Military AI
 
 
AUGUST 2023

Military AI brought to you by the editors of Militaryembedded.com focuses on artificial intelligence technology in the defense and aerospace domain, bringing readers coverage on machine learning, neural networks, and deep learning techniques leveraged in military and aerospace applications.
 
 
 
 
 
 
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DAN TAYLOR, TECHNOLOGY EDITOR
 
A three-hour sortie led by the Air Force Research Laboratory (AFRL) demonstrated the first flight of machine-learning (ML) trained artificial intelligence (AI) algorithms on an XQ-58A Valkyrie uncrewed jet aircraft, according to an AFRL statement. The mission took place on July 25 in the Eglin Test and Training Complex.
 
 
 
 
 
 
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DAN TAYLOR, TECHNOLOGY EDITOR
 
As the defense industry grapples with exponential increases in mission data that must be collected, managed, and analyzed, the promise of artificial intelligence (AI) to harness the power of big data and drive strategic decision-making represents an unprecedented shift in the industry.
 
 
 
 
 
 
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JOHN MCHALE, EDITORIAL DIRECTOR
 
Modular open system approach (MOSA) strategies such as the Future Airborne Capability Environment (FACE) Technical Standard are changing how the Department of Defense acquires technology. In this podcast with Tim Reed, Chief Executive Officer for Lynx Software Technologies, he and I discuss how MOSA benefits the warfighter and what it means to be certified conformant other the FACE Technical Standard.
 
 
 
 
 
 
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CHRISTOPHER YATES, RED HAT
 
The U.S. Department of Defense (DoD)is investing in multiple initiatives including the Joint Warfighting Concept (JWC) and Combined Joint All-Domain Command and Control (CJADC2) to enable coordinated military operations against current and future threats.
 
 
 
 
 
 
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ARON BRAND, CTERA
 
In the theater of modern warfare, data reigns supreme. The ability to swiftly acquire, process, and act on information transforms the battlefield into a dynamic digital landscape where data is the new strategic resource.
 
 
 
 
 
 
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DAN TAYLOR, TECHNOLOGY EDITOR
 
The Air Force Research Laboratory (AFRL) has expanded a contract for the development of artificial intelligence (AI) driven techniques for drone sensors to Sarcos Technology and Robotics Corporation, according to a statement from the company. This technology will be used for autonomously controlling a Heterogeneous Sensing Network (HSN).
 
 
 
 
 
 
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LISA DAIGLE, ASSISTANT MANAGING EDITOR
 
Artificial intelligence (AI)-based counter-uncrewed systems company DroneShield won a $33 million contract with the U.S. Department of Defense (DoD), consisting of DroneShield counter-uncrewed aerial system (C-UAS) equipment and multiyear support services.
 
 
 
 
 
 
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DAN TAYLOR, TECHNOLOGY EDITOR
 
Boeing subsidiary Aurora Flight Sciences is working on the development and testing of machine learning-based introspection technologies to help uncrewed surface vessels (USV) better operate in a maritime environment, the company announced in a statement.
 
 
 
 
 
 
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DAN TAYLOR, TECHNOLOGY EDITOR
 
The global growth in uncrewed aerial vehicle (UAV) usage is making the development and deployment of counter-UAV systems increasingly essential in order to detect, track, and neutralize unauthorized drones, states a new report from market research firm Market Forecast.
 
 
 
 
 
 
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LISA DAIGLE, ASSISTANT MANAGING EDITOR
 
Boeing and Intel announced a new strategic collaboration under which the companies are working together to advance semiconductor technology across the aerospace industry, with the intent to create next-generation microelectronics applications in artificial intelligence (AI), secure computing, and advanced flight capabilities for future products.
 
 
 
 
 
 
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ONE STOP SYSTEMS (OSS)
 
Military program leaders in charge of transportable AI missions can avoid painful and costly AI performance compromises when leveraging open standards such as VPX/Open VPX and SOSA. Standard-compliant sensors and sensor interfaces can be partitioned as part of the AI system design.
 
 
 
 
 
 
Analog Devices
 
ANALOG DEVICES
 
Millimeter wave scanners are superior to traditional metal detectors because they can identify and locate both metallic and nonmetallic threats. This article describes how mmWave imaging hardware works and will present a chipset that uses edge processing to manage massive data loads to enable the development of walkthrough security scanning systems.
 
 
 
 
 
 
 
 
Sponsored by: Mercury Systems
Date: On-Demand
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