But the program also intends to include different ambient setting and image sources. IARPA has selected six teams to work on new developments in identifying two primary types of behaviors: primitive activities (a person carrying an object or getting in or out of a car), and complex activities (a car arriving to pick a person up, two people exchanging an object, or a person carrying a particular object, such as a gun). The technology does not track the identity of individuals, and will be implemented to protect personal privacy.”
MOVIES ABOUT ARTIFICIAL INTELLIGENCE 2018 MANUAL
“The resulting technology will provide the ability to detect potential threats while reducing the need for manual video monitoring. “There is an increasing number of cases where officials, and the communities they represent, are tasked with viewing large stores of video footage, in an effort to locate perpetrators of attacks, or other threats to public safety,” said Terry Adams, DIVA program manager. The program wants to advance development in artificial visual perception as a way to use AI both to quickly cull through collected full-motion video, and take over live monitoring of secure areas. The Intelligence Advanced Research Projects Activity (IARPA), the scientific arm of the Office of the Director of National Defense, wants to tackle these challenges by pushing AI’s learning ability further toward a human-like cognitive realm, with a new program called Deep Intermodal Video Activity, or DIVA. The other concerns the prospect of real-time video surveillance in which machines could unblinkingly watch endless feeds from CATV and other cameras to identify suspicious activity outside a government building, inside a train station, or near a military post. The first has to do with the hundreds of thousands of hours of surveillance footage collected by airborne drones that overwhelm the capacity of human analysts to view all the video, let alone analyze it.
Machines have a bit of a challenge with moving pictures in part because unlike humans, computer systems separate processing and memory, limiting their ability to connect current activity which has already been learned.įor the intelligence community and the Department of Defense, this presents a couple of challenges. And while AI, machine learning, and neural networks have made some promising strides in this area, it’s not quite the slam dunk that it might seem.Īn artificial intelligence robot might make a formidable chess opponent or a splendid accountant, but it wouldn’t be much of a movie-watching buddy. Artificial intelligence has been applied to everything from cybersecurity and financial management to human resources and self-driving cars, so it seemed only a matter of time before it could take over video surveillance duties.