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.
Humans by their nature have many cognitive biases. This can become detrimental to real scientific progress. Research tends to be bias in favor of approaches that many experts have invested countless…
We are very quickly nearing the end of 2018. As I have done in previous years, this is a retrospective of my prediction for Deep Learning in 2018. The purpose of this exercise is to get a measure of…
What’s not apparent to many practitioners and researchers in Deep Learning is that the rich variety of methods developed over the past several years are relevant to systems that have different kinds…
An analysis of more than 400 use cases across 19 industries and nine business functions highlights the broad use and significant economic potential of advanced AI techniques.
In this work, we address the problem of musical timbre transfer, where the goal is to manipulate the timbre of a sound sample from one instrument to match another instrument while preserving other musical content, such as pitch, rhythm, and loudness.
The year 2018 has been an inflection point for machine learning models handling text (or more accurately, Natural Language Processing or NLP for short).
In this blog-post, we’ll go over the MAML model, identify key problems, and then formulate a number of methodologies that attempt to solve them, as proposed in the recent paper How to train your MAML and implemented in the How to train your MAML github repo.
Meta-learning, also known as “learning to learn”, intends to design models that can learn new skills or adapt to new environments rapidly with a few training…
This web page contains materials to accompany the NeurIPS 2018 tutorial, “Adversarial Robustness: Theory and Practice”, by Zico Kolter and Aleksander Madry.
The year 2018 marked a turning point for the field of Natural Language Processing, with a series of deep-learning models achieving state-of-the-art results on NLP tasks ranging from question…
How to install TensorFlow GPU on Ubuntu 18.04 in one line. Lambda Stack also installs caffe, caffe2, pytorch with GPU support on Ubuntu 18.04 or 16.04. Stop wasting time configuring your linux system and just install Lambda Stack already!
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. It’s more like a popular science book and less of a business book.
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