House Armed Services Committee holds hearing on the Department of Defense using AI. The Pentagon is planning to field thousands of artificial intelligence-enabled autonomous vehicles by 2026 in a bid to keep pace with the Chinese military. The plan, which has been called Replicator, will seek to "galvanize progress in the too-slow shift of U.S. military innovation to leverage platforms that are small, smart, cheap and many," Deputy Secretary of Defense Kathleen Hicks said, according to a report by The Associated Press. While the report notes few details, including how the program will be funded and how fast the Pentagon will truly be able to accelerate the development of the new vehicles, the program represents an ongoing shift in how the U.S. views the future of warfare, especially as China continues to forge ahead with AI programs of its own. Phil Siegel, the founder of the Center for Advanced Preparedness and Threat Response Simulation (CAPTRS), believes the rapid push toward AI weapons is similar to that of a nuclear arms race.

Whether it's in novels, or the movies based on them, artificial intelligence has been a subject of fascination for decades. The synthetic humans envisioned by Philip K. Dick remain (fortunately) the stuff of science fiction, artificial intelligence is real and playing an increasingly large role in many aspects of our lives. While it's fun to root against (or maybe for) human-like robots with AI brains, a much more mundane, but equally powerful form of AI is starting to play a role in cybersecurity. The goal is for AI to be a force multiplier for hardworking security professionals. Security operations center (SOC) analysts, as we saw in the most recent Devo SOC Performance Report, are often overwhelmed by the never-ending number of alerts that hit their screens each day.

Much has been made of the use of artificial intelligence in security. Some experts will tell you it is the single biggest key to success, while others will tell you that AI is little more than marketing jargon without any real-world value. I think the truth is somewhere in the middle. AI absolutely has a place in security, but it is not a silver bullet. With that said, there are three primary ways that organizations should be using AI to act as a force multiplier for security teams. The use of AI in security should be very focused on multiplying the efforts of security teams, especially considering the current shortage of security skills.

Since joining Intel in 2010, Kelly has specialized in systems software, primarily in Linux and Linux-based operating systems, including Chrome and Android. She has led teams developing products ranging from Android phones, Ultrabook sensor based applications, and pathfinding work with artificial intelligence for thermal solutions. Career highlights include achieving the most performant Linux OS with Clear Linux, growing the robot operating system (ROS2) ecosystem for industrial applications, and teaching the'Outside In' systems engineering workshop. She holds one patent for her work on sensors and currently has another patent pending for AI applied to thermal solutions. Prior to Intel, she worked at Northrup Grumman on radars and satellite navigation systems.

Video surveillance has long been a necessary tool for law enforcement to keep communities safe and reduce crime. Yet sifting through hundreds of hours of footage can be time-consuming and slow down investigations. Video content analytics make this footage significantly more valuable by extracting, identifying and classifying video metadata, making the footage searchable, actionable and quantifiable. The ability to efficiently review, analyze, and respond to events captured by video surveillance has revolutionized law enforcement operations. Video analytics help these agencies accelerate investigations, attain situational awareness, and derive operational intelligence.

AI safety issues are becoming increasingly important. Google DeepMind and Faculty, both based in London, are devoting considerable resources to this area. But Anthropic, a San Francisco-based startup research company spun out of OpenAI, and some academic labs, including the Future of Humanity Institute in Oxford, are building expert teams in this field. "There is so little scrutiny over building very, very powerful software systems," says Hogarth. "We can plausibly have systems that exceed human capabilities in 30 years but there are fewer than 200 people in the world working on oversight and regulation."

As you have probably heard or read, IBM's Marketing Cloud recently published that "90% of world's data today has been created in the last two years alone." Growing daily at 2.5 quintillion bytes of data daily, this number will only explode over the next few years. This may seem impressive, but much of it is simply raw data. Nonetheless, you may point out that with all this data we are advancing technology, improving outcomes, enriching lives and making better decisions. However, how vastly improved these outcomes could be if all this data was enriched?

The session was moderated by Pranjal Sharma, Author, Kranti Nation: India and the Fourth Industrial Revolution.

There's untold opportunity in the mountains of data being amassed today but also the potential for harm, according to former U.S. Chief Data Scientist DJ Patil. Modern life has changed dramatically over the past decade, thanks in large part to new technologies and the ever-evolving business models they've enabled, but the fundamental transformative factor underlying it all is data. So contended DJ Patil, who served as the first chief data scientist for the United States, at the most recent Deloitte Analytics and AI Summit. Massive increases in computational power and storage are making it possible to collect, store, and analyze rapidly increasing volumes of data--currently some 2.5 quintillion bytes every day, by Patil's estimation--and the transformations that have resulted so far are just the beginning, he said. "We're about to go from sequencing the human genome to precision medicine. Autonomous vehicles have started to appear on our roads, and we'll soon see efforts to build self-driving cargo ships and airplanes as well."

At this year's DSEI, L3Harris' Stuart Gardiner explores where and when machine learning techniques can be used in modern warfare as an integrated …