Radar used to be a slow science. Electronic warfare is a blanket term that encompasses the radar signals used to detect an attack, the radios used to communicate that the attack is coming, and the specific radio interference sent to confuse enemy radars as they're attacking. And in the Cold War, every part of this used to be analog. "In Vietnam we learned what an SA-2 radar signal started looking like," Joshua Niedzwiecki, director of the Sensor Processing and Exploitation group at BAE Systems, tells Popular Science. The SA-2 is a surface to air missile that destroyed a lot of U.S. Air Force planes, especially B-52 bombers, over Vietnam.
Russian President Vladimir Putin warned Friday (Sept. AI development "raises colossal opportunities and threats that are difficult to predict now," Putin said in a lecture to students, warning that "it would be strongly undesirable if someone wins a monopolist position." Future wars will be fought by autonomous drones, Putin suggested, and "when one party's drones are destroyed by drones of another, it will have no other choice but to surrender." U.N. urged to address lethal autonomous weapons AI experts worldwide are also concerned. On August 20, 116 founders of robotics and artificial intelligence companies from 26 countries, including Elon Musk and Google DeepMind's Mustafa Suleyman, signed an open letter asking the United Nations to "urgently address the challenge of lethal autonomous weapons (often called'killer robots') and ban their use internationally."
Z Advanced Computing, Inc. (ZAC) of Potomac, MD announced on August 27 that it is funded by the US Air Force, to use ZAC's detailed 3D image recognition technology, based on Explainable-AI, for drones (unmanned aerial vehicle or UAV) for aerial image/object recognition. ZAC is the first to demonstrate Explainable-AI, where various attributes and details of 3D (three dimensional) objects can be recognized from any view or angle. "With our superior approach, complex 3D objects can be recognized from any direction, using only a small number of training samples," said Dr. Saied Tadayon, CTO of ZAC. "For complex tasks, such as drone vision, you need ZAC's superior technology to handle detailed 3D image recognition." "You cannot do this with the other techniques, such as Deep Convolutional Neural Networks, even with an extremely large number of training samples. That's basically hitting the limits of the CNNs," continued Dr. Bijan Tadayon, CEO of ZAC.
Software star-up, Z Advanced Computing, Inc. (ZAC), has received funding from the U.S. Air Force to incorporate the company's 3D image recognition technology into unmanned aerial vehicles (UAVs) and drones for aerial image and object recognition. ZAC's in-house image recognition software is based on Explainable-AI (XAI), where computer-generated image results can be understood by human experts. ZAC – based in Potomac, Maryland – is the first to demonstrate XAI, where various attributes and details of 3D objects can be recognized from any view or angle. "With our superior approach, complex 3D objects can be recognized from any direction, using only a small number of training samples," says Dr. Saied Tadayon, CTO of ZAC. "You cannot do this with the other techniques, such as deep Convolutional Neural Networks (CNNs), even with an extremely large number of training samples. That's basically hitting the limits of the CNNs," adds Dr. Bijan Tadayon, CEO of ZAC.