Agents use the same senses and controls as humans: seeing pixels and using a keyboard and mouse. Universe makes it possible to train a single agent on any task a human can complete with a computer.

Oculus Touch has two pretty good reasons to stay inside this winter, and Amazon is killing checkout lines. Is this the future of retail? Amazon premieres the "Just Walk Out Shopping experience" Amazon already has internet shopping boiled down to a single click or voice command, so what's next? It's opened an employees-only shopping location in Seattle that uses " computer vision, sensor fusion, and deep learning" to track what people take. There's no check-out lane here -- just take your stuff and go, while Amazon bills your account and emails a receipt.

The Google logo is displayed at the Google headquarters in Mountain View, California. According to PCMag, Google's DeepMind Lab serves as a testing ground for building better and smarter artificial intelligence (AI). DeepMind has been working on AI for six years. Its artificial intelligence technology can excel at arcade games like Pac-Man and Space Invaders, as well as more complex games such as Chinese board game Go. Google's DeepMind Lab has also built rich simulated environments with the aim to serve as a kind of "laboratories" for AI research," according to company's blog post.

While AI (artificial intelligence) has been around since the 50's, IBM was the pioneer in the latest AI cycle with their own custom solution dubbed Watson. Ever since the introduction of Watson and its ability to beat Jeopardy Champion Ken Jennings, the company has been increasing its investment in the space. IBM Watson is now an entire division of the company which indicates the importance they put on the future of AI. Watson is only one part of IBM's AI investment which I consider the "easy button" for those enterprise who don't want to create everything from scratch. IBM also has DIY (do it yourself) infrastructure for cloud providers through POWER8, OpenPOWER, OpenCAPI, designed for cloud giant rolls their own AI software. But what about enterprises who are in the middle, those who want solid infrastructure and want to invest in the latest deep neural network frameworks? IBM announced an answer this week at SC16 and it's called PowerAI.

DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning. Disclaimer: This is not an official Google product. If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper.

One contribution to this pragmatic efficiency is supplied by the guidance a representation provides for organizing information so as to facilitate making the recommended inferences.

A few weeks ago, Montreal-based AI pioneer Yoshua Bengio launched Element AI, a Silicon Valley-style startup incubator dedicated to deep learning. Despite its modest (but growing) startup scene, Montreal is already a hotbed in AI talent, with a trove of deep learning researchers across the city. Bengio -- along with Jean-François Gagné, Nicolas Chapados, Jean-Sébastien Cournoyer, and the rest of their team of tech mavericks -- is hoping to accelerate the proliferation of AI startups and researchers in Montreal to turn the city into an AI center. As a proud Montrealer and bot maker, I couldn't be happier with this news. Surprisingly, though, the launch received some mixed feedback locally.

With demand for graduates with AI skills booming, we've released the NVIDIA Deep Learning Teaching Kit to help educators give their students hands on experience with GPU-accelerated computing. The kit -- co-developed with deep-learning pioneer Yann LeCun, and largely based on his deep learning course at New York University -- was announced Monday at the NIPS machine learning conference in Barcelona. Thanks to the rapid development of NVIDIA GPUs, training deep neural networks is more efficient than ever in terms of both time and resource cost. The result is an AI boom that has given machines the ability to perceive -- and understand -- the world around us in ways that mimic, and even surpass, our own. "Deep learning has become one of the most important computing models, and the need for graduating students with theoretical and application expertise in this area is critical," LeCun said.

Nvidia cofounder Chris Malachowsky is eating a sausage omelet and sipping burnt coffee in a Denny's off the Berryessa overpass in San Jose. It was in this same dingy diner in April 1993 that three young electrical engineers--Malachowsky, Curtis Priem and Nvidia's current CEO, Jen-Hsun Huang--started a company devoted to making specialized chips that would generate faster and more realistic graphics for video games. East San Jose was a rough part of town back then--the front of the restaurant was pocked with bullet holes from people shooting at parked cop cars--and no one could have guessed that the three men drinking endless cups of coffee were laying the foundation for a company that would define computing in the early 21st century in the same way that Intel did in the 1990s. "There was no market in 1993, but we saw a wave coming," Malachowsky says. "There's a California surfing competition that happens in a five-month window every year. When they see some type of wave phenomenon or storm in Japan, they tell all the surfers to show up in California, because there's going to be a wave in two days. We were at the beginning."

AWS (Amazon Web Services) introduced a handful of new artificial intelligence (AI) services at its re:Invent conference last week. Among the new products are Polly, a more lifelike text-to-speech service, Rekognition, an image analysis and face recognition service that can be added to applications and Lex, a standalone version of the technology that powers the company's Alexa AI assistant. "Amazon AI services are fully managed services so there are no deep learning algorithms to build, no machine learning models to train, and no up-front commitments or infrastructure investments required," the company said in a statement. "This frees developers to focus on defining and building an entirely new generation of apps that can see, hear, speak, understand, and interact with the world around them." So far, few developers have been able to build, deploy, and broadly scale apps with AI capabilities due to the vast amount of data and specialized expertise in machine learning and neural networks required, Amazon said.