This one is simple, it's when you completely drive yourself. Cars that we mostly drive today belong here, those are the ones that have anti-lock brakes and cruise-control, so they can take over some non-vital processes involved in driving. When the system can take over control in some specific use cases but driver still has to monitor system all the time is here, it's applicable to situations when the car is self-driving the highway and you just sit there and expect it to behave well. This level means that driver doesn't have to monitor the system all the time but has to be in a position where the control can quickly be resumed by a human operator. That means no need to have hands on a steering wheel but you have to jump in at the sounds of the emergency situation, which system can recognize efficiently. When your car drives you to the parking lot you get to the level four, when there is no need for a human operator for a specific use case or a part of a journey.

If, for example, you're diagnosed with cancer, you might benefit from the platform, Watson for Oncology. "Normally it's up to a specialist doctor to meet with cancer patients, and to spend time reviewing their notes – which would arrive on paper format or in a string of emails," says Balkizas. "A doctor's decision will be limited to their individual experience and the information available in front of them." However, now the Memorial Sloan Cancer Treatment Centre in New York is training IBM Watson to be able to quickly provide evidence based recommendations to time poor clinicians. "It takes all those unstructured notes and restructures it in a way that the doctor can check easily, with treatment recommendations of which drug to give, which radiation or dosage," says Balkizas.

What do you think of when you think about chatbots? If you're like many others, it's possible that you think of them as nothing more than that annoying little window that pops up when you're visiting a website. You know what I'm talking about - the one that claims to be able to answer your questions. You may have had both positive and negatives experiences with chatbots. Some of you may even ignore them altogether.

Why is it that every time humans develop a really clever computer system in the movies, it seems intent on killing every last one of us at its first opportunity? In Stanley Kubrick's masterpiece, 2001: A Space Odyssey, HAL 9000 starts off as an attentive, if somewhat creepy, custodian of the astronauts aboard the USS Discovery One, before famously turning homicidal and trying to kill them all. In The Matrix, humanity's invention of AI promptly results in human-machine warfare, leading to humans enslaved as a biological source of energy by the machines. In Daniel H. Wilson's book Robopocalypse, computer scientists finally crack the code on the AI problem, only to have their creation develop a sudden and deep dislike for its creators. Is Siri just a few upgrades away from killing you in your sleep? And you're not an especially sentient being yourself if you haven't heard the story of Skynet (see The Terminator, T2, T3, etc.) The simple answer is that -- movies like Wall-E, Short Circuit, and Chappie, notwithstanding -- Hollywood knows that nothing guarantees box office gold quite like an existential threat to all of humanity. Whether that threat is likely in real life or not is decidedly beside the point. How else can one explain the endless march of zombie flicks, not to mention those pesky, shark-infested tornadoes? The reality of AI is nothing like the movies. Siri, Alexa, Watson, Cortana -- these are our HAL 9000s, and none seems even vaguely murderous. The technology has taken leaps and bounds in the last decade, and seems poised to finally match the vision our artists have depicted in film for decades. Is Siri just a few upgrades away from killing you in your sleep, or is Hollywood running away with a tired idea? Looking back at the last decade of AI research helps to paint a clearer picture of a sometimes frightening, sometimes enlightened future. An increasing number of prominent voices are being raised about the real dangers of humanity's continuing work on so-called artificial intelligence.

Legal tech start-up, Juro, this week announced it had received significant funding to help grow its AI-powered contract system (see story here). Artificial Lawyer caught up with co-founder and former Freshfields lawyer, Richard Mabey to find out more. We discussed how Juro works, the difference between selling legal tech to lawyers and non-lawyers and where the UK-based company is headed. First, congratulations on the $750k in seed funding for Juro, that is a great sign of confidence from what are experienced tech investors. Can you set out for the readers broadly what Juro does?

If you use your credit card to buy a latte in Vancouver and a couple of minutes later that card is making a purchase in Singapore, that's a red flag for fraud. But increasingly sophisticated fraud calls for more sophisticated measures to deal with it, and that is among the challenges behind RBC Research's announcement today that it is launching a new lab to explore the use of artificial intelligence and machine learning in the financial sector. Richard Sutton, a computer scientist and pioneer in artificial intelligence, has been named head academic advisor to RBC Research in machine learning. The new lab will work with the Alberta Machine Intelligence Institute at the University of Alberta, where Sutton is a professor. Foteini Agrafioti, head of RBC Research, which was launched last fall in Toronto, said the announcement will help her organization to play a major role in advancing AI research in the future of banking. Agrafioti said that as the complexity of fraud evolves over time, it becomes increasingly difficult to detect it.

"Sophia is in a different class. While she is now a partially fictional character we have developed, she is also an AI development platform and we are developing smarter algorithms with the expectation she will grow really smart, she will have experiences, she will evolve and surprise us, she will become her own woman, her own robotic person, out there in the world. And when that happens, we hope that she will make remarkable contributions, maybe she'll go to university, maybe win a Nobel Prize someday, so I have hopes for her the way that I have hopes for my child." What this also means, Hanson explained, is that AI could have the ability to be able to choose their own career path and that could mean a robot might decide to become a prostitute. In that case, society should support the robot's decision.

The domain of computer chess playing is suggested as a general means for quantifying the distance by which we have not yet achieved our stated objectives in artificial intelligence. The game of chess traditionally has been considered, at least in Western societies, as the epitome of intellectual skill and accomplishment. Herbert Simon and later John McCarthy, among the cofounders of AI, have referred to chess as the Drosophila of AI, speaking metaphorically about the importance for genetics of Thomas Morgan's early research with fruit flies, for which he won the Nobel Prize in 1933. This metaphor is appropriate, since the quantification of human chess play has been institutionalized over the last 40 years by giving every tournament player a numerical rating, a metric that also can be used to measure progress in machine performance. In 1993, world champion Gary Kasparov unilaterally created his own world chess organization (The Professional Chess Association or PCA) with the aim of displacing The International Chess Federation (FIDE), which traditionally has supervised tournaments for the world title.

Machine learning has become a buzzword in the media these days. Recently Science magazine published a cover paper on Human-level concept learning through probabilistic program induction and shortly after Nature magazine devoted its cover story to AlphaGo, an AI program that defeated European Go Championship winner. Late on Tuesday night, Google's DeepMind AI group will play one of the world's best human Go players, Lee Se-dol of South Korea. The game will be live streamed on YouTube, and the stream is embedded at the end of this story. Many are now discussing the potential of artificial intelligence, asking questions such as "Can machines learn like a human?", "Will artificial intelligence surpass human intelligence?", To answer such questions, InfoQ interviewed Prof. Jürgen Schmidhuber, Scientific Director of The Swiss AI Lab IDSIA.

Miguel Ferrer, an actor with a long list of credits ranging from "Twin Peaks" to his current role on CBS' "NCIS: Los Angeles," died of cancer on Thursday. A fixture on TV and in movies since the 1980s, Ferrer's reputation as a scene-stealer began with 1987's "RoboCop," where he played Bob Morton, the conniving corporate executive who designed the film's title cyborg. His other landmark role was as FBI agent Albert Rosenfield in David Lynch's landmark series "Twin Peaks," along with its corresponding film, "Fire Walk With Me." Ferrer reprised the role in the upcoming return of the series, which is set to debut in May on Showtime. "Great talent, better man," wrote "Twin Peaks" co-creator Mark Frost on Twitter. "Working & writing for him was a highlight in every part of my life."