Engineering AI Systems for Mission-Practical Capabilities
AI holds incredible promise for transforming our software-driven world in general and DoD mission capabilities in particular. The computational advantages AI offers allow us to make the most of human-machine teaming, freeing humans to focus their attention on the types of tasks they do best. The SEI’s history as a federally funded research and development center (FFRDC) dedicated to software engineering means that we know what it takes to lay a foundation for confident, rapid adoption of AI for national defense and security. In collaboration with faculty and researchers at Carnegie Mellon University, the SEI focuses in the following areas:
- AI Engineering: The SEI is addressing a variety of challenges of engineering AI-enabled systems. Such challenges include scalability, representation, AI architectures, verification and validation for AI assurance, and interpretability.
- Applied AI: The SEI applies AI to DoD missions, including intelligence, surveillance, and reconnaissance (ISR); cybersecurity; mission planning and mission command; and logistics.
- AI for Software Engineering: Not only is AI at the heart of many software programs, it has the potential to revolutionize the process of software engineering itself. The SEI is exploring the potential of AI in this area.
The SEI is working to study how quantum computing can serve as the next paradigm for optimization in fields like software verification and validation.
September 05, 2019 • Technical Report
This report suggests seven key questions that managers and decision makers should ask about machine learning tools to effectively use those tools to solve cybersecurity problems.read
August 26, 2019 • Presentation
This presentation will discuss why the construction of secure software is a concern beyond the IT industry, the elements of a secure software development process and how artificial intelligence could be applied to improve that process.read
June 18, 2019 • Video
Rotem Guttman and April Galyardt describe how machine learning (ML) fits into the bigger picture of artificial intelligence (AI) and discuss the current state of AI.watch