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July 5, 2023 | International, Aerospace

Germany to buy 60 Chinooks for up to 8 bln euros -lawmakers

Germany will buy 60 Chinook helicopters from Boeing in a package that will cost up to 8 billion euros ($8.7 billion), including necessary infrastructure for the aircraft, two members of the parliamentary budget committee told Reuters on Wednesday.

https://www.reuters.com/business/aerospace-defense/germany-buy-60-chinooks-up-8-bln-eur-committee-members-2023-07-05/

On the same subject

  • Bulgaria is looking for 3D radars to fully utilize its F-16s

    August 28, 2023 | International, C4ISR

    Bulgaria is looking for 3D radars to fully utilize its F-16s

    A total of five defense corporations are contending to secure a contract. This contract pertains to the production of Bulgaria's military surveillance radars.

  • Can AI help limited information have endless potential?

    June 19, 2019 | International, C4ISR, Other Defence

    Can AI help limited information have endless potential?

    By: Kelsey D. Atherton Humans are remarkably good at choosing to act on limited information. Computers, less so. A new DARPA program wants to train artificial intelligence to process and evaluate information like humans do, and produce actionable results on far smaller datasets than presently done. It's a program of such important DARPA's giving it VIP status, or a least VIP as an acronym: Virtual Intelligence Processing. “Successful integration of next-generation AI into DoD applications must be able to deal with incomplete, sparse and noisy data, as well as unexpected circumstances that might arise while solving real world problems,” reads a solicitation posted June 14. “Thus, there is need for new mathematical models for computing leading to AI algorithms that are efficient and robust, can learn new concepts with very few examples, and can guide the future development of novel hardware to support them.” To create these mathematical models, DARPA wants partners to look inward, creating AI inspired by the robust and massive parallelism seen in the human neocortex. If it is the architecture of the brain that makes humans so especially skilled at processing information quickly, then it is an architecture worth studying. “In order to reverse engineer the human brain,” the solicitation continues, calmly, “we need to apply new mathematical models for computing that are complete and transparent and can inform next-generation processors that are better suited for third-wave AI.” It is DARPA's nature to inject funding into problem areas it sees as both yielding future results and not presently served by the market, and this is not different. The solicitation explicitly asks for mathematical models that have not already been the focus of AI development. It's also looking for models that can inform the development of future hardware, rather than programs that can run on existing machines. DARPA is interested in how the hardware works in simulation, but wants partners to hold off on actually making the hardware for the model. So, the plan goes: create a mathematical model, inspired by brains, to process information on a small and limited data set, and then design it for hardware that doesn't exist yet. Easy as that sounds, the solicitation also asks proposers to talk about the limitations of the algorithms when applied to military tasks, and specifically limitations related to accuracy, data, computing power and robustness. Working from limited information is an expected future of military machines going forward. Between electronic warfare, denied environments and the very nature of battlefield events as rare and hard to record moments, doing more with on-board processing of limited data should enable greater autonomy. Even in the rare case where a weapon system transmits data back for algorithm refinement, that data set will be orders of magnitude smaller than the big data sets used to train most commercial machine learning tools. Should a proposer's idea be accepted and they follow through both Phase 1 and Phase 2 of the project, the total award is set at $1 million. A tidy sum, for anyone who can figure out the math to make a future computer run on sparse information as effectively as a human brain. https://www.c4isrnet.com/artificial-intelligence/2019/06/18/can-brain-inspired-ai-run-on-lean-data/

  • United Technologies nets $325.2M contract for F-35 depot maintenance

    October 8, 2019 | International, Aerospace

    United Technologies nets $325.2M contract for F-35 depot maintenance

    ByEd Adamczyk Oct. 7 (UPI) -- The Pratt & Whitney division of United Technologies Corp. was awarded a potential four-year, $325.2 million contract for aircraft maintenance equipment for the F-35 fighter aircraft. The contract, announced by the Defense Department on Friday, calls for UTC to provide material and support equipment for depot maintenance facilities, as well as non-recurring sustainment activities, supplies, services and planning for depot activations. It also includes two F135 full-scale mockup engines and four modules for test activities in support of the F-35 Lightning II Program. Work will be performed largely at UTC's Oklahoma City facility, as well as in several other locations within the United States and in foreign countries, and is expected to conclude in 2023. Fiscal 2019 aircraft procurement funds of the Navy, Marine Corps and Navy, as well as those of non-Defense Department agencies and foreign buyers of the F-35, will pay for the contract, the Pentagon said. The F-35 has been in service since 2015 and is currently in the fleets of, or with purchases planned by, 12 nations. Built by Lockheed Martin with UTC as a major subcontractor, the plane is a single engine, fifth-generation stealth combat aircraft designed for ground-attack and air-superiority missions. Currently regarded as the world's most advanced fighter plane, its F135 engine delivers over 40,000 lbs. of thrust and has been included on each of the 425 F-35s manufactured thus far. https://www.upi.com/Defense-News/2019/10/07/United-Technologies-nets-3252M-contract-for-F-35-depot-maintenance

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