«Tinker with a real neural network right here in your browser».
Source : A Neural Network Playground
Étiquette : deep learning (Page 10 of 12)
«The paper introduces AlphaGo Zero, the latest evolution of AlphaGo, the first computer program to defeat a world champion at the ancient Chinese game of Go. Zero is even more powerful and is arguably the strongest Go player in history. Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play».
«Neural nets are just thoughtless fuzzy pattern recognizers, and as useful as fuzzy pattern recognizers can be—hence the rush to integrate them into just about every kind of software—they represent, at best, a limited brand of intelligence, one that is easily fooled. A deep neural net that recognizes images can be totally stymied when you change a single pixel, or add visual noise that’s imperceptible to a human. Indeed, almost as often as we’re finding new ways to apply deep learning, we’re finding more of its limits. Self-driving cars can fail to navigate conditions they’ve never seen before. Machines have trouble parsing sentences that demand common-sense understanding of how the world works.Deep learning in some ways mimics what goes on in the human brain, but only in a shallow way—which perhaps explains why its intelligence can sometimes seem so shallow».
Source : Is AI Riding a One-Trick Pony? – MIT Technology Review
«Meet Todai Robot, an AI project that performed in the top 20 percent of students on the entrance exam for the University of Tokyo — without actually understanding a thing».
Deep learning software for colorizing black and white images with a few clicks.
Qualitative results are presented on several tasks where paired training data does not exist, including collection style transfer, object transfiguration, season transfer, photo enhancement, etc.
Source : Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
« Ingesting data, predicting trends, and suggesting solutions is almost perfectly suited to DeepMind’s neural network expertise. While the National Grid is surely aware of some potential optimisations, a more rigorous investigation by a DeepMind AI may uncover solutions that the grid’s human operators have never considered. One thing’s for certain: a system as large as the UK grid has millions of inefficiencies ».
Source : DeepMind in talks with National Grid to reduce UK energy use by 10% | Ars Technica UK
« Vision ThroughArtificial Intelligence »
The pix2pix model works by training on pairs of images such as building facade labels to building facades, and then attempts to generate the corresponding output image from any input image you give it. The idea is straight from the pix2pix paper, which is a good read.
Source : Image-to-Image Demo – Affine Layer
« Creating new image details out of thin air: Good for law enforcement, or just plain scary? »
Source : Google Brain super-resolution image tech makes “zoom, enhance!” a real thing | Ars Technica UK