Approximately Correct: An AI Podcast from Amii

We’re taking a bit of a break this month, so no new episode of Approximately Correct. Instead, we wanted to revisit one of our favourite episodes from the past year. So let’s talk survival prediction with Russ Greiner. How can machine learning revolutionize healthcare? In this episode, Amii Fellow and Canada CIFAR AI Chair Russ Greiner explores how AI is transforming survival prediction, giving doctors and patients personalized health insights that were never before possible. From creating tailored survival curves to improving treatment decisions, Greiner reveals the groundbreaking potential of AI in medicine.

Ever wonder what exactly plants get up to all day? It’s much more than just sitting around to soak up the sun. Now, machine learning is helping to unlock the mysteries of how plants change over the course of a day, and the impact it could have on how we grow our food. Biochemist  Dr. Glen Uhrig joins hosts Alona Fyshe and Scott Lilwall to talk about how his lab is using machine learning to study how plants grow in different lighting conditions of the course of the day. This could lead to applications with big impacts for indoor farming in northern climates, and perhaps even feeding astronauts during space missions. Listen to discover the potential that artificial intelligence has in advancing scientific research in biochemistry, agriculture, and other fields.

Should powerful foundational AI models be kept under lock and key, or shared openly with the world? In this episode of Approximately Correct, we sit down with Joelle Pineau, a professor at McGill University, former head of AI research at Meta and current chief AI officer at Cohere.. She led the development and release of the early versions of Meta’s Llama models, a series of open-weight models that challenged the closed-door approach of other AI teams. Pineau argues that openness is the fastest path to better, safer AI, and that diversity in foundational models is essential to developing a limited ‘algorithm monoculture’.

On this episode of Approximately Correct, we talk with Michael Littman about the importance of making AI accessible and fun for everyone. A former division director for the AI division at the National Science Foundation, Michael shares his unique perspective on AI policy, communication, and his career in reinforcement learning. He also discusses his new role as Associate Provost of Artificial Intelligence at Brown University, where he is working to coordinate AI research and teaching across the entire university.

This AI doesn't replace jobs; it collaborates with human experts to get the job done.On this episode of Approximately Correct, we talk with Revan McQueen on the future of industrial control and AI's role in making it safer and better