Software Engineering Institute (SEI) Podcast Series

Tom Longstaff, who in 2018 was hired as the SEI’s chief technology officer, discusses the challenges of leading a technical organization in the age of artificial intelligence.

April Galyardt, Angela Horneman, and Jonathan Spring discuss seven key questions that managers and decision makers should ask about machine learning to effectively solve cybersecurity problems.

Learn more about the future of CERT and Rich Pethia's view of the Internet security landscape. Listen on Apple Podcasts.

At the request of the White House, the Office of the Director of National Intelligence (ODNI) began exploring use cases for large language models (LLMs) within the Intelligence Community (IC). As part of this effort, ODNI sponsored the Mayflower Project at Carnegie Mellon University’s Software Engineering Institute (SEI) from May 2023 through September 2023. The Mayflower Project attempted to answer the following questions:

1. How might the IC set up a baseline, stand-alone LLM?
2. How might the IC customize LLMs for specific intelligence use cases?
3. How might the IC evaluate the trustworthiness of LLMs across use cases?

In this SEI Podcast, Shannon Gallagher, AI engineering team lead, and Rachel Dzombak, special advisor to the director of the SEI’s AI Division, discuss the findings and recommendations from the Mayflower Project and provides additional background information about LLMs and how they can be engineered for national security use cases.

Developers know that static analysis helps make code more secure. However, static analysis tools often produce a large number of false positives, hindering their usefulness. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), David Svoboda, a software security engineer in the SEI’s CERT Division, discusses Redemption, a new open source tool from the SEI that automatically repairs common errors in C/C++ code generated from static analysis alerts, making code safer and static analysis less overwhelming.