Digital Engineering: From point solutions to trusted processes

In the world of cyber physical systems, the aim of Digital Engineering (DE) is to speed up the development process while simultaneously improving security, reliability, safety and performance. The core mechanism enabling this outcome is a refinement based design and implementation process whereby high-level requirements and reference architectures are refined into low-level requirements and system […]

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Ontology, AI, and Human-Machine Teaming: How Does a Machine Know What We Mean?

We’ve all seen it—a couple on a date, politicians, friends, or colleagues talking right past each other, trapped in a moment of profound misunderstanding over the meaning of a single word. For me, that moment came when my partner, a New Yorker through and through, told me, a Midwesterner, to take “the next left” while […]

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U.S. Government Programs Need Authoritative Sources of Truth Aligned with Multi-organization Workflows

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 […]

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Digital Engineering: Changing the Paradigm

The Greek philosopher Heraclitus once said, “change is the only constant in life.” Yet, all too often, it is change that we struggle with the most. In business and technology, as in life, there is comfort in doing things the way we have always done them. We hold onto strategies, processes, and approaches that are […]

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Formal methods + AI: Where does Galois fit in?

Thus far in our ongoing series on artificial intelligence we’ve spoken in depth on questions of trust, human perception, and limitations of generative models. We have focused specifically on large language models (LLMs), due in part to their recent successes and media attention. We’ve explored questions of data, testing, and broad model implications. However, LLMs […]

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Vehicle E/E Architectures – The Last Ten Years and the Future

Before diving in, I’d like to acknowledge our amazing partners in this research, DGTech and Transportation Research Center Inc., and share a quick disclaimer. This material is based upon work done in partnership with DGTech and Transportation Research Center Inc., and supported by National Highway Traffic Safety Administration (NHTSA). Any opinions, findings, conclusions, or recommendations expressed […]

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Language is a Noisy Measure

In my ongoing efforts to deeply engage with research into large language models, I have continually wrestled with and confronted a persistent sense of dissatisfaction. Unfortunately, the source of my dissatisfaction has also been frustratingly difficult to articulate and to pin down.  At times, I have wondered if I’m not dissatisfied but rather uneasy because […]

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Making a scalable, SMT-based machine code memory model

In this post, we describe a new memory model that we have added to our Macaw binary analysis framework which dramatically improves its performance when dealing with large binaries. Galois continues to invest in our binary analysis tools because they address a significant problem: many developers distribute closed source binaries that cannot be analyzed with […]

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Confabulators, Persuaders, and Imagination Catalysts: An Expert Perspective on the Chatbot Phenomenon

In all my years as a researcher, I’ve never had so many friends and family members asking me about AI – chatbots, in particular. Even people that I would have described as fairly disinterested in tech in general have shared with me their experiences interacting with ChatGPT, or expressed that they are fearful and/or intrigued […]

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