BEGIN ARTICLE PREVIEW: Senvol was awarded a United States Army Research Laboratory (ARL) contract to apply its machine learning software, Senvol ML, to rapidly design additive manufactured parts. The software allows the Army to qualify parts across AM processes and platforms, thus reducing the Army’s supply chain lead time. By leveraging ML algorithms, the qualification plan will also be notably more efficient than more traditional qualification plans (i.e. require fewer builds and less time). Senvol’s partners on the program include Lockheed Martin Missiles and Fire Control, EWI, and Pilgrim Consulting. The contract is administered by the National Center for Manufacturing Sciences (NCMS) through the Advanced Manufacturing, Materials, and Processes Program (AMMP) program. Ms. Stephanie Koch, ARL’s Manager, said that “Additive manufacturing is a promising technology that could be used to enable multiple Army Modernization Priorities applications. Despite the poten
A machine learning algorithm has shown the ability to link specific behaviors, such as walking and breathing, to their related brain signals – a first step to developing brain-machine interfaces. The algorithm, funded by the US Army, was tested on two monkeys that made various arm and eye movements. The technology successfully isolated the neural patterns in each of the animal's brain signals and determined which control these specific movements. The brain decoding algorithm could be designed to restore lost functions in those suffering with neurological and mental disorders. Although the algorithm is still in the development phase, the team sees it being used in brain-machine interfaces.
WASHINGTON -- The U.S. Army's heavy common ground robot has reached full-rate production, less than a year after FLIR won the contract to deliver the system, FLIR's vice president in charge of unmanned ground systems told Defense News in an interview this month. "We've progressed with the U.S. Army through all the milestones on the program and are now at full-rate production on the program. We're building systems, we're delivering them, there are systems out at Fort Leonard Wood right now going through training with troops and there are more systems in the pipeline to be delivered all the way through next year and further," Tom Frost said. "I think what's remarkable is how quickly the Army was able to run a program to find a very capable, large [explosive ordnance disposal] robot and then get it out to troops as quickly as they did," he added. The service award FLIR an Other Transaction Authority type contract in November 2019 to provide its Kobra robot to serve as its Common Robotic System-Heavy -- or CRS-H.
Future near-peer adversaries will attempt to contest all domains and utilize complex and congested terrain to mitigate current joint force capabilities and reduce effectiveness of U.S. Department of Defense (DoD) tactical maneuver elements. During Potomac Officers Club's Artificial Intelligence for Maneuver Virtual Event, a panel of expert speakers across the public and private sectors will discuss how the federal government, and its industry partners, can deter or defeat peer threats in contested multi-domain environments. To register for Artificial Intelligence for Maneuver Virtual Event, as well as learn about new upcoming opportunities, visit Potomac Officers Club's Event Page. Christian Dunbar of the Department of the Navy, the panelist will discuss how advances in artificial intelligence and machine learning algorithms can enable human-machine teams to bring greater precision, certainty, speed and mass to the battlefield. The panel will be moderated by Joel Dillon, vice president of Global Defense, Army Account, with Booz Allen Hamilton.
Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The U.S. Army will soon operate robots able to destroy enemy armored vehicles with anti-tank missiles, surveil warzones under heavy enemy fire and beam back identified targeting details in seconds due to rapid progress with several new armed robot programs. Several of the new platforms now operate with a Kongsberg-built first-of-its-kind wireless fire control architecture for a robotic armored turret with machine guns, Javelin Anti-Tank Missiles and robot-mounted 30mm cannon selected by the Army to arm its fast-emerging Robotic Combat Vehicles. These now-in-development robotic systems are intended to network with manned vehicles in high-risk combat operations.
On a bright Tuesday afternoon in Paris last fall, Alex Karp was doing tai chi in the Luxembourg Gardens. He wore blue Nike sweatpants, a blue polo shirt, orange socks, charcoal-gray sneakers and white-framed sunglasses with red accents that inevitably drew attention to his most distinctive feature, a tangle of salt-and-pepper hair rising skyward from his head. Under a canopy of chestnut trees, Karp executed a series of elegant tai chi and qigong moves, shifting the pebbles and dirt gently under his feet as he twisted and turned. A group of teenagers watched in amusement. After 10 minutes or so, Karp walked to a nearby bench, where one of his bodyguards had placed a cooler and what looked like an instrument case. The cooler held several bottles of the nonalcoholic German beer that Karp drinks (he would crack one open on the way out of the park). The case contained a wooden sword, which he needed for the next part of his routine. "I brought a real sword the last time I was here, but the police stopped me," he said matter of factly as he began slashing the air with the sword. Those gendarmes evidently didn't know that Karp, far from being a public menace, was the chief executive of an American company whose software has been deployed on behalf of public safety in France. The company, Palantir Technologies, is named after the seeing stones in J.R.R. Tolkien's "The Lord of the Rings." Its two primary software programs, Gotham and Foundry, gather and process vast quantities of data in order to identify connections, patterns and trends that might elude human analysts. The stated goal of all this "data integration" is to help organizations make better decisions, and many of Palantir's customers consider its technology to be transformative. Karp claims a loftier ambition, however. "We built our company to support the West," he says. To that end, Palantir says it does not do business in countries that it considers adversarial to the U.S. and its allies, namely China and Russia. In the company's early days, Palantir employees, invoking Tolkien, described their mission as "saving the shire." The brainchild of Karp's friend and law-school classmate Peter Thiel, Palantir was founded in 2003. It was seeded in part by In-Q-Tel, the C.I.A.'s venture-capital arm, and the C.I.A. remains a client. Palantir's technology is rumored to have been used to track down Osama bin Laden -- a claim that has never been verified but one that has conferred an enduring mystique on the company. These days, Palantir is used for counterterrorism by a number of Western governments.
This is normally the time when we start buying candy corn for trick or treaters. But this year is horrifying no matter who comes to the door. After years of investigations, hearings, and the rattling of legal sabers, we finally have a Techlash case: United States of America, et al. v. Google LLC. As I wrote earlier in the week, the government made a direct comparison to the Microsoft case two decades earlier, where it also invoked the trust-busting Sherman Act. In that litigation, the key issue was whether or not Microsoft leveraged its market power to jam its browser down the throats of users.
U.S. Soldiers, assigned to the 1st Squadron, 2d Cavalry Regiment, scan sectors of fire during the AH-64 Apache helicopter gunnery training in Grafenwoehr Training Area, Germany, July 15, 2020. The gunnery training concluded with the squadron's table VIII and IX live-fire certifications. LaShic Patterson) For future battlefield operations, speed is the name of the game. The side that can make decisions faster has the advantage.A new, AI-enabled effort by the U.S. Army can give operators the ability to detect, identify, process and engage targets quicker than ever and at longer ranges than before. The Tactical Intelligence Targeting Access Node, or TITAN, offers frontline forces, as well as headquarter commanders, a resilient tactical ground station capable of rapidly sifting through massive amounts of incoming sensor data to find and track potential threats.
With the addition of artificial intelligence and machine learning, the aim is to make every soldier, regardless of job specialty, capable of identifying and knocking down threatening drones. While much of that mission used to reside mostly in the air defense community, those attacks can strike any infantry squad or tank battalion. The goal is to reduce cognitive burden and operator stress when dealing with an array of aerial threats that now plague units of any size, in any theater. "Everyone is counter-UAS," said Col. Marc Pelini, division chief for capabilities and requirements at the Joint Counter-Unmanned Aircraft Systems Office, or JCO. Army units aren't ready to defeat aerial drones, the study shows.
Last month, an artificial intelligence agent defeated human F-16 pilots in a Defense Advanced Research Projects Agency challenge, reigniting discussions about lethal AI and whether it can be trusted. Allies, non-government organizations, and even the U.S. Defense Department have weighed in on whether AI systems can be trusted. But why is the U.S. military worried about trusting algorithms when it does not even trust its AI developers? Any organization's adoption of AI and machine learning requires three technical tools: usable digital data that machine learning algorithms learn from, computational capabilities to power the learning process, and the development environment that engineers use to code. However, the military's precious few uniformed data scientists, machine learning engineers, and data engineers who create AI-enabled applications are currently hamstrung by a lack of access to these tools.