The study explores the risks and tradeoffs when adapting enterprise-IT security and zero trust principles to weapon systems.

DeCapria, D., 2025: DataOps: Towards More Reliable Machine Learning Systems. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed ...

At the November event, co-organized by the SEI, artificial intelligence experts will present case studies and research and development in building AI systems for safety-critical applications.

Robert, J., and Schmidt, D., 2024: 10 Benefits and 10 Challenges of Applying Large Language Models to DoD Software Acquisition. Carnegie Mellon University, Software ...

The October 23 virtual workshop will feature presentations on dataset generation, exploration, preparation, and testing for ensuring data quality when training AI systems.

In this webcast, Brett Tucker, Dan Justice, and Matthew Butkovic discuss the challenges to be expected with the realization of quantum computing capabilities.

Morales, J., 2019: Challenges to Implementing DevOps in Highly Regulated Environments: First in a Series. Carnegie Mellon University, Software Engineering Institute's ...

DeCapria, D., 2024: Introduction to MLOps: Bridging Machine Learning and Operations. Carnegie Mellon University, Software Engineering Institute's Insights (blog ...

Ozkaya, I., and Schmidt, D., 2024: Generative AI and Software Engineering Education. Carnegie Mellon University, Software Engineering Institute's Insights (blog ...

Robinson, K., and Turri, V., 2024: Auditing Bias in Large Language Models. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed ...

This report describes 11 common vulnerabilities and 3 risks related to application programming interfaces, providing suggestions about how to fix or reduce their impact. Application programming ...

Sherman, M., 2024: Using ChatGPT to Analyze Your Code? Not So Fast. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed October 27 ...