For more than two decades, the Need for Speed (NFS) video game franchise captured the hearts of young gamers across the globe with its high-octane thrills, heart-pounding car chases, and the adrenaline rush of illegal street racing. Yet for many, especially those who played the earliest iterations in the late ‘90s and early 2000s, NFS […]
Digital engineering (DE) is gaining momentum as the system engineering community matures practices and tooling. In its present avatar, DE workflows and tools rely on MBSE (Model-Based Systems Engineering) for developing and maintaining digital system artifacts and keeping these artifacts in sync during all phases of the system. This is presently achieved via descriptive models […]
Systems engineering has come a long way since the 1960s. Defense and aerospace data management systems, which initially evolved under a centralized authority, must now adapt to highly distributed organizations with multiple authorities and open and modular development needs. Organizational management techniques have evolved to smooth logistics and collaboration between contributors, and data management and […]
The National Cryptologic Museum opened its doors to the public last week. As part of the exhibits, visitors will be able to interact with a quirky little car with a big claim: under the hood, it demonstrates hardware that can thwart many cyberattacks on automobiles. The BESSPIN Vehicle Demonstrator DARPA’s System Security Integration Through Hardware […]
Following our previous blog post, The Next Assembly Line, Galois continues our quest to invent tooling that can transform the DevOps process for developing and maintaining software. One of the unwritten pieces of common knowledge in software is that software rarely meets the models of design as implemented. As such, the notion of utilizing modern, […]
The Challenge At Galois, we verify and assure complex critical systems. Autonomous vehicles are prime examples of complex systems which operate in uncertain and unstructured environments. Autonomous driving decisions use Deep Neural Networks (DNNs) which are data-driven and can react in unsafe ways when faced with out-of-distribution driving scenarios. Rigorously assuring the safety of these systems […]
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