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.
My Story in Computing with Sam Procter
Developing and Using a Software Bill of Materials Framework
The Importance of Diversity in Cybersecurity: Carol Ware
The Importance of Diversity in Software Engineering: Suzanne Miller
The Importance of Diversity in Artificial Intelligence: Violet Turri
Using Large Language Models in the National Security Realm
Atypical Applications of Agile and DevSecOps Principles
When Agile and Earned Value Management Collide: 7 Considerations for Successful Interaction
The Impact of Architecture on Cyber-Physical Systems Safety
ChatGPT and the Evolution of Large Language Models: A Deep Dive into 4 Transformative Case Studies
The Cybersecurity of Quantum Computing: 6 Areas of Research
User-Centric Metrics for Agile
The Product Manager’s Evolving Role in Software and Systems Development
Measuring the Trustworthiness of AI Systems
Actionable Data in the DevSecOps Pipeline
Insider Risk Management in the Post-Pandemic Workplace
An Agile Approach to Independent Verification and Validation
Zero Trust Architecture: Best Practices Observed in Industry
Automating Infrastructure as Code with Ansible and Molecule
Identifying and Preventing the Next SolarWinds
Create your
podcast in
minutes
It is Free