When in 2012 a computer learned to recognize cats in YouTube videos and just last month another correctly captioned a photo of "a group of young people playing a game of Frisbee," artificial intelligence researchers hailed yet more triumphs in "deep learning," the wildly successful set of algorithms loosely modeled on the way brains grow sensitive to features of the real world simply through exposure. Using the latest deep-learning protocols, computer models consisting of networks of artificial neurons are becoming increasingly adept at image, speech and pattern recognition -- core technologies in robotic personal assistants, complex data analysis and self-driving cars. But for all their progress training computers to pick out salient features from other, irrelevant bits of data, researchers have never fully understood why the algorithms or biological learning work. Now, two physicists have shown that one form of deep learning works exactly like one of the most important and ubiquitous mathematical techniques in physics, a procedure for calculating the large-scale behavior of physical systems such as elementary particles, fluids and the cosmos. The new work, completed by Pankaj Mehta of Boston University and David Schwab of Northwestern University, demonstrates that a statistical technique called "renormalization," which allows physicists to accurately describe systems without knowing the exact state of all their component parts, also enables the artificial neural networks to categorize data as, say, "a cat" regardless of its color, size or posture in a given video.

In March, Microsoft revealed that it was using the open-world game Minecraft to train AI agents to learn how to do things like climbing a hill. The company also promised to make it available to the public so they could work on their own artificial intelligence projects and research, and it's finally available today. Project Malmo (formerly known as Project AIX) is a Minecraft mod that works on Windows, Mac and Linux, and supports just about any programming language you might want to use. So yes, that means you will need to know how to code – but Microsoft says that even novice programmers can get in on the action. You can learn more about Project Malmo here and grab the mod from this GitHub repository to try it for yourself.

"Really, we're building collision avoidance for industrial drones," said Alexander Harmsen, CEO and co-founder of Iris Automation. "We see this huge need for industrial drones for mining exploration, pipeline inspection, agricultural surveying, forestry, or even package delivery." Without a way to avoid mid-air collisions, drones risk crashing into a Cessna, a flock of geese or a 747. Worst case scenario: a drone gets sucked into a jet engine causing catastrophic engine failure as high-velocity bits of metal penetrate fuel tanks, hydraulic lines and the cabin. Iris Automation's solution is an AI computer that blends real-time images and 3D maps to track incoming objects.

Drowsy driving is notoriously tough to detect. There's no test to prove it, the way a breathalyzer can prove someone was driving drunk. But technology to detect drowsy driving is in the works. In commercial transport, one industry is leading the way: mining. The stakes are particularly high in this field since the enormous haul trucks used in mining are several times the height of a person.

A 13-year-old in California shook her head at the TV. A 5-year-old in Pittsburgh asked her father why people are so angry. As America coped with one tragic moment after another this week, with the deaths of Alton Sterling and Philando Castile followed by the shooting of a dozen police officers in Dallas, the country's parents had an added task: explaining each act of violence to their children. "If [children] see a bunch of this on television, they can become the indirect victims of trauma," said Suzanne Silverstein, director of the Cedars-Sinai Psychological Trauma Center. African American children might be afraid for their own lives or for their friends and families when they see black men being shot.

Two recent accidents involving Tesla's Autopilot system may raise questions about how computer systems based on learning should be validated and investigated when something goes wrong. A fatal Tesla accident in Florida last month occurred when a Model S controlled by Autopilot crashed into a truck that the automated system failed to spot. Tesla tells drivers to pay attention to the road while using Autopilot, and explains in a disclaimer that the system may struggle in bright sunlight. Today the National Highway Traffic Safety Administration said it was investigating another accident in Pennsylvania last week where a Model X hit the barriers on both sides of a highway and overturned. The driver said his car was operating in Autopilot mode at the time.

The three cutting-edge frameworks showcased in these talks from MesosCon North America demonstrate the amazing power and flexibility of Apache Mesos for solving large-scale problems. Perhaps you have noticed, in our Apache Mesos series, the importance of frameworks. Mesos frameworks are the essential glue that make everything work in a Mesos cluster, the layer between Mesos and your applications. They perform a multitude of tasks, including launching and scaling applications, monitoring and health checks, configuration management, and scheduling. In these talks, you'll learn how: Netflix uses Mesos to power their recommendation engines.

Scientists are closer to creating a computer with emotions. Researchers in Russia are expected to reveal an emotional computer within a year and a half, which will be able to think like a person and build up trust, its creators say. The system, called'Virtual Actor', is being created by the National Research Nuclear University in Moscow. Computers are machines used for practical reasons, without any emotion involved. The AI, called'Virtual Actor', is expected to be online within the next year and a half.

Bringing bloody resolution to a standoff with the suspected shooter in Thursday's horrific sniper attack on police at a Black Lives Matter protest, Dallas Police cornered and killed the suspect in a parking garage with an explosive delivered by a bomb-disposal robot. The AP quotes robotics expert Peter W. Singer at the New America Foundation as saying that, to his knowledge, this is the first instance in the United States of police killing someone with a robot. In a statement given on Friday, Police Chief David Brown said that the robot was deployed after several hours of failed negotiations and an exchange of fire at the El Centro College parking structure where the suspect was found. "We saw no other option but to use our bomb robot and place a device on its extension for it to detonate where the suspect was," said Brown. "Other options would have exposed our officers to great danger. The suspect is deceased as a result of detonating the bomb."

She paints and writes poetry. She's also an artificial intelligence from the movie Her, which imagines how a juiced-up Siri will change our lives. Now, tech companies large and small are racing to make this a reality. You've heard the jargon: AI, machine learning, deep learning, neural networks, natural language processing. AI, simply put, is an attempt to make computers as smart, or even smarter than human beings.