Research funded by the National Science Foundation may have found an ingenious solution to poaching: applying game theory and computer science to real-life situations. One of the biggest factors in why there are so many endangered animals today is poaching – a centuries-old problem. The dwindling tiger population is one of the most glaring examples of this. Whether for sport, medicine, pelts or other body parts, poaching remains a huge threat to wildlife. Patrols have long been the most direct form of human intervention in wildlife protection.

Computer chip giant Nvidia has developed a "miracle" chip that is expected to significantly accelerate breakthroughs in artificial intelligence research. Nvidia's Tesla P100 chip crams in 15 billion transistors within its 610-square-millimeter frame, around three-times more than most processors or graphics chips on the market. According to the company's CEO, this makes the Tesla P100 the largest computer chip ever made. "Three years ago, we dedicated ourselves on the single greatest endeavour in the history of our company," Jen-Hsun Huang, CEO of Nvidia, said at the GPU Technology Conference earlier this month. "We decided to be all in on AI. For the first time, we would design [a chip] that is dedicated to this field of work. Dedicated to accelerating AI; dedicated to accelerating deep learning. "I think we are going to realize looking back that one of the biggest things that ever happened is AI." The Tesla P100 is the product of around 2.5 billion worth of research and development at the hands of thousands of computer engineers. The Tesla P100 chip contains more than 15 billion transistors and is described by Nvidia's CEO as "a beast of a machine." "The odds of this working at all is approximately zero," said Huang. "We are changing so many things in one project.

In the race to develop self-driving cars, the United States and Europe lead in technology, but China is coming up fast in the outside lane with a regulatory structure that could put it ahead in the popular adoption of autonomous cars on its highways and city streets.

Venture capitalists pride themselves on their ability to pick winning ideas and winning people. But could artificial intelligence do a better job? Founders Factory, a U.K. startup accelerator, has developed an AI platform that identifies high-potential entrepreneurs. The hope is to avoid the unconscious bias that normally privileges some demographic groups and backgrounds, and prevents others from getting ahead. "I was interested in getting around the bias of selection, that if you've gone to a good school or university, you probably have a good network and a good chance of doing fairly well," says Tom Bowles, who created the software.

This month Nvidia bolstered its GPU strategy to stretch further into deep learning, high performance computing, and other markets, and while there are new options to consider, particularly for the machine learning set, it is useful to understand what these new arrays of chips and capabilities mean for users at scale. As one of the companies directly in the lens for Nvidia with its recent wave of deep learning libraries and GPUs, Baidu has keen insight into what might tip the architectural scales--and what might still stay the same, at least for now. Back in December, when we talked to one of the lead scientists at Baidu's Silicon Valley AI Lab, Bryan Catanzaro, we dug into how teams there make architectural decisions to power deep learning for speech recognition and other services. At the time, he told us about their use of Nvidia Titan X GPU cards as the most cost efficient option for the computationally-intensive task of model training, despite the availability of other GPUs, including the M40 and for the inference phase, M4 as well as other more powerful GPUs, including the supercomputing oriented Tesla K80. Following GTC16, where Nvidia announced its forthcoming Pascal architecture, yet another possible option for these workloads emerged in the form of the P100, which have detailed rather extensively here and here.

A century ago, more than 60,000 tigers roamed the wild. Today, the worldwide estimate has dwindled to around 3,200. Poaching is one of the main drivers of this precipitous drop. Whether killed for skins, medicine or trophy hunting, humans have pushed tigers to near-extinction. The same applies to other large animal species like elephants and rhinoceros that play unique and crucial roles in the ecosystems where they live.

A trip to Iceland wouldn't be complete without a dip in the Blue Lagoon, a man-made geothermal pool on Reykjanes peninsula. A trip to Iceland wouldn't be complete without a dip in the Blue Lagoon, a man-made geothermal pool on Reykjanes peninsula. The premise is simple: Correspondents, editors and producers from our newsroom share the pieces that have kept them reading, using the #NPRreads hashtag. Each weekend, we highlight some of the best stories. You have storms, you have darkness, but the pool is a place to find yourself again.

A team from the University of Nebraska-Lincoln flew an unmanned aircraft over the prairie at the Homestead National Monument of America on Friday, dropping ping pong-like balls filled with a chemical mixture to ignite brush-clearing grass fires. Local and federal officials are interested in the technology because it could help clear overgrown vegetation in rugged, hard-to-reach terrain, said Michael Johnson, a spokesman for the National Park Service. The balls are filled with a chemical powder, potassium permanganate, before they're loaded into the drone. During flight, the aircraft pierces the ball with a needle and injects it with another chemical, glycol, before releasing it. The technology is already used by helicopters to start controlled burns, but researchers note that the drone is cheaper and more portable.

China's Nasdaq-listed internet search engine giant Baidu Inc. said Friday it has formed a team in Silicon Valley dedicated to its self-driving car efforts. The announcement comes as Chinese officials rush to set up a road map for incorporating highway-ready, self-driving cars within three to five years. Baidu's Silicon Valley team will grow to more than 100 researchers and engineers, focused on research, development and testing, by the end of 2016, the company said in a statement Friday. The Beijing-headquartered firm is looking to work on areas "integral to self-driving car development, including planning, perception, control and systems." The team in Silicon Valley will be part of the company's newly created Autonomous Driving Unit.

Google made headlines earlier this year when its AlphaGo AI defeated world champion Lee Se-Dol in the ancient board game Go. But a group of researchers want to push the boundaries and see how a computer might fare in a first-person shooter deathmatch. The 2016 Computational Intelligence and Games (CIG) Conference will host a competition to determine the best bot that's capable of winning a multiplayer round of Doom, while playing the way a human does. Our biggest ever edition of TNW Conference is fast approaching! That means that unlike enemy AI in video games, which have a complete overview of the level's map, locations of powerups and weapons, the bots will have to rely only on raw visual input that mimics what a human gamer sees when they play a game. The Visual AI Doom Competition will pit bots against each other in two tracks: the first one will see them playing a map known to their programmers with only rocket launchers and health boosts, while the other will feature an undisclosed map with all weapons and items available.