Imagine a world in which healthcare can prevent disease. It's a world that is actually within our grasp. And the key to it is centralising health data to enable the use of emerging technologies, such as Artificial Intelligence (AI), Machine Learning (ML), and Predictive Analytics. Using such cutting-edge tech would enable accurate predictions on the extensive data we've captured over many years. Which in turn would catch these ailments in their early stages or even before symptoms start to manifest.

In one of the first lawsuits to address the use of live facial recognition technology by governments, a British court ruled on Wednesday that police use of the systems is acceptable and does not violate privacy and human rights. The case has been closely watched by law enforcement agencies, privacy groups and government officials because there is little legal precedent concerning the use of cameras in public spaces that scan people's faces in real time and attempt to identify them from photo databases of criminal suspects. While the technology has advanced quickly, with many companies building systems that can be used by police departments, laws and regulations have been slower to develop. The High Court dismissed the case brought by Ed Bridges, a resident of Cardiff, Wales, who said his rights were violated by the use of facial recognition by the South Wales Police. Mr. Bridges claimed that he had been recorded without permission on at least two occasions -- once while shopping and again while attending a political rally.

Researchers, including one of Indian-origin, have found that bots or fake accounts enabled by Artificial Intelligence (AI) on social media have evolved and are now able to copy human behaviour to avoid detection. For the study published in the journal First, the research team from the University of Southern California examines bot behaviour during the 2018 US presidential elections compared to bot behaviour during the 2016 US elections. "Our study further corroborates this idea that there is an arms race between bots and detection algorithms. As social media companies put more efforts to mitigate abuse and stifle automated accounts, bots evolve to mimic human strategies. Advancements in AI enable bots producing more human-like content," said study lead author Emilio Ferrara.

Eight industry-driven AI pilots will demonstrate the value of the AI-on-demand platform as a technological innovation tool. The pilots and research will showcase how AI4EU can stimulate scientific discovery and technological innovation. The AI4EU Ethics Observatory will be established to ensure the respect of human centred AI values. Sustainability will be ensured via the creation of the AI4EU Foundation. The results will feed a new and comprehensive Strategic Research Innovation Agenda for Europe.

Cybersecurity, a huge industry worth over $100 billion, is regularly subject to buzzwords. Cybersecurity companies often (pretend) to use new state-of-the-art technologies to attract customers and sell their solutions. Naturally, with artificial intelligence being in one of its craziest hype cycles, we're seeing plenty of solutions that claim to use machine learning, deep learning and other AI-related technologies to automatically secure the networks and digital assets of their clients. But contrary to what many companies profess, machine learning is not a silver bullet that will automatically protect individuals and organizations against security threats, says Ilia Kolochenko, CEO of ImmuniWeb, a company that uses AI to test the security of web and mobile applications. While machine learning and other AI techniques will help improve the speed and quality of cybersecurity solutions, they will not be a replacement for many of the basic practices that companies often neglect.

Leaders of the Air Force, Navy, Army and Marines are converging on a vision of the future military: connecting every asset on the global battlefield. That means everything from F-35 jets overhead to the destroyers on the sea to the armor of the tanks crawling over the land to the multiplying devices in every troops' pockets. Every weapon, vehicle, and device connected, sharing data, constantly aware of the presence and state of every other node in a truly global network. The effect: an unimaginably large cephapoloidal nervous system armed with the world's most sophisticated weaponry. In recent months, the Joint Chiefs of Staff put together the newest version of their National Military Strategy.

A recent Forbes Insights survey and report based on the responses of over 200 chief information security officers (CISOs) showed the tough choices they must make as they face "an arms race between the capabilities of attackers and their own defense postures."[1] Every CISO is acutely aware of the double-edged sword presented by the use of AI technologies such as machine learning: They are increasingly being deployed by malicious actors as an offensive tool that can automate many of the tasks in building a weapon, at lower cost and with greater efficiency. That's why the other edge of the sword--a strong, automated defensive bulwark--is critical for enterprises to secure their vast environments. For Emily Heath, vice president and chief information security officer at United, the global airline, one of the key benefits of automation through machine learning is visibility into the network--understanding what is normal or anomalous activity. "Without a machine to help you, you can't possibly weed through millions and tens of millions of events that happen across the data flow," she says.

AS THE NAVY plane swooped low over the jungle, it dropped a bundle of devices into the canopy below. Some were microphones, listening for guerrilla footsteps or truck ignitions. Others were seismic detectors, attuned to minute vibrations in the ground. Strangest of all were the olfactory sensors, sniffing out ammonia in human urine. Tens of thousands of these electronic organs beamed their data to drones and on to computers.

A country's dexterity with artificial intelligence technology might be the next strong source of national pride and international power. Knowing it would lay the foundation for the future of medicine, IBM captured the world's imagination in 2011 with Watson, a supercomputer that not only won Jeopardy!, but beat trivia superstar Ken Jennings in the process. The novel cognitive computing technology was quickly adapted to "read" the thousands of medical research papers published weekly in order to diagnose cancer patients more accurately than human doctors seemingly could. It's a banner technology for IBM, a company that remains no slouch in its 105 years of operation Now five years after Watson's debut, Japanese researchers at Kyoto University and Fujitsu are collaborating to build their own computing technology that's fairly characterized as a response to Watson. Skipping the game shows and going straight to medical applications, the Japanese system aims to close the gap in understanding how our genes determine our health by accounting for a patient's genetic code in its computer-generated diagnoses.

A country's dexterity with artificial intelligence technology might be the next strong source of national pride and international power. Knowing it would lay the foundation for the future of medicine, IBM captured the world's imagination in 2011 with Watson, a supercomputer that not only won Jeopardy!, but beat trivia superstar Ken Jennings in the process. The novel cognitive computing technology was quickly adapted to "read" the thousands of medical research papers published weekly in order to diagnose cancer patients more accurately than human doctors seemingly could. It's a banner technology for IBM, a company that remains no slouch in its 105 years of operation Now five years after Watson's debut, Japanese researchers at Kyoto University and Fujitsu are collaborating to build their own computing technology that's fairly characterized as a response to Watson. Skipping the game shows and going straight to medical applications, the Japanese system aims to close the gap in understanding how our genes determine our health by accounting for a patient's genetic code in its computer-generated diagnoses.