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.

A report shown at the 2016 World Economic Forum in January says millions of jobs will be lost to robots in the next few years. When thinking about who is most vulnerable, factory workers, drivers, and pilots come to mind. Surely the jobs requiring a human touch, such as artists, entertainers, and managers, will stick around, right? Maybe some of those jobs will be safe. Managers, not so much; very soon, robots will be replacing humans in top management positions, even up to the CEO level.

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.

Inbox by Gmail has a few useful features but probably the most interesting is Smart Reply, which was expanded to the desktop this week. As impressive as the A.I.-powered suggestions for replies to your emails are, they're just not very useful yet. Sure, Smart Replies tend to offer relevant options, but they're not very useful in most real-world cases. Open an invitation to party and you might get'Sounds good!,' 'Can't wait,' and Sorry, I can't be there!' as the suggestions. By the time I've added'Hi Bob,' and a few other bits of personalization, I might as well have written the whole thing myself.

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 ...

Note: This is Part 2 of a two-part series on AI. We have what may be an extremely difficult problem with an unknown time to solve it, on which quite possibly the entire future of humanity depends. Welcome to Part 2 of the "Wait how is this possibly what I'm reading I don't get why everyone isn't talking about this" series. Part 1 started innocently enough, as we discussed Artificial Narrow Intelligence, or ANI (AI that specializes in one narrow task like coming up with driving routes or playing chess), and how it's all around us in the world today. We then examined why it was such a huge challenge to get from ANI to Artificial General Intelligence, or AGI (AI that's at least as intellectually capable as a human, across the board), and we discussed why the exponential rate of technological advancement we've seen in the past suggests that AGI might not be as far away as it seems. This left us staring at the screen, confronting the intense concept of potentially-in-our-lifetime ...