After great promise in the 1960s that machines would soon think like humans, progress stalled for decades. Only in the past 10 years or so has research picked up, and now there are several popular products on the market that do a decent job of at least recognizing spoken speech. For Björn Schuller, full professor and head of the chair of Complex and Intelligent Systems at the University of Passau, Germany, who grew up watching Knight Rider--a television show about a car that could talk--this is the fulfillment of a childhood fantasy. Schuller is a World Economic Forum Young Scientist who will speak at the World Economic Forum's Annual Meeting of the New Champions in Tianjin, China, from June 26 to 28.He recently spoke about the possibility of machines soon tuning in to human language quirks, behavior and emotion. How did you get interested in machine intelligence and speech recognition?

We need to make data the centre of what we're doing, to be able to achieve the benefits of AI, says Deborah El-Sayed, Director of Digital & Multi-Channel Development at NHS England. And it has to be a collective process - because everyone, whether from academia, a provider organisation or clinician, has a piece of the jigsaw. AI and the NHS might at first glance seem uneasy bedfellows. Are the two an unlikely combination – or a match made in heaven? I think that we've hit a kind of tipping point in healthcare. People are living longer – which is a triumph; our expectations as healthcare consumers are growing and because we're surviving more conditions because we have better healthcare, we've got more complexities and more comorbidities.

A school in London is set to become the first in Britain to welcome a robot teacher when it opens in September. The humanoid robot, known as Pepper, will be used in classrooms at the London Design and Engineering University Technical College, to help teach pupils about cutting-edge robotics. It will be the first instance of an educational robot being used in a UK classroom. Claims made by an expert in artificial intelligence predict that in less than five years, office jobs will disappear completely to the point where machines will replace humans. The idea that robots will one day be able to do all low-skilled jobs is not new, but Andrew Anderson from UK artificial intelligence company, Celaton, said the pace of advance is much faster than originally thought.

There's always one game at E3 that proves, counter to the general theme of the show, bigger isn't always better. This year, a tiny studio named Compulsion found itself thrust into the limelight after its project We Happy Few caused a considerable splash at Microsoft's press conference. But as a black comedy set in a dystopian Britain being destroyed by a vast group hallucination, it may now take on more profound and pressing connotations following last night's result. For some, this strange combination of 1984, A Clockwork Orange and Bioshock feels very much the game of the moment. The opening of the E3 demo, which momentarily silenced the usual energetic whooping, evoked the spirit of another wonderful introductory sequence, from Terry Gilliam's seminal 1985 film Brazil.

In an unassuming building on the outskirts of Budapest engineers working for small Hungarian security firm BalaBit have spent the last three years working on technology its makers are convinced can contain one of cybersecurity's most intractable woes. In 2014 the relatively unknown firm launched a system called Blindspotter which, as its name suggests, gives its customers mostly in finance and telco sector buyers the ability to see things most networks barely acknowledge as existing let alone attempt to look for. Blindspotter is designed to watch what network users are doing in a lot of detail, a boon for organisations that worry about user credentials being abused, either deliberately from within by attackers who've somehow pilfered them. When used in conjunction with the firm's network proxy appliance, Shell Control Box (SCB), organisations suddenly have the ability to monitor their whole infrastructure using measurements of user behaviour rather than packets, ports and protocols. The system's real intrigue isn't what it does – cybersecurity is already chock full of network monitoring in different forms – so much as how it does it.

NEW YORK – Here in the United States, the horrific shooting at a night club in Orlando, Florida, that killed 49 people has intensified the debate once again over the extent leaders must go to fight terrorism and gun violence. In the immediate aftermath of the tragedy, the contrasting responses of Hillary Clinton and Donald Trump and their attacks on one another suggest that a mud-slinging showdown between the two would-be national leaders is on track. And a world away, in the Philippines, the rhetoric surrounding the battle against terrorists and criminals is equally sensational. The one-time student of U.S. democracy has recently elected a leader of its own in political incorrectness. Who would have thought a man who vowed to kill criminals and grant himself a presidential pardon, who boasts of being a womanizer, has joked about wanting to rape a missionary and talked of the killing of journalists, would win a popular election and become head of state. Such is the dramatic turn of events in the Philippines, a nation shaped by centuries of Spanish and then by decades of American colonial rule.

By the end of this article, you'll understand how Numerai is using advances in cryptography like homomorphic encryption to allow for open participation in the problem of stock market efficiency. Over the last few years, machine learning algorithms solved big problems in computer vision. One such problem was getting an algorithm to learn how to recognize handwritten digits in the MNIST dataset. Everyone writes digits differently, so the problem was difficult for computers to grasp. When the dataset first became available in 1998, machine learning algorithms for computer vision were not very accurate.

That's just one of "five practical research problems" proposed by scientists at Google, OpenAI, Stanford and Berkeley in a paper called "Concrete Problems in AI Safety" (pdf). Others included "safe exploration" issues, or how to stop a curious cleaning robot from sticking a wet mop in an electrical socket, and "avoiding negative side effects" such as a robot breaking granny's vase when cleaning in a rush. The problems may seem a bit silly, when compared to an AI-induced doomsday, but Google researcher Chris Olah wrote, "These are all forward thinking, long-term research questions – minor issues today, but important to address for future systems." A particularly interesting portion of the paper was devoted to avoiding reward hacking, or how to stop AI from gaming its reward function. "Imagine that an agent discovers a buffer overflow in its reward function: it may then use this to get extremely high reward in an unintended way."

AI is coming for your paintbrush too… A new iOS app, called Prisma, is using deep learning algorithms to turn smartphone photos into stylized artworks based on different artwork/graphical styles. Snap or choose your photo, select an'art filter' to be applied and then wait as the app works its algorithmic magic -- returning your stylized image in a matter of seconds, along with options to share it to your social networks. So if you've ever wanted your bedroom to resemble a rotoscope animation, or your selfie to have shades of manga, or your hopeless sketching skills not to hold back your yearning to create a web comic then Prisma is definitely the app for you… Prisma was launched only last week but has already garnered some 1.6 million downloads, CEO and co-founder Alexey Moiseenkov tells TechCrunch, on the phone from Moscow where the team is currently based. The key to this early growth is clearly the app's prominently placed social share function, which prompts users to post to Instagram as soon as they receive their processed shot. And just this week the Facebook-owned photo-sharing behemoth revealed it had more than doubled its monthly active users over the past two years -- reaching a whopping 500 million MAUs.

Learned experts in the field of science and technology have had predicted how'Artificial Intelligence' may take over the world. On close heels, a Russian robot appears to have'escaped' the research lab in which it was housed. Do you know what's more weird? It is the second time the bot has tried to flee the lab in just a span of two weeks, according to news reports. Engineers at the Russian lab reprogrammed the intelligent machine, dubbed Promobot IR77, after last week's incident, but the robot recently made a second escape attempt, The Mirror reported. Reportedly, in its first effort to flee last week, the robot almost made 50 meters into the street before it got'partially paralyzed' due to power exhaustion.