The recent growth of applications that leverage large language models, including ChatGPT and Copilot, has spurred reactions ranging from fear and uncertainty to adoration and lofty expectations. In this podcast from the Carnegie Mellon University Software Engineering Institute, Jay Palat, senior engineer and technical director of AI for mission, and Dr. Rachel Dzombak, senior advisor to the director of the SEI’s AI Division, discuss the current landscape of large language models (LLMs), common misconceptions about LLMs, how to leverage tools built on top of LLMs, and the need for critical thinking around both the outputs of the tools and the trends in their use.
Deep Learning in Depth: The Good, the Bad, and the Future
The Evolving Role of the Chief Risk Officer
Obsidian: A Safer Blockchain Programming Language
Agile DevOps
Kicking Butt in Computer Science: Women in Computing at Carnegie Mellon University
Is Software Spoiling Us? Technical Innovations in the Department of Defense
Is Software Spoiling Us? Innovations in Daily Life from Software
How Risk Management Fits into Agile & DevOps in Government
5 Best Practices for Preventing and Responding to Insider Threat
Pharos Binary Static Analysis: An Update
Positive Incentives for Reducing Insider Threat
Mission-Practical Biometrics
At Risk Emerging Technology Domains
DNS Blocking to Disrupt Malware
Best Practices: Network Border Protection
Verifying Software Assurance with IBM’s Watson
The CERT Software Assurance Framework
Scaling Agile Methods
Ransomware: Best Practices for Prevention and Response
Integrating Security in DevOps
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