When we look very closely at images generated by neural networks, we often see a strange checkerboard pattern of artifacts. It’s more obvious in some cases than others, but a large fraction of recent models exhibit this behavior. Mysteriously, the checkerboard pattern tends to be most prominent in images with strong colors. What’s going on? Read more about Deconvolution and Checkerboard Artifacts — Distill[…]

A popular method for exploring high-dimensional data is something called t-SNE, introduced by van der Maaten and Hinton in 2008. The technique has become widespread in the field of machine learning, since it has an almost magical ability to create compelling two-dimensonal “maps” from data with hundreds or even thousands of dimensions. Although impressive, these Read more about How to Use t-SNE Effectively — Distill[…]

Recurrent neural networks are one of the staples of deep learning, allowing neural networks to work with sequences of data like text, audio and video. They can be used to boil a sequence down into a high-level understanding, to annotate sequences, and even to generate new sequences from scratch! Source: Attention and Augmented Recurrent Neural Read more about Attention and Augmented Recurrent Neural Networks — Distill[…]

The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. Source: Deep Learning

Neural Networks and Deep Learning is a free online book. The book will teach you about: Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data Deep learning, a powerful set of techniques for learning in neural networks Neural networks and deep learning currently provide the best solutions to Read more about Neural networks and deep learning[…]

Several interactive visualizations of a generative model of handwriting. Some are fun, some are serious. Source: Experiments in Handwriting with a Neural Network — Distill

Embeddings are ubiquitous in machine learning, appearing in recommender systems, NLP, and many other applications. Indeed, in the context of TensorFlow, it’s natural to view tensors (or slices of tensors) as points in space, so almost any TensorFlow system will naturally give rise to various embeddings. To learn more about embeddings and how to train Read more about TensorBoard: Embedding Visualization for Tensorflow[…]

DeepMind Lab is a fully 3D game-like platform tailored for agent-based AI research. It is observed from a first-person viewpoint, through the eyes of the simulated agent. Scenes are rendered with rich science fiction-style visuals. The available actions allow agents to look around and move in 3D. The agent’s “body” is a floating orb. It Read more about Open-sourcing DeepMind Lab[…]

We’re releasing Universe, a software platform for measuring and training an AI’s general intelligence across the world’s supply of games, websites and other applications. Universe allows an AI agent to use a computer like a human does: by looking at screen pixels and operating a virtual keyboard and mouse. We must train AI systems on Read more about OpenAI Universe allows your AI to train on games, browsers by looking at screen pixels. Uses Gym (also OSS) for algo devs[…]

“There’s a 60-year-old woman in Tokyo. She was at the University of Tokyo. She had been diagnosed with leukemia six years ago. She was living, but not healthy. So the University of Tokyo ran her genomic sequence through Watson and it was able to ascertain that they were off by one thing. Actually, she had Read more about How IBM Watson saved the life of a woman dying from cancer, exec says – Business Insider[…]

AMD is announcing a new series of Radeon-branded products today, targeted at machine intelligence (AI) and deep learning enterprise applications, called Radeon Instinct. As its name suggests, the new Radeon Instinct line of products are comprised of GPU-based solutions for deep learning, inference, and training. The new GPUs are also complemented by a free, open-source library Read more about AMD Introduces Radeon Instinct Machine Intelligence And Deep Learning Accelerators[…]

The Chicago Face Database was developed at the University of Chicago by Debbie S. Ma, Joshua Correll, and Bernd Wittenbrink. The CFD is intended for use in scientific research. It provides high-resolution, standardized photographs of male and female faces of varying ethnicity between the ages of 17-65. Extensive norming data are available for each individual Read more about Chicago Face Database[…]

Source: China has now eclipsed US in AI / deep-learning research, robotics and VC funding (government-backed $338 billion) · GitHub