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.
I’ve got this ominous feeling that 2018 could be the year that everything just changes dramatically. The incredible breakthroughs we saw in 2017 for Deep Learning is going to carry over in a very…
Last year, I wrote my predictions for Deep Learning in 2017. I will recap those prediction and present new predictions for the coming year. Nvidia continues to dominate as predicted. They’ve added on…
With all new technologies there are predictions of how good it will be for humankind, or how bad it will be. A common thread that I have observed is how people tend to underestimate how long new technologies will take to be adopted after proof of concept demonstrations. I pointed to this as the seventh of seven deadly sins of predicting the future of AI.
The year is coming to an end. I did not write nearly as much as I had planned to. But I’m hoping to change that next year, with more tutorials around Reinforcement Learning, Evolution, and Bayesian Methods coming to WildML!
As part of the 2017–2018 Fellows’ Presentation Series at the Radcliffe Institute for Advanced Study, Michael Bronstein RI ’18 discusses the past, present, an…
Over the past few years, Deep Learning (DL) architectures and algorithms have made impressive advances in fields such as image recognition and speech processing.
Tutorial Deep Learning: Practice and Trends. Nando de Freitas, Scott Reed, Oriol Vinyals. Abstract: Deep Learning has become an essential toolbox which is us…
In my last post on Machine Learning we followed Unity’s Getting Started tutorial and managed to get the “Balance Ball” example project up and running. In this post we are going to start something from
We propose a hierarchical policy network which can reuse previously learned skills alongside and as subcomponents of new skills. It achieves this by discovering the underlying relations between skills.
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