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:    How might the IC set up a baseline, stand-alone LLM?   How might the IC customize LLMs for specific intelligence use cases?   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.

Using Large Language Models in the National Security Realm

Across the globe, women account for less than 30 percent of professionals in technical fields. That number drops to 22 percent in the field of Artificial Intelligence (AI). In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Violet Turri, a software developer in the SEI’s AI Division, discusses the evolution of her career in AI and the importance of diversity in the field.&nbsp;

The Importance of Diversity in Artificial Intelligence: Violet Turri

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Suzanne Miller, a principal researcher in the SEI’s Software Solutions Division, discusses her career path, the value of mentorship,&nbsp;and&nbsp;the importance of diversity in software engineering.

The Importance of Diversity in Software Engineering: Suzanne Miller

In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Ware, a senior cybersecurity engineer in the SEI’s CERT Division, discusses her career path, the value of mentorship, and the importance of diversity in cybersecurity.

The Importance of Divesity in Cybersecurity: Carol Ware

With the increasing complexity of software systems, the use of third-party components has become a widespread practice. Cyber disruptions, such as SolarWinds and Log4j, demonstrate the harm that can occur when organizations fail to manage third-party components in their software systems. In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Woody, principal researcher, and Michael Bandor, a senior software engineer, discuss a Software Bill of Materials (SBOMs) framework to help promote the use of SBOMs and establish a more comprehensive set of practices and processes that organizations can leverage as they build their programs. They also offer guidance for government agencies who are interested in incorporating SBOMs into their work.&nbsp;

Developing and Using a Software Bill of Materials Framework

Sam Procter started out studying computer science at the University of Nebraska, but he didn’t love it. It wasn’t until he took his first software engineering course that he knew he’d found his career path. In this podcast from the Carnegie Mellon University Software Engineering Institute, Sam Procter discusses the early influences that shaped his career, the importance of embracing different types of diversity in his research and work, and the value of a work-life balance.

My Story in Computing with Sam Procter

Not all paths to cybersecurity careers look the same. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Randy Trzeciak, deputy director of cyber risk and resilience in the SEI’s CERT division, discusses his career journey, resources for pursuing a career in cybersecurity, and the importance of building a diverse workforce.

Cyber Career Pathways and Opportunities

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.

Automated Repair of Static Analysis Alerts

In this podcast excerpt, Ritwik Gupta and Carson Sestili describe deep learning and how it differs from machine learning.  “As you compose more and more non-linear functions together, you can represent a much wider function space than you could with just one non-linear function. That is why deep learning is different from shallow learning. Shallow learning doesn’t compose multiple things together. Deep learning does.”

Deep Learning in Depth: Deep Learning versus Machine Learning

The SEI is a nonprofit, public–private partnership conducting R&D in software engineering, systems engineering, cybersecurity, and many other areas of computing, working to introduce private-sector innovations into government.

Deep Learning in Depth: Deep Learning versus Machine Learning

Carnegie Mellon - Software Engineering Institute

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