This episode of Generation AI dives into a groundbreaking research paper on model interpretability in large language models. Dr. JC Bonilla and Ardis Kadiu discuss how this new understanding of AI's inner workings could change the landscape of AI safety, ethics, and reliability. They explore the similarities between human brain function and AI models, and how this research might help address concerns about AI bias and unpredictability. The conversation highlights why this matters for higher education professionals and how it could shape the future of AI in education. Listeners will gain key insights into the latest AI developments and their potential impact on the field.
Introduction to Model Interpretability
Understanding AI's Inner Workings
Types of AI Features
Implications for AI Safety and Ethics
Impact on Higher Education
Looking Ahead: The Future of AI
- - - -
Connect With Our Co-Hosts:
Ardis Kadiu
https://www.linkedin.com/in/ardis/
https://twitter.com/ardis
Dr. JC Bonilla
https://www.linkedin.com/in/jcbonilla/
https://twitter.com/jbonillx
About The Enrollify Podcast Network:
Generation AI is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!
Enrollify is made possible by Element451 — The AI Workforce Platform for Higher Ed. Learn more at element451.com.