Australian physicists, perhaps searching for a way to shorten the work week, have created an AI that can run and even improve a complex physics experiment with little oversight. The research could eventually allow human scientists to focus on high-level problems and research design, leaving the nuts and bolts to a robotic lab assistant. The experiment the AI performed was the creation of a Bose-Einstein condensate, a hyper-cold gas, the process for which won three physicists the Nobel Prize in 2001. It involves using directed radiation to slow a group of atoms nearly to a standstill, producing all manner of interesting effects. "It did things a person wouldn't guess, such as changing one laser's power up and down, and compensating with another," said ANU's Paul Wigley, co-lead researcher, in a news release.

For a conference that has been used to advance Android and Chrome, and introduce Google Glass with users parachuting from a plane, people are expecting to hear about virtual reality and artificial intelligence at this week's Google I/O conference. "This year's focus will be virtual reality, no doubt," said Jeff Kagan, an independent industry analyst. "I believe Google wants to be a leader in virtual reality and, in this marketplace where there are no leaders yet, I think they will try and secure their place in the front of the line." Kagan said Google may even roll out its own early- generation virtual reality device at I/O, the company's annual developer conference, which generally draws more than 6,000 attendees. The conference is being held from Wednesday through Friday in Mountain View, Calif., the same city where Google is headquartered.

Vasant Dhar is a professor at the Stern School of Business and the Center for Data Science at New York University. The widespread conversations about AI took a new turn in March 2016 when Microsoft launched, then quickly unplugged, Tay, its artificial intelligence chat robot. Within 24 hours, interactions on Twitter had turned the bot, modeled after a teenage girl, into a "Hitler-loving sex robot." This controversy, on the heels of the Feb. 14, 2016, accident of Google's self-driving robot car, has ignited a new debate over artificial intelligence. How should we design intelligent learning machines that minimize undesirable behavior?

We would be lost without GPS. The Global Positioning System constellation of satellites started life as a military project, but now enables turn-by-turn directions in the palm of your hand, and confidence that it's almost impossible to get lost as long as you can see the sky. GPS doesn't penetrate the briny deep, so Darpa, the Pentagon's research arm, wants a system that will keep the robots plumbing the oceans on the map, and it's asking for proposals from industry. The proposed solution also wins this week's award for best military acronym: "Posyndon," for Positioning System for Deep Ocean Navigation. "What they are trying to do here is revolutionize underwater navigation in a way that is similar for what GPS did for above water," says Neil Adams, director of defense systems at Draper, the non-profit R&D lab that's working on an answer.

No sooner than one global consulting giant has jumped on board with the latest technology trend, another follows suit. Accenture is launching an artificial intelligence practice just a week after PwC did the same with drones, in a bid for a share of the multi-billion dollar and fast growing industry. The Amelia practice, named after the AI software from IPsoft with which it has partnered, will work with clients on integrating AI technology into their business, initially focusing on the banking, insurance and travel sectors. "Artificial intelligence is maturing rapidly and offers great potential to reshape the way that organisations conduct business and interact with their customers and employees. At the same time, executives are overwhelmed by the plethora of technologies and many products that are advertising AI or cognitive capabilities," said Accenture chief technology officer Paul Daugherty.

"Work hard, play hard," that is the motto that scored Hope Reese 542.10 at the Kentucky Derby. "I was watching this with a whole group of people and thinking'there's no way this can happen," TechRepublic Staff Writer Hope Reese said. Reese won more than 500 on a 1.00 superfecta box which she put 24 down on. The odds were 540 to one. So, how did she predict the first four finishers in the Kentucky Derby?

LET me hazard a guess that you think a real person has written what you're reading. Perhaps you should ask me to confirm it the way your computer does when it demands that you type those letters and numbers crammed like abstract art into that annoying little box. Because, these days, a shocking amount of what we're reading is created not by humans, but by computer algorithms. We probably should have suspected that the information assaulting us 24/7 couldn't all have been created by people bent over their laptops. The multitude of digital avenues now available to us demand content with an appetite that human effort can no longer satisfy.

The researchers recently presented their work at the international Autonomous Agents and Multiagent Systems conference. As robots become more pervasive in society, humans will want them to do chores like cleaning house or cooking. But to get a robot started on a task, people who aren't computer programmers will have to give it instructions. "We want everyone to be able to program, but that's probably not going to happen," said Matthew Taylor, Allred Distinguished Professor in the WSU School of Electrical Engineering and Computer Science. "So we needed to provide a way for everyone to train robots -- without programming."

The following interview is one of many included in the report. As part of our ongoing series of interviews surveying the frontiers of machine intelligence, I recently interviewed Brendan Frey. Frey is a co-founder of Deep Genomics, a professor at the University of Toronto and a co-founder of its Machine Learning Group, a senior fellow of the Neural Computation program at the Canadian Institute for Advanced Research, and a fellow of the Royal Society of Canada. His work focuses on using machine learning to understand the genome and to realize new possibilities in genomic medicine. Brendan Frey: I completed my Ph.D. with Geoff Hinton in 1997.

John Markoff recently reported in the New York Times, "In its quest to maintain a United States military advantage, the Pentagon is aggressively turning to Silicon Valley's hottest technology -- artificial intelligence. On Wednesday, Secretary of Defense Ashton B. Carter made his fourth trip to the tech industry's heartland since being named to his post last year. Before that, it had been 20 years since a defense secretary had visited the area, he noted in a speech at a Defense Department research facility near Google's headquarters. The Pentagon's intense interest in A.I. -- and by connection the Silicon Valley companies specializing in that technology -- has grown out of the'Third Offset' strategy articulated by Mr. Carter last fall. Concerned about the re-emergence of China and Russia as military competitors, he stated that computer-based, high-tech weapons would give the American military an edge in the future."