More than six billion dollars: That's how much health care providers and consumers will be spending every year on artificial intelligence tools by 2021--a tenfold increase from today--according to a new report from research firm Frost & Sullivan. AI will be everywhere--from diagnosing cancer to providing weight-loss coaching, says Venkat Rajan, who has the great title of global director for the company's Visionary Healthcare Program. "Prior to 2015, most of what was happening was sort of academic: pilot programs, exploratory, proof of concept-type stuff," he says. AI's ability to sort through scads of information, and remember everything it has ever seen, could enable a digital (and congenial) version of Dr. House, the brilliant diagnostician from the eponymous TV show, says Rajan. "At first, it's a complete mystery, it could be one of ten different things," he says, about the process in the show, and real life, called differential diagnosis. "And then he's able to sort through various issues, you know, illuminate certain factors on why it's not one of these other conditions, and he's able to pull something from memory that figures out ultimately what it is, and they can provide the appropriate treatment." Robots won't steal doctors' jobs, says Rajan, but they will spare overworked docs some of the dangerous fatigue that can lead to mistakes.

ToyTalk, the startup that mashed together Barbie and the Internet of Things and let your kids chat away with Thomas the Tank Engine for hours on end, is cashing out on the bot craze with a slight realignment of philosophy -- and a new name. "When working with children," the company's CEO Oren Jacob said, "you are beholden to some pretty strict laws, and ToyTalk as a company had to work diligently to ensure we toe the line." To do that, the company developed a whole toolset to enable writers to create narratives for children's toys. The toolset was called PullString, named after the string you can pull on some dolls to make them talk. The name is undoubtedly a nod to the Andy cowboy doll from Toy Story -- Jacob did head up Pixar's technical team as its CTO, after all.

In his newly published scan of the literature, expert Thomas B. Sheridan concludes that the time is ripe for human factors researchers to contribute scientific insights that can tackle the many challenges of human-robot interaction. Massachusetts Institute of Technology Professor Emeritus Sheridan, who for decades has studied humans and automation, looked at self-driving cars and highly automated transit systems; routine tasks such as the delivery of packages in Amazon warehouses; devices that handle tasks in hazardous or inaccessible environments, such as the Fukushima nuclear plant; and robots that engage in social interaction (Barbies). In each case, he noted significant human factors challenges, particularly concerning safety. No human driver, he claims, will stay alert to take over control of a Google car quickly enough should the automation fail. Nor does self-driving car technology consider the value of social interaction between drivers such as eye contact and hand signals.

Global law firm Baker & McKenzie has paired with Euromoney Thought Leadership to reveal what is driving the global financial services industry towards a rapid embrace of Artificial Intelligence and Machine Learning, and the implications both for the industry and financial markets as a whole. Ghosts in the machine: Artificial intelligence, risks and regulation in financial markets shows an industry rapidly seeing the potential benefits of AI, while being increasingly concerned about risk and the ability of regulators to keep pace. The survey asked 424 senior executives from financial institutions and fintech companies around the world as well as leading experts in the field for their view on how AI will affect the financial sector, what risks and benefits AI will bring to the sector, what the associated regulatory and legal challenges will be and many more questions. Surprisingly similar views emerged from across the globe, with only a few notable variations, such as AI investment seen as lagging slightly in Asia Pacific compared to other regions and Latin American participants seeing AI as a regulatory tool to combat money laundering first rather than market misconduct, the top choice elsewhere. The results provide some insights into the likely future of the financial sector.

Imagine a human being born on the cusp of a robotic revolution. At first, when the machines take over the economy, Bill is stoked. He wakes up late every morning, smokes some 22nd century weed and then watches TV. His degree in accounting has become worthless, because there is nothing he could do that couldn't be done better by a machine. Bill plugs his brain into a virtual world, becomes obsessed with killing dragons and winning digital gold, and dies shriveled and alone as a level 900 paladin.

Here's a scene from our digital future: You sit down to dinner at a restaurant where your server was selected by a "robo-boss" based on an optimized match of personality and interaction profile, and the angle at which he presents your plate, or how quickly he smiles can be evaluated for further review. Or, perhaps you walk into a store to try on clothes and ask the digital customer assistant embedded in the mirror to recommend an outfit in your size, in stock and on sale. Afterwards, you simply tell it to bill you from your mobile and skip the checkout line. These scenarios describe two predictions in what will be an algorithmic and smart machine driven world where people and machines must define harmonious relationships. In his session at Gartner Symposium/ITxpo 2016 in Orlando, Daryl Plummer, vice president, distinguished analyst and Gartner Fellow, discussed how Gartner's Top Predictions begin to separate us from the mere notion of technology adoption and draw us more deeply into issues surrounding what it means to be human in a digital world.

Emotionally intelligent computers are already changing how we see ourselves as humans. As we make computers more human, we learn more about us. This has already changed how we see our skills, talents and intelligence. How we see emotional intelligence, personalities and leadership will change too. Computers can now read our emotions by reading our faces.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

American Academy of Arts and Sciences welcomes Carnegie Mellon's Tom Mitchell On Wednesday, April 20, the American Academy of Arts and Sciences (AAAS) announced its 2016 member class, which included Tom Mitchell, a member of Carnegie Mellon's Machine Learning Department. Mitchell has been with Carnegie Mellon since 1986 and was named Fredkin University Professor of Artificial Intelligence and Machine Learning. Mitchell also served for 10 years as the founding head of the Machine Learning Department. His research focuses on learning algorithms, with particular interest in analyzing MRIs to model brain cognition. In addition to his new membership in the AAAS, he has also been elected fellow of the American Association for the Advancement of Science, and served for two years as President of the Association for the Advancement of Artificial Intelligence.

Dreams are successions of images, ideas, emotions, and sensations that occur usually involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]