September 27, 2021 | International, C4ISR
The radios provide critical capabilities allowing forces multiple paths of communication.
November 16, 2023 | International, Land
Amazon.com said on Thursday its two prototype satellites for its planned Kuiper internet network have been operating successfully in orbit, with the project on track to start launching operational satellites by mid-2024.
June 19, 2019 | International, Aerospace, Other Defence
By: Seth J. Frantzman and Kelsey D. Atherton Rafael Advanced Defense System's Spice bombs now have a new technological breakthrough as the Israeli company enables its Spice 250 with artificial intelligence alongside automatic target recognition to be used with scene-matching technology. The Spice 250, which can be deployed on quad racks under the wings of warplanes like the F-16, has a 75-kilogram warhead and a maximum range of 100 kilometers with its deployable wings. Its electro-optic scene-matching technology — which involves uploading terrain data onto the bomb and combining it with real-time electro-optic imagery — allows the weapon to work in GPS-denied environments. And the bomb can use this autonomous capability to navigate and correct its location, according to Gideon Weiss, Rafael's deputy general manager of marketing and business development at the company's air and C4I division. With its AI and “deep learning” technologies, the weapon has the ability to identity moving ground targets and distinguish them from other objects and terrain. This is based on 3D models uploaded to the bomb as well as algorithms. As the weapon identifies and homes in on its target, such as a convoy of vehicles, it separates the convoy of interest from other vehicles it has “learned” to ignore. “The deep-learning algorithm is indifferent to the actual data fed to it for modeling targets of interest and embedding their pertaining characteristics into the system," Weiss said. "However, the more the data used for modeling is representative of the target of interest, the more robust the recognition probability will be in real life.” Rafael has completed the development and testing phase of the Spice 250, including flight tests, which have “proven the robustness of the ATA and ATR, so it is mature for delivery,” Weiss said, using acronyms for automatic target acquisition and recognition. Asked if the ATR algorithm will select a secondary target if the computer cannot find the initial human-selected target, Weiss said: “This goes into the area of user-defined policies and rules of engagement, and it is up to the users to decide on how to apply the weapon, when and where to use it, and how to define target recognition probabilities and its eventuality.” Automatically selecting a secondary target may eventually become part of the upgrade profile for the munition, if customers express significant interest in the feature. With a two-way data link and a video-streaming capability, the bomb can be aborted or told to re-target up until a “few second before the weapon hits its target,” Weiss explained. That two-way data-link, enabled by the weapon's mounting on a Smart Quad Rack, or SQR, will enable future deep learning to be based on data extracted from earlier launches. Data recorded will include either live-streaming video or a burst of still images of the entire homing phase up until impact. “These are automatically and simultaneously recorded on the SQR — enabling two functions: (a) real-time and post-mission BDI (Bomb Damage Indication); (b) post-mission target data extraction for intel updates, etc.," Weiss said. "The ATR capability, including its deep learning updates, must be more agile than the enemy's ability to conceal and/or change its battlefield footprint, tactics, appearance or anything else which might impede the ATR from accurately recognizing and destroying targets.” The Spice family of weapons is operational with the Israeli Air Force and international customers. https://www.defensenews.com/artificial-intelligence/2019/06/17/israels-rafael-integrates-artificial-intelligence-into-spice-bombs/
June 12, 2020 | International, Security
Andrew Eversden The Army's artificial intelligence task force is working on two key projects, including one that would allow unmanned vehicles in the air to communicate with autonomous vehicles on the ground, after securing new funding, a service official said June 10. Gen. Mike Murray, commander of Army Futures Command, said during a June 10 webinar hosted by the Association of the United States Army that the task force has moved forward on the projects through its partnership with Carnegie Mellon University, launched in late 2018 . First, the team is working on programs dedicated to unmanned-unmanned teaming, or developing the ability of air and ground unmanned vehicles to talk to one other. The other effort underway is on a DevSecOps environment to develop future algorithms to work with other Army systems, Murray said. He did not offer further detail. The task force force has fewer than 15 people, Murray said, and fiscal 2021 will be the first year that it receives appropriated funds from Congress. Much of the work the task force has done so far as been building the team. In response to an audience question, Murray said that the task force is not yet working on defending against adversarial machine learning, but added that leaders recognize that's an area the team will need to focus on. “We're going to have to work on how do we defend our algorithms and really, how do we defend our training data that we're using for our algorithms," Murray said. In order to train effective artificial intelligence, the team needs significant amounts of data. One of the first projects for the task force was collecting data to develop advanced target recognition capabilities. For example, Murray said, being able to identify different types of combat vehicles. When the work started, the training data for target recognition didn't exist. “If you're training an algorithm to recognize cats, you can get on the internet and pull up hundreds of thousands of pictures of cats,” Murray said. “You can't do that for a T-72 [a Russian tank]. You can get a bunch of pictures, but are they at the right angles, lighting conditions, vehicle sitting camouflaged to vehicle sitting open desert?” Murray also said he recognizes the Army needs to train more soldiers in data science and artificial intelligence. He told reporters in late May that the Army and CMU have created a masters program in data science that will begin in the fall. He also said that the “software factory,” a six- to 12-week course to teach soldiers basic software skills. That factory will be based in Austin, where Futures Command is located, and will work with industry's local tech industry. “We have got to get this talent identified I'm convinced we have it in our formations,” Murray said. https://www.c4isrnet.com/artificial-intelligence/2020/06/10/the-army-ai-task-force-takes-on-two-key-projects/