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Intuition Machine - Issue #48

Intuition Machine
Intuition Machine - Issue #48
By Intuition Machine  • Issue #48 • View online
Welcome to the weekly newsletter of Deep Learning AI and Blockchain Convergence. We hope that this newsletter will appeal to all those interested in Deep Learning developments and its relationship to decentralized consensus architectures.

Intuition Machines versus Algebraic Minds
I owe at least Gary Marcus a more detailed examination of each of his assertions of the limitations of Deep Learning. 
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Why is it hard to train deep neural networks? Degeneracy, not vanishing gradients, is the key
Why is it hard to train deep neural networks? Degeneracy, not vanishing gradients, is the key
It seems to be a widely held belief that this difficulty is mainly, if not completely, due to the vanishing (and/or exploding) gradients problem. 
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Synthetic Gradients Tutorial - How to Speed Up Deep Learning Training - YouTube
Synthetic Gradients Tutorial - How to Speed Up Deep Learning Training - YouTube
Synthetic Gradients were introduced in 2016 by Max Jaderberg and other researchers at DeepMind. 
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Professor Cédric Villani, “Optimal Transport Theory”
Professor Cédric Villani, “Optimal Transport Theory”
Professor Villani from Université Claude Bernard (Lyon), discusses optimal transport theory, artificial intelligence and the journey and opportunities that a career in mathematics can offer.
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 To achieve human level intelligence, learning machines need the guidance of a model of reality, similar to the ones used in causal inference tasks. 
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“Whatever you are studying right now if you are not getting up to speed on deep learning, neural networks, etc., you lose,” says Mark Cuban. “We are going through the process where software will automate software, automation will automate automation.”
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Artificial Intuition : The Improbable Deep Learning Revolution
 There are two kinds of audiences, those looking to explore and those looking to optimize. There are two ways to learn, learning by exploration and learning by exploitation. This book is about exploration into the emerging field of Deep Learning. 
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