At San Francisco's first fully automated restaurant, meals appear in little glass cubbies, just 90 seconds after customers order and pay on wall-mounted iPads. It's a human-less experience – no waitstaff, no cashier, no one to get your order wrong and no one to tip. The moment before the meal appears, the see-through display screen that fronts the cubbies goes black for the few seconds when you might catch sight of the hand that feeds you. Eatsa has not yet achieved total automation. The company admits it employs a small kitchen staff, and one employee is present in the front of the house, answering questions about how to order and dodging questions about what's going on behind the wall of magic cubbies.

Unexpected convergent consequences…this is what happens when eight different exponential technologies all explode onto the scene at once. This post (sixth in a series of seven) is a look at robotics. Be sure to read the first five posts if you haven't already: When the World Is Wired: The Magic of the Internet of Everything Where Artificial Intelligence Is Now and What's Just Around the Corner The Near Future of VR and AR: What You Need to Know Drones Have Reached at Tipping Point--Here's What Happens Next How 3D Printing Is Transforming the Way We Make Things An expert might be reasonably good at predicting the growth of a single exponential technology (e.g., 3D Printing), but try to predict the future when AI, robotics, VR, drones, and computation are all doubling, morphing and recombining…You have a very exciting (read: unpredictable) future. This post is the result of an interview with Rodney Brooks on the top five recent robotics breakthroughs (2012-2015) and the top five anticipated robotics breakthroughs (2016-2018). Rodney is the Panasonic Professor of Robotics at MIT.

At first, Fan Hui thought the move was rather odd. But then he saw its beauty. I've never seen a human play this move," he says. It's a word he keeps repeating. The move in question was the 37th in the second game of the historic Go match between Lee Sedol, one of the world's top players, and AlphaGo, an artificially intelligent computing system built by researchers at Google. Inside the towering Four Seasons hotel in downtown Seoul, the game was approaching the end of its first hour when AlphaGo instructed its human assistant to place a black stone in a largely open area on the right-hand side of the 19-by-19 grid that defines this ancient game. And just about everyone was shocked. I've never seen a human play this move.' "That's a very surprising move," said one of the match's English language commentators, who is himself a very talented Go player. Then the other chuckled and said: "I thought it was a mistake." But perhaps no one was more surprised than Lee Sedol, who stood up and ...

Once thought safe, DDR4 memory shown to be vulnerable to "Rowhammer" Physical weaknesses in memory chips that make computers and servers susceptible to hack attacks dubbed "Rowhammer" are more exploitable than previously thought and extend to DDR4 modules, not just DDR3, according to a recently published research paper. The paper, titled How Rowhammer Could Be Used to Exploit Weaknesses in Computer Hardware... Ars Technica How HTC and Valve built the Vive Long before the Vive was born, both software developer Valve and phone manufacturer HTC were separately looking into virtual reality. In 2012, VR was beginning to creep back into the public imagination. It started in May of that year, when id Software's John Carmack demoed a modified Oculus Rift running Doom 3. The following month, he took the Rift to a wider audience at the E3 games convention. By August, Palmer Luckey launched the Oculus Kickstarter campaign, and it broke records.

Updated 15 March 2016: Today concludes the five'Go' matches played by AlphaGo, an AI system built by DeepMind and South Korean champion, Lee Sedol. AlphaGo managed to win the series of games 4-1. 'Go' is a strategy-led board game in which two players aim to gather and surround the most territory on the board. The game is said to require a certain level of intuition and be considerably more complex than Chess. The first three games were won by AlphaGo with Sedol winning the fourth round, but still unable to claim back a victory.

God moves the player, he in turn the piece. But what god beyond God begins the round Of dust and time and sleep and agony? As I write this column, a computer program called AlphaGo is beating the professional go player Lee Sedol at a highly publicized tournament in Seoul. Sedol is among the top three players in the world, having attained the highest rank of nine dan. The victory over one of humanity's best representatives of this very old and traditional board game is a crushing 4 to 1, with one more game to come.

This week, Google's AlphaGo beat a grandmaster at the complex game Go – an artificial intelligence milestone (see "How victory for Google's Go AI is stoking fear in South Korea", "Machines are teaching themselves to grapple with the real world" and "Humans strike back: How Lee Sedol won a game against AlphaGo"). Here's what the experts say AI's next big challenge should be. No-limit poker: Go represents the ultimate in games where all the information is available to the players. But AI still struggles with games where information is incomplete – like poker, where a player doesn't know what card is coming next. "Computers have beaten the best people at heads-up limit Texas Hold'em, but not yet at no-limit, a much more complicated game," says Peter Stone at the University of Texas at Austin.

A huge milestone has just been reached in the field of artificial intelligence: AlphaGo, a program developed by Google's DeepMind unit, has defeated legendary Go player Lee Se-dol in the first of five historic matches being held in Seoul, South Korea. Lee resigned after about three and a half hours, with 28 minutes and 28 seconds remaining on his clock. The series is the first time a professional 9-dan Go player has taken on a computer, and Lee is competing for a 1 million prize. "I was very surprised," said Lee after the match. "I didn't expect to lose. DeepMind founder Demis Hassabis expressed "huge respect for Lee Se-dol and his amazing skills," calling the game "hugely exciting" and "very tense." Team lead David Silver said it was an "amazing game of Go that really pushed AlphaGo to its limits." Go is an ancient Chinese board game that has long been considered one of the great challenges faced by AI. While computer programs now best the world's leading human players of games like checkers and chess, the high level of intuition and evaluation required by Go has made it tough for computers to crack. DeepMind's AlphaGo program is the most advanced effort yet, using a complex system of deep neural networks and machine learning; it beat European champion Fan Hui last year, but Lee Se-dol is another proposition entirely. "I don't regret accepting this challenge," said Lee. "I am in shock, I admit that, but what's done is done.

Unexpected convergent consequences…this is what happens when eight different exponential technologies all explode onto the scene at once. This post (the second of seven) is a look at artificial intelligence. Future posts will look at other tech areas. An expert might be reasonably good at predicting the growth of a single exponential technology (e.g., the Internet of Things), but try to predict the future when A.I., robotics, VR, synthetic biology and computation are all doubling, morphing and recombining. You have a very exciting (read: unpredictable) future. This year at my Abundance 360 Summit I decided to explore this concept in sessions I called "Convergence Catalyzers." For each technology, I brought in an industry expert to identify their Top 5 Recent Breakthroughs (2012-2015) and their Top 5 Anticipated Breakthroughs (2016-2018). Then, we explored the patterns that emerged.

Welcome to robot nursery school," Pieter Abbeel says as he opens the door to the Robot Learning Lab on the seventh floor of a sleek new building on the northern edge of the UC-Berkeley campus. The lab is chaotic: bikes leaning against the wall, a dozen or so grad students in disorganized cubicles, whiteboards covered with indecipherable equations. Abbeel, 38, is a thin, wiry guy, dressed in jeans and a stretched-out T-shirt. He moved to the U.S. from Belgium in 2000 to get a Ph.D. in computer science at Stanford and is now one of the world's foremost experts in understanding the challenge of teaching robots to think intelligently. But first, he has to teach them to "think" at all. "That's why we call this nursery school," he jokes. He introduces me to Brett, a six-foot-tall humanoid robot made by Willow Garage, a high-profile Silicon Valley robotics manufacturer that is now out of business. The lab acquired the robot several years ago to experiment with. Brett, which stands for ...