The overeager adoption of big data is likely to result in catastrophes of analysis comparable to a national epidemic of collapsing bridges. Hardware designers creating chips based on the human brain are engaged in a faith-based undertaking likely to prove a fool's errand. Despite recent claims to the contrary, we are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree. Those may sound like the Luddite ravings of a crackpot who breached security at an IEEE conference. In fact, the opinions belong to IEEE Fellow Michael I. Jordan, Pehong Chen Distinguished Professor at the University of California, Berkeley. Jordan is one of the world's most respected authorities on machine learning and an astute observer of the field. His CV would require its own massive database, and his standing in the field is such that he was chosen to write the introduction to the 2013 National Research Council report "Frontiers in Massive Data Analysis." San Francisco writer Lee Gomes interviewed him for IEEE Spectrum on 3 October 2014. IEEE Spectrum: I infer from your writing that you believe there's a lot of misinformation out there about deep learning, big data, computer vision, and the like. Michael Jordan: Well, on all academic topics there is a lot of misinformation. The media is trying to do its best to find topics that people are going to read about. Sometimes those go beyond where the achievements actually are.

The number of new malware variations that pop up each day runs somewhere between 390,000 (according to AV-TEST Institute) and one million (according to Symantec Corporation). These are new strains of malware that have not been seen in the wild before. Even if we consider just the low end figure, the situation is still dire. Google Now is about to get a lot better in the future, aiming to serve Android users even when they're offline. With smartphones increasingly gaining ground, digital assistants have become widely popular and heavyweight companies are competing to deliver the best software in this category.

Every age has its iconic images. One of the more terrifying ones of the 21st century is the image of a man in desert or army fatigues making a "V for victory" sign with raised arm while standing over the decapitated body of a Western victim. In most of these images, the perpetrator's face and head are covered with a scarf or hood to hide his identity. That has forced military and law enforcement agencies to identify these individuals in other ways, such as with voice identification. This is not always easy or straightforward, so there is significant interest in finding new ways.

We all know that alcohol and tweeting is not always a good combination. Yet a surprising number of us indulge in this peculiar form of indiscretion. And this practice has given Nabil Hossain and pals at the University of Rochester an interesting idea. Today, these guys show how they've trained a machine to spot alcohol-related tweets. And they also show how to use this data to monitor alcohol-related activity and the way it is distributed throughout society.

For outsiders, the idea of artificial intelligence in the court room sounds horrifying. AI, however, has been pushing its way into law for decades. The next time you apply to claim child benefits, you may be met with the unexpected: robots. Most might not even notice it, but the future of law is heavily tied to Artificial Intelligence. In fact, the slow integration of AI into the legal sphere has been happening for decades, and several magazines, news sources and committees have been built around the topic.

South Korean Go master Lee Se-dol is now down 0-2 to Google DeepMind's AlphaGo which is on the verge of a milestone achievement in artificial intelligence. Master Se-dol has expressed surprise and amazement at the sophistication and skill of his virtual opponent. It has taken a long time to get here. Games have long been an attractive development tool for artificial intelligence researchers. In 1994, a computer program excelled at checkers and in 1997 it was chess.

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.

Rapid advances in artificial intelligence technology are raising ethical questions, as pointed out by Dr Jason Millar ("The momentous advance in artificial intelligence demands a new set of ethics", Comment). He asks whether it is desirable to develop autonomous systems that operate beyond human control. Other ethical dilemmas may arise sooner than we think. While many have poured scorn on the idea that robots could possess consciousness, if consciousness can be interpreted as an algorithm – a series of logical cause-and-effect statements – then, because the output of an algorithm is platform-independent, there is no reason in principle why that algorithm should not operate in a robot. There is a debate as to whether brain activity is algorithmic, but other forms of biological information processing are and there is no convincing evidence to the contrary.

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 ...