Uploaded November 2020 | Updated September 2026, 1 week ago
AI specialist Jürgen Schmidhuber on the first deep networks, backpropagation and whether you can train a network without unsupervised pre-training.
Read the full text on our website: serious-science.org/deep-feedforward-neural-networks-10374
'The convolutional neural network architecture was introduced by Fukushima in 1979: he called it the neocognitron. It was inspired by neurophysiological insights of Hubel and Wiesel, and today such architectures are widely used for computer vision.'
Jürgen Schmidhuber, Scientific Director, Swiss AI Lab IDSIA
Neural Networks: serious-science.org/neural-networks-9479
Deep Learning: serious-science.org/deep-learning-10364
This lecture is part of the collaboration between Serious Science and the Technology Contests Up Great READ//ABLE: https://en.ai.upgreat.one/
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AI specialist Jürgen Schmidhuber on the first deep networks, backpropagation and whether you can train a network without unsupervised pre-training.
Read the full text on our website: serious-science.org/deep-feedforward-neural-networks-10374
'The convolutional neural network architecture was introduced by Fukushima in 1979: he called it the neocognitron. It was inspired by neurophysiological insights of Hubel and Wiesel, and today such architectures are widely used for computer vision.'
Jürgen Schmidhuber, Scientific Director, Swiss AI Lab IDSIA
Neural Networks: serious-science.org/neural-networks-9479
Deep Learning: serious-science.org/deep-learning-10364
This lecture is part of the collaboration between Serious Science and the Technology Contests Up Great READ//ABLE: https://en.ai.upgreat.one/
Be the first to find out about our new videos and articles. Learn interesting facts about various topics and people. Discover the answers to the big questions. Be in the know.
serious-science.org
Follow us:
We are on Patreon: patreon.com/SeriousScience
Facebook — facebook.com/serious.science.org
Twitter — twitter.com/scienceserious
YouTube — youtube.com/user/SeriousScience
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