" for ML Text, language, human chat Image recognition from blurry, multiple views, multiple lighting conditions photos formal patterns with large numbers of variations These are not at all the same, yet the praise seems to want to declare "the best" and "beating competitors" .. wh…
I think Schmidhuber should be up there. LSTMs are everywhere, not just NLP. The latest Starcraft 2 bot from Deepmind uses LSTMs extensively in its architecture.
Schmidhuber's significance in the field is not at the same level. He invented one type of neural network, but the "Canadian mafia" launched the whole Deep Learning revolution with multiple breakthroughs and theoretical understanding. LSTM's are clever and they were bleeding edge up to 2014, but once they were understood better as a bypass mechanism, attention, context vectors and averaging networks and causal convolu…
As far as I'm aware, causal convolutions were used in WaveNet (and subsequent models) and a small number of NLP applications. Meanwhile, LSTM-based models are used in just about every NLP paper, and at least a baseline in the newer ones more dominated by Transformers.
how much is changed since those geniuses started to work in this particular field? Me coming from web full-stack dev and see how things change fast and I find myself jumping from A way to B way very quick these days. I just need to know your perception of how fast thing goes and changes on ML.
It's pretty much the same in ML. These people built the building blocks that we still use in ML everyday (e.g. backpropagation, ConvNets etc). But the fine-tuning, packaging and tooling of these techniques also changes all the time and it can be hard to keep up. Having moved from full-stack web to ML I have a similar feeling about the pace of things.
It saddens me to see these people being given awards for improving the surveillance and manipulation capabilities of advertising corporations. This isn't how you encourage people to use their abilities to contribute to society in a positive way.
Earlier quoted context omitted.
Schmidhuber's significance in the field is not at the same level. He invented one type of neural network, but the "Canadian mafia" launched the whole Deep Learning revolution with multiple breakthroughs and theoretical understanding. LSTM's are clever and they were bleeding edge up to 2014, but once they were understood better as a bypass mechanism, attention, context vectors and averaging networks and causal convolu…
Ironically Schmidhuber's lab also came up with a more general version of bypassing http://arxiv.org/abs/1505.00387 to train deep networks (with similar performance), of which the popular ResNet is a special case.
It saddens me to see these people being given awards for improving the surveillance and manipulation capabilities of advertising corporations. This isn't how you encourage people to use their abilities to contribute to society in a positive way.
Then you must be sad when the Internet was invented as well ? How about cars ?
Also, my comment was about people being given awards, not people inventing things.
I think Schmidhuber should be up there. LSTMs are everywhere, not just NLP. The latest Starcraft 2 bot from Deepmind uses LSTMs extensively in its architecture.
Hinton/Lecun pioneered early BP research, which is significant and fundamental. Bengio has attention mechanism/GAN, and in early days greedy layer wise pretraining for RBM (which isn't something end up today, but pertaining is a thing back in pre 2010 era).
Not saying LSTM isn't significant, but his achievements aren't quite there with those 3, looking closer.
Earlier quoted context omitted.
Schmidhuber's significance in the field is not at the same level. He invented one type of neural network, but the "Canadian mafia" launched the whole Deep Learning revolution with multiple breakthroughs and theoretical understanding. LSTM's are clever and they were bleeding edge up to 2014, but once they were understood better as a bypass mechanism, attention, context vectors and averaging networks and causal convolu…
Schmidhuber did way more than LSTMs. And they still are SOTA on many tasks. You clearly are not very familiar with the field.
When you put researchers or groups into order of importance, the work from this trio comes before others, including Schmidhuber. The Turing Award is given to those at the top and it's not inclusive.
If I could give Turing Award for someone in the field who has not received it yet, I would give it to Vladimir Vapnik.
I think Schmidhuber should be up there. LSTMs are everywhere, not just NLP. The latest Starcraft 2 bot from Deepmind uses LSTMs extensively in its architecture.
Yes seems political to snub him, but then ACM is an American association.
http://people.idsia.ch/~juergen/deep-learning-conspiracy.htm...
Note for people put off by the link: The conspiracy refers to the title of a paper by the Turing award winners, not Schmidhuber's.