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.

Hewlett Packard Enterprise Co., having backed away from a key portion of the cloud computing-on-demand market, is expanding into cloud services to help companies analyze data such as photos, audio clips and comments on social media. Haven OnDemand, which runs on computers operated by Microsoft Corp.'s Azure cloud-computing division, gives users access to sophisticated techniques such as machine learning without the need to maintain...

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.

Google is teaching its artificial intelligence how to understand language by making it predict, and replicate, the works of famous dead authors. The company is building systems that are capable of understanding natural language in the same way humans do, with the works of William Shakespeare, Mark Twain and others currently being analysed. "This work has the potential to enrich products through personalisation," Marc Pickett from Google's Natural Language Understanding research group wrote in a recent blog post. Researchers training the deep neural network -- using the work of authors from Project Gutenberg -- fed the AI an input sentence and asked it to say what would come next. The network is given millions of lines from a "jumble" of authors and then works out the style of individual writers.

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.

Machine Learning is a subfield within Artificial Intelligence that builds algorithms that allow computers to learn to perform tasks from data instead of being explicitly programmed. We can make machines learn to do things! The first time I heard that, it blew my mind. That means that we can program computers to learn things by themselves! The ability of learning is one of the most important aspects of intelligence. Translating that power to machines, sounds like a huge step towards making them more intelligent. And in fact, Machine Learning is the area that is making most of the progress in Artificial Intelligence today; being a trendy topic right now and pushing the possibility to have more intelligent machines.