To better understand the potential uses of large language models (LLMs) and their impact, a team of researchers at the Carnegie Mellon University Software Engineering Institute CERT Division conducted four in-depth case studies. The case studies span multiple domains and call for vastly different capabilities. In this podcast, Matthew Walsh, a senior data scientist in CERT, and Dominic Ross, Multi-Media Design Team lead, discuss their work in developing the four case studies as well as limitations and future uses of ChatGPT.
Women in Software and Cybersecurity: Bobbie Stempfley
Women in Software and Cybersecurity: Dr. Lorrie Cranor
Leading in the Age of Artificial Intelligence
Applying Best Practices in Network Traffic Analysis
10 Types of Application Security Testing Tools and How to Use Them
Using Test Suites for Static Analysis Alert Classifiers
Blockchain at CMU and Beyond
Leading in the Age of Artificial Intelligence
Deep Learning in Depth: The Future of Deep Learning
Deep Learning in Depth: Adversarial Machine Learning
System Architecture Virtual Integration: ROI on Early Discovery of Defects
Deep Learning in Depth: The Importance of Diverse Perspectives
A Technical Strategy for Cybersecurity
Best Practices for Security in Cloud Computing
Risks, Threats, and Vulnerabilities in Moving to the Cloud
Deep Learning in Depth: IARPA's Functional Map of the World Challenge
Deep Learning in Depth: Deep Learning versus Machine Learning
How to Be a Network Traffic Analyst
Workplace Violence and Insider Threat
Why Does Software Cost So Much?
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