So NVIDIA engineer Robert Bond is using deep learning -- and our Jetson TX1 development platform -- to recognize cats and turn on his home's sprinkler system to gently shoo the visitors away. "My wife is a gardener and she likes her garden to be tidy and clean," says Bond, 65, a system software engineer who has been at NVIDIA for more than eight years. Bond quickly dismissed the idea of trapping the cats -- which just seemed "unneighborly" -- and decided to go with a more technical solution. Bond is no stranger to deep learning or Jetson. Last year, he build a system that shines a harmless 5 milliwatt laser beam on the ants that occasionally scuttle across his kitchen floor (see "How One NVIDIA Built a Jetson-Powered Laser'Ant Annoyer'").

Reuters – The fatal crash of a Tesla Motors, Inc. Model S in Autopilot mode has turned up pressure on auto industry executives and regulators to ensure that automated driving technology is deployed safely. The first such known accident, which occurred in Florida in May, has highlighted tensions surrounding efforts to turn over responsibility for braking, steering and driving judgments to machines. It may delay the U.S. government's plan to outline guidelines for self-driving cars this month. The cause of the Model S crash is still under investigation by federal and Florida state authorities, which are looking into whether the driver was distracted before his 2015 Model S went under a truck trailer. Shares of Tesla and Mobileye NV, the maker of the camera vision system used in the Model S, rose on Friday as analysts said the accident was likely a short-term setback.

Scientists have taught a robot how to hunt and destroy prey in a chilling new experiment. The test comes as experts warm AI could wipe out a tenth of the global population in five years. The ability to identify and zone in on a specific target will be crucial for any useful robotic technology like driverless cars, the researchers at the University of Zurich in Switzerland believe. And despite the chilling prospect of allowing a robot to mark up a target, they believe their research will prove more useful than deadly. Scientists have taught a robot how to hunt and destroy prey in a chilling new experiment.

Artificially-intelligent medical devices capable of continuously monitoring critically-ill patients and administering treatments when needed, are being investigated in a UK-wide research project. The research network, involving the Universities of Nottingham, Oxford and Warwick, will identify technologies that can provide more personalised and responsive care for cancer and intensive care patients, and those with chronic wounds. The three-year, EPSRC-funded project, which is being led by Prof Stephen Morgan at Nottingham University, will investigate technologies to monitor patients and administer medicines or adjust treatments as necessary, using information from built-in sensors. A particular focus of the research will be on devices that use the type of closed loop control system of feedback and intelligence found in power electronics used to control motors, said Morgan. "These continuously measure and feed their output back into the system, so they can constantly adjust," he said.

Twitter just paid 150m for 14-person Magic Pony, a UK-based AI visual search company barely anyone had heard of before the deal. At 10m per employee it marks a high water mark in AI for what is essentially a team acquisition. Magister has tracked 26 AI driven deals since 2014 in the US, Europe and Israel, 11 of which involved companies with less than 50 employees which were acquired largely, or entirely, for the team and capability. Across all 11 deals, the median price paid per employee has reached 2.4m, meaning a high quality AI company with 40 employees would be valued at near 100m. Even if it had little or no revenue.

Software governs much of our daily lives from behind the scenes, from which sorts of information we consume, to who we date. For some, secretive algorithms decide whether they are at risk of committing a future crime. It's only natural to want to understand how these black boxes accomplish all this, especially when it impacts us so directly. Artificial intelligence is getting better all the time. Google, for example, recently used a technique known as deep learning to kick a human's ass at Go, an incredibly complex board game invented thousands of years ago.

A fleet of drones could soon send M&M-sized peanut butter-flavoured treats raining down on the Montana grasslands, in efforts to save North America's endangered black-footed ferrets. The plan offers an unusual ray of hope for these rare predators, administering baited plague vaccines across a 1,200 acre habitat to preserve their main food source – prairie dogs. Outbreaks of sylvatic plague have wiped out prairie dogs by the masses, reducing their numbers by more than 95 percent, and thus killing off the ferrets who depend on them for survival. A fleet of drones could soon send M&M-sized peanut butter-flavoured treats raining down on the Montana grasslands, to save the endangered black-footed ferrets. Black-footed ferrets rely on prairie dogs for survival, but outbreaks of sylvatic plague have wiped out their prey by the masses.

Washington University in Saint Louis researchers demonstrated their upgraded camera by pointing laser light onto a printout of a toy car to create a movie of the light reaching different portions of the car at different times. A new approach to high-speed photography could help capture the clearest-ever footage of light pulses, explosions or neurons firing in the brain, according to a team of ultrafast camera developers. The technique involves shooting 100 billion frames per second in a single exposure without an external light source. That means, for example, there would be no need to set off multiple explosions just to gather enough data to create a video reconstructing exactly how chemicals react to create the blast. A team of Washington University in Saint Louis researchers introduced their "single-shot compressed ultrafast photography" camera two years ago.

Pieter Abbeel is an associate professor in UC Berkeley's EECS department, where he works in machine learning and robotics--in particular his research is on making robots learn from people (apprenticeship learning) and how to make robots learn through their own trial and error (reinforcement learning). Pieter's robots have learned advanced helicopter aerobatics, knot tying, basic assembly, and organizing laundry. He has won various awards, including best paper awards at ICML and ICRA, the Sloan Fellowship, the Air Force Office of Scientific Research Young Investigator Program (AFOSR-YIP) Award, the Office of Naval Research Young Investigator Program (ONR-YIP) Award, the DARPA Young Faculty Award (DARPA-YFA), the National Science Foundation Faculty Early Career Development Program Award (NSF-CAREER), the Presidential Early Career Award for Scientists and Engineers (PECASE), the CRA-E Undergraduate Research Faculty Mentoring Award, the MIT TR35, the IEEE Robotics and Automation Society (RAS) Early Career Award, and the Dick Volz Best US PhD Thesis in Robotics and Automation Award.

Or at least a coin-sized cyborg stingray made from rat heart cells that can be controlled underwater using light. Designed by Kevin Kit Parker from Harvard University's Wyss Institute and his team, the 16-millimetre-long soft robot has a gold skeleton overlaid with a flexible polymer. Its muscles are made up of about 200,000 rat heart cells laid down in layers. "My building material is alive," says Parker. To get the tiny robot to move, the team tweaked the rat-cell genes to make them light-sensitive.