ALEX CASTRO has been patient. Ever since his teenage years, when he volunteered to work on speech-recognition projects during an internship at AT&T Bell Labs, Mr Castro has been waiting for the technology to work well enough to become widely adopted. "I always felt that voice recognition was a technology that would someday be applied to mainstream uses," he says. While waiting for "someday" to arrive, the 32-year-old had time to finish his college degree, earn a Masters at Cornell, do a stint at Microsoft's MSN Entertainment business and oversee the launch of Amazon's Mechanical Turk online marketplace. Now Mr Castro has finally started his own firm, called Pluggd, a podcast directory with a nifty audio search-engine that can search audio clips (and the soundtracks of video clips) for keywords, using speech-recognition technology.

THE teams competing in DARPA's Grand Challenge (see article) have it easy. The driverless vehicles racing off-road in the Mojave desert merely have to avoid boulders, dunes and the occasional cactus. That is nothing compared with the hazards of the open road. Put those same autonomous vehicles on Interstate 15--the busy road that links Los Angeles and Las Vegas--and they would also have to contend with bleary-eyed weekenders, huge trucks and octogenarians puttering along in mobile homes. Even so, engineers and scientists at a handful of academic and industrial research centres are valiantly grappling with the problem of designing autonomous passenger vehicles, buses and trucks.

THEY certainly cannot be faulted for a lack of ambition. The scientists and engineers who gathered this week in Oxford for the first International Workshop on Complex Agent-Based Dynamic Networks are seeking to explain much of the world's behaviour through the use of "agents". In this context, an agent is a program that acts in a self-interested manner in its dealings with numerous other agents inside a computer. This arrangement can mimic almost any interactive system: a stockmarket; a habitat; even a business supply-chain. If the constituent parts can be understood, the reasoning goes, some insight into the whole will follow.

JUST as native English-speakers stumble with Japanese, the Japanese struggle mightily with English, not to mention Korean or Chinese. In the widely used TOEFL tests of English as a foreign language, Japan invariably ranks second from bottom among the 29 countries participating in the scheme. Compared with the 150m people around the world who speak English as a second language, there are only 9m non-native speakers of Japanese--and most of those were forced to learn the language during Japan's era of colonial occupation, and are now dying of old age. For those who put their faith in technology, therefore, it was encouraging to hear Shinzo Abe, Japan's prime minister, demonstrate his linguistic skills a few weeks ago with a palm-sized gizmo that provided instantaneous translations of spoken Japanese into near-flawless English and Chinese. Mr Abe can manage perfectly well without such a device, being one of the few Japanese prime ministers in recent years to speak English fluently.

JUST below a half-opened garage door a tiny device can be seen at the feet of someone lurking in the shadows. It looks like a blue dragonfly. Then its miniature wings begin to flap as it slips under the door and darts along the street. After rising through the air it stops to hover outside the window of a building several storeys high. There is an opening on the roof, and it slips inside.

AMONG government organisations, America's Defence Advanced Research Projects Agency (DARPA) has always been somewhat unusual. As the research arm of the Department of Defence, it is akin to a high-stakes venture capitalist, gambling large sums of money (its estimated 2004 budget is $3 billion) on risky technologies that will probably fail, but could pay off in a big way. It has had some stupendous successes, such as the internet, the Saturn rocket and micro-electro-mechanical systems (tiny machines that work at the scale of a human cell). There have also been some resounding duds, such as the Total Information Awareness project, a Big Brotherish plan to spot terrorists by combing through databases of personal information, which was swiftly abandoned. But what is arguably DARPA's most outlandish scheme yet will start rolling on March 13th, when a gaggle of strange-looking vehicles will line up in Barstow, California to make a wild run across 250 miles of scrub and desert.

IS IT a new medium on a par with film and music, a valuable educational tool, a form of harmless fun or a digital menace that turns children into violent zombies? Video gaming is all these things, depending on whom you ask. Gaming has gone from a minority activity a few years ago to mass entertainment. Video games increasingly resemble films, with photorealistic images, complex plotlines and even famous actors. The next generation of games consoles--which will be launched over the next few months by Microsoft, Sony and Nintendo--will intensify the debate over gaming and its impact on society, as the industry tries to reach out to new customers and its opponents become ever more vocal. Games consoles are the most powerful mass-produced computers in the world and the new machines will offer unprecedented levels of performance.

Advances in deep learning have led Elon Musk and others to start preparing for the AI apocalypse. And indeed, by feeding terabytes into neural networks, computers are now able to understand voices, recognise faces and sift through data with unprecedented accuracy. And yet, advances in so-called unsupervised learning - which finds the structure or relationships in data inputs without training in the way that a child learns from experience - are almost non-existent. In recent years, Yann LeCun of Facebook, Geoffrey Hinton of Google and Yoshua Bengio from the University of Montreal have made significant advances in machine learning through their use of deep neural networks and other learning techniques. For example, Yaniv Taigman, one of my co-founders at face.com (which was acquired by Facebook in June 2012), recently published that the company achieved a 97.25 per cent accuracy rate for face recognition, just 0.25 per cent below human perception.

The cybersecurity industry has always been under constant strain from cybercriminals and malware. With increasing integration of hardware, software and services being built into every aspect of our lives, the task of keeping data secure has become even more difficult. The arsenal of tools that cybercriminals now have at their disposal has raised concerns for security companies, and turned the criminals into threat actors who can create, disseminate and penetrate a target's defenses using custom-built and never-before-seen malware. The security industry has had to adopt a new way of dealing with the unknown by leveraging the powerful capabilities of machine learning algorithms. Cybersecurity & Machine Learning Because targeted and advanced threats that seek to prey on organizations and businesses often evade traditional security mechanisms, machine learning algorithms have stepped in to fill in the gap between proactivity and detection.

The following letter was published in the Letters to the Editor of the February 2016 CACM (http://cacm.acm.org/magazines/2016/2/197433). Arguments for and against LAWS share this common foundation, but where Goose argued for a total ban on LAWS-related research, Ronald Arkin, in his "Counterpoint," favored a moratorium while research continues. Both sides accept international humanitarian law (IHL) as the definitive authority concerning whether or not LAWS represents a humane weapon. If I read them correctly, Goose's position was because LAWS would be able to kill on their own initiative they differ in kind from other technologically enhanced conventional weapons. That difference, he said, puts them outside the allowable scope of IHL and therefore ought to be banned.