Modern sensors can see farther than humans. Electronic circuits can shoot faster than nerves and muscles can pull a trigger. Humans still outperform armed robots in knowing what to shoot at -- but new research funded in part by the Army may soon narrow that gap. Researchers from DCS Corp and the Army Research Lab fed datasets of human brain waves into a neural network -- a type of artificial intelligence -- which learned to recognize when a human is making a targeting decision. They presented their paper on it at the annual Intelligent User Interface conference in Cyprus in March.

University of Nottingham researchers created an AI system that scanned routine medical data to predict which patients would have strokes or heart attacks within 10 years. The AI system beat the standard method of prediction, correctly making calls in 355 more cases than traditional means. Predicting cardiovascular events like strokes and heart attacks is a notoriously challenging task. In fact, the researchers note in their recent paper that around half of all strokes and heart attacks occur in patients who were never identified as being "at risk." The records included a decade of health outcomes, lab data, drug information, hospital records, and demographic information.

Where is the next big marketing disruption coming from? I caught up with a host of digital experts at the CMO Digital Insight Summit to find out. Tucked away on Scotland's wild and rugged west coast, Turnberry has a special place in golfing folklore. Famous for the legendary'Duel in the Sun' between Tom Watson and Jack Nicklaus at the 1977 Open Championship – an epic display of both sport and sportsmanship – the resort has seen its fair share of intense competition over the years. And in many ways, that made it the perfect setting for the recent CMO Digital Insight Summit.

To that end, Chris founded Arago in Germany in 1995, pushing existing boundaries in AI technology to build a general AI. Since then, Chris has led Arago to become a key partner and driver for the established economy, positioning Arago's AI HIRO as a platform for companies to reinvent their business models in the digital age. As CEO of Arago, Chris Boos' vision is to transform traditional companies into future-proof, AI-enabled enterprises – regardless of their respective industry. Arago's international client base includes IT service providers, banks and companies in the telecommunications, steel and metals industries. Chris was awarded the John F. Kennedy National Leadership Award in 2003.

Newswire) Breaking Data Corp. (TSX VENTURE:BKD) (OTC PINK:BKDCD) (the "Company" or "BKD") is pleased to announce that is has now finalized its new independent Director appointees with key industry veteran leadership and experience. "We are extremely privileged to have this group of experienced and successful directors join our board," said Nick Thain, CEO. "These executives not only bring a vast network of knowledge but also have deep ties in many sports related businesses across the globe, that cross into our key markets. They will, no doubt, be valuable to our strategic and business progress." Greg D'Alba: Mr. D'Alba is currently the Co- founder & CEO of VIDL NEWS LLC, a start-up artificial intelligence news venture focused on real-time personalized news intelligence and reporting.

French presidential candidate Emmanuel Macron's campaign said Friday it has been hacked -- 9GB of authentic and fake emails were posted Friday to Pastebin, a document-sharing site, from a user named EMLEAKS, according to Reuters. The campaign said this is "déjà vu" of the kind of "democratic destabilization" that took place in the U.S. last year. Why it matters: It's less than two days before the French presidential election comes to a close, and the way that works in France includes a ban on campaigning over the weekend. The hack came hours before the ban sets in. What to watch: The polls.

Machine learning takes the heavy lifting out of interpreting and responding to the vast swathes of digital data available in the world today. The term refers to computers or software that can "learn" without being explicitly programmed. February 2016 data from Ipsos MORI for the Royal Society found that large proportions of consumers ages 15 and older in Great Britain were aware of various machine learning applications. Digital assistants, driverless cars and facial recognition applications were each cited by around three-quarters of survey respondents as technologies that they had either seen or heard about. The term "machine learning" itself, however, was much less commonly understood.

I first learned about artificial intelligence (AI) in healthcare during my undergraduate studies. As a biomedical engineering major planning a career in medicine, the concepts of AI in healthcare intrigued me. There was talk that these innovations could revolutionize medical practice in a way that would disrupt traditional physician roles. When I entered medical school, I expected to see these innovations translated into medical practice. The launch of Watson Health shortly after my medical school graduation instilled hope that these innovations would finally make it into my medical practice during residency training.

Every person on Earth got the equivalent of an extra x-ray from the Fukushima nuclear disaster, a new study claims. Researchers have carried out the first global survey of radiation exposure caused by the meltdown of three nuclear reactors at the Fukushima-Daiichi nuclear plant in Japan after a tsunami struck in 2011. They concluded that people need not panic about the dosage. Every person on Earth got the equivalent of an extra x-ray from the Fukushima nuclear disaster, a new study claims. 'We don't need to worry,' Nikolaos Evangeliou at the Norwegian Institute for Air Research, whose team conducted the tests, told the annual meeting of the European Geosciences Union in Vienna, Austria, last month, according to New Scientist.

Last week we discussed how doctors perform medicine, and what parts of the process are worth automating. It turns out that deep learning is a very good match for some of the most time consuming (and therefore costly) parts of medicine: the perceptual tasks. We also saw that many decisions simply fall out of the perceptual process; once you have identified what you are seeing or hearing, there is no more "thinking" work to do. In fact, the answers these systems arrive at can be superhuman. "In situations where the only information required to make the decision is in the signal itself, machine learning wins by a small margin." It turns out that quite a large subset of medical tasks are like this, which we will explore in more detail today. To begin with we should recognise that automating a subset of medical tasks is not the same as automating all of medicine.