10 janvier 2022 | International, C4ISR

Défense : la France confie à Thales son système de surveillance aérienne

La Direction de la maintenance aéronautique du ministère des Armées a confié un contrat très important pour assurer le suivi de tous les équipements de surveillance aérienne. Thales devient son interlocuteur unique.

https://www.lesechos.fr/industrie-services/air-defense/defense-la-france-confie-a-thales-son-systeme-de-surveillance-aerienne-1377662

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    25 octobre 2018 | International, Aérospatial

    Dassault dévoile le remplaçant du Rafale

    Le salon Euronaval (Le Bourget, 23 au 26 octobre 2018), est l'occasion pour l'avionneur de Saint-Cloud de lever un coin de voile sur son concept de « New Generation Fighter ». Ce NGF est destiné à occuper une place essentielle dans le projet franco-allemand SCAF (Système de Combat Aérien Futur) développé par Airbus et Dassault, et dont la France (comprendre Dassault) aura la maitrise d'oeuvre. La maquette présentée sur le stand Dassault à Euronaval montre un avion piloté, sans dérive, sans canard, avec des entrées d'air trapézoïdales à la mode du F-22. L'accent est mis sur la furtivité et l'appareil disposerait en bonne logique d'une soute pour emporter son armement. Les équations qui dictent la furtivité aux ondes électromagnétiques étant les mêmes pour tout le monde, il n'est pas étonnant que les avions existant ou en projet reprennent les mêmes solutions. La maquette de Dassault se distingue par l'absence de dérive : l'avionneur français maîtrise le sujet depuis qu'il fait voler le Neuron. Le démonstrateur de drone de combat lui a également mis le pied à l'étrier en matière de furtivité. Le NGF ayant vocation à succéder au Rafale, il devrait logiquement exister en deux versions : terrestre et embarquée. Ce qui explique sa présence au salon Euronaval... Frédéric Lert https://www.aerobuzz.fr/defense/dassault-devoile-le-remplacant-du-rafale/

  • DARPA: Building Trusted Human-Machine Partnerships

    4 février 2019 | International, C4ISR

    DARPA: Building Trusted Human-Machine Partnerships

    A key ingredient in effective teams – whether athletic, business, or military – is trust, which is based in part on mutual understanding of team members' competence to fulfill assigned roles. When it comes to forming effective teams of humans and autonomous systems, humans need timely and accurate insights about their machine partners' skills, experience, and reliability to trust them in dynamic environments. At present, autonomous systems cannot provide real-time feedback when changing conditions such as weather or lighting cause their competency to fluctuate. The machines' lack of awareness of their own competence and their inability to communicate it to their human partners reduces trust and undermines team effectiveness. To help transform machines from simple tools to trusted partners, DARPA today announced the Competency-Aware Machine Learning (CAML) program. CAML aims to develop machine learning systems that continuously assess their own performance in time-critical, dynamic situations and communicate that information to human team-members in an easily understood format. “If the machine can say, ‘I do well in these conditions, but I don't have a lot of experience in those conditions,' that will allow a better human-machine teaming,” said Jiangying Zhou, a program manager in DARPA's Defense Sciences Office. “The partner then can make a more informed choice.” That dynamic would support a force-multiplying effect, since the human would know the capabilities of his or her machine partners at all times and could employ them efficiently and effectively. In contrast, Zhou noted the challenge with state-of-the-art autonomous systems, which cannot assess or communicate their competence in rapidly changing situations. “Under what conditions do you let the machine do its job? Under what conditions should you put supervision on it? Which assets, or combination of assets, are best for your task? These are the kinds of questions CAML systems would be able to answer,” she said. Using a simplified example involving autonomous car technology, Zhou described how valuable CAML technology could be to a rider trying to decide which of two self-driving vehicles would be better suited for driving at night in the rain. The first vehicle might communicate that at night in the rain it knows if it is seeing a person or an inanimate object with 90 percent accuracy, and that it has completed the task more than 1,000 times. The second vehicle might communicate that it can distinguish between a person and an inanimate object at night in the rain with 99 percent accuracy, but has performed the task less than 100 times. Equipped with this information, the rider could make an informed decision about which vehicle to use. DARPA has scheduled a pre-recorded webcast CAML Proposers Day for potential proposers on February 20, 2019. Details are available at: https://go.usa.gov/xE9aQ. The CAML program seeks expertise in machine learning, artificial intelligence, pattern recognition, knowledge representation and reasoning, autonomous system modeling, human-machine interface, and cognitive computing. To maximize the pool of innovative proposal concepts, DARPA strongly encourages participation by non-traditional proposers, including small businesses, academic and research institutions, and first-time Government contractors. DARPA anticipates posting a CAML Broad Agency Announcement solicitation to the Federal Business Opportunities website in mid-February 2019. https://www.darpa.mil/news-events/2019-01-31

  • L3Harris sees opportunities in Pentagon’s growing responsive space business

    18 mars 2021 | International, Aérospatial

    L3Harris sees opportunities in Pentagon’s growing responsive space business

    The company says its move into responsive space has opened up $9 billion in opportunities.

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