Cyber criminals are quite adept at stealing data, money and privacy. No network is off limits as they exploit any point of weakness they find in businesses, homes, institutions, automobiles, utility networks and other portals. And their tactics evolve faster than security professionals can manage them. The question is, can we leverage technologies such as artificial intelligence (AI) and cognitive computing to win the war against cyber criminals? Cybersecurity experts shared their thoughts on this topic.

In this episode of Newsbud's Roundtable Professor Abigail Hall Blanco provides a deeper look into the driving factors behind official drone policy, who it benefits and why. We are also joined by Erik Moshe, a Newsbud Analyst & Author. We cover Erik's recent series'The New Drone Order, Part IV- Reapernomics: An Economic Way of Thinking About Drones' Follow Newsbud on Twitter http://bit.ly/29d5XFD

NSA Chief Says Without Artificial Intelligence, Cyber'Is A Losing Strategy' by Giuseppe Macri, Artificial intelligence will play a big role in the future of U.S. strategy in cyberspace, according to National Security Agency Director Adm. Michael Rogers, who told Congress Tuesday that relying primarily on human intelligence "is a losing strategy." "[We're] very much interested in artificial intelligence, machine learning, how we can do cyber at scale [and] at speed," Rogers testified before the Senate Armed Services Committee Tuesday. "Because if we're just going to take this largely human capital approach to doing business, that is a losing strategy." "It will be both incredibly resource intensive, and it will be very slow," Rogers added. "That is a big area of focus for us."

What's the best way to track drones in the sky? There is no good way to track the drones in the sky. Passenger airplanes and helicopters report their flights to air traffic control, and even if they didn't, the vehicles are large and show up easily on radar, making it possible to keep an eye on them over land. Drones, especially commercial or hobbyist drones, are small enough to appear like birds on radar. Drones are also new enough that there isn't yet a system requiring them to broadcast their location to traffic control (or even, if such a system was devised, a guarantee that all small drones could power and obey it).

"At a minimum, the documents show a pretty cozy relationship between Google and the Department of Transportation, as well as the White House," said Anne Weismann, the executive director of the Campaign for Accountability. "Google, it appears, had a lot of input into how the federal government was going to deal with driverless cars. I don't think there's necessarily anything suspicious or improper about that, but there's a fine line." The fine line Weismann describes has to do with navigating corporate and public interests as they pertain to technology that promises to transform cities, decimate and create entire industries, and save tens of millions of lives this century. It's natural that federal officials have turned to Google to educate themselves on this technology.

Data volumes are soaring to previously unimaginable heights. More data has been created in the past two years than in the entire history of humanity. It is predicted that, by 2020, each person on the planet will account for the creation of an average of 1.7 megabytes of new data every second. Scalable AI solutions could help address humanity's biggest challenges. Drawing meaningful insight from such vast amounts data is beyond our capabilities as humans, but perhaps not those of machines.

A newly declassified U.S. Air Force Arizona Air National Guard video shows how a recently installed autopilot system saved the life of an F-16 pilot who had fallen unconscious in the middle of his flight. SEE ALSO: No, it's not OK to let Tesla's Autopilot drive you to the hospital In the above video, the jet goes into a nosedive as the pilot falls unconscious. The dropping altitude is shown on the right side of the frame. In this instance, an international F-16 student pilot was undergoing basic fighter maneuver training with his USAF instructor pilot in two separate F-16s over the U.S. southwest. The student rolled and started to pull the aircraft but experienced G-induced loss of consciousness (G-LOC) as the F-16 hit around 8.3g.

Timothy Amukele, an assistant professor of pathology at Johns Hopkins Medical School in Baltimore, and systems engineer Jeff Street are trying to figure out how to use drones to deliver blood samples. Timothy Amukele, an assistant professor of pathology at Johns Hopkins Medical School in Baltimore, and systems engineer Jeff Street are trying to figure out how to use drones to deliver blood samples. Three years ago, Geoff Baird bought a drone. A Seattle dad and hobby plane enthusiast, Baird used the 2.5-pound quadcopter to photograph the Hawaiian coastline and film his son's soccer and baseball games. But his big hope is that drones will soon fly tubes of blood and other specimens to Harborview Medical Center, where he works as a clinical pathologist running the hospital's chemistry and toxicology labs.

The death of a person earlier this year while driving with Autopilot in a Tesla sedan, along with news of more crashes involving Teslas operating in Autopilot, has triggered a torrent of concerns about the safety of self-driving cars. But there is a way to improve safety across a rapidly evolving range of advanced mobility technologies and vehicles – from semi-autonomous driver assist features like Tesla's Autopilot to a fully autonomous self-driving car like Google's. The answer is connectivity: wireless communication that connects vehicles to each other, to the surrounding infrastructure, even to bicyclists and pedestrians. Joshua Brown (pictured before the crash) died earlier this year while driving with Autopilot in a Tesla sedan. With news of more crashes involving Teslas in Autopilot, people worry about the safety of self-driving cars.

Data center workloads are changing. Not long ago these systems were primarily used to handle storage and serve up web pages, but now they're increasingly tasked with AI workloads like understanding speech, text, images and video or analyzing big data for insights. Billions of consumers want instant answers to a multitude of questions, while enterprise companies want to analyze mountains of data to better serve their customers' needs. Where do those answers come from? As a leader in server systems, IBM saw this trend coming several years ago, and partnered with us to accelerate new data center workloads.