#241 Patrick M. Pilarski: The Alberta Plan’s Roadmap to AI and AGI

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Can AI learn like humans? In this episode, Patrick Pilarski, Canada CIFAR AI Chair and professor at the University of Alberta, breaks down The Alberta Plan—a bold roadmap for achieving Artificial General Intelligence (AGI) through reinforcement learning and real-time experience-based AI.

Unlike large pre-trained models that rely on massive datasets, The Alberta Plan champions continual learning, where AI evolves from raw sensory experience, much like a child learning through trial and error. Could this be the key to unlocking true intelligence?

Pilarski also shares insights from his groundbreaking work in bionic medicine, where AI-powered prosthetics are transforming human-machine interaction. From neuroprostheses to reinforcement learning-driven robotics, this conversation explores how AI can enhance—not just replace—human intelligence.

What You’ll Learn in This Episode:

Why reinforcement learning is a better path to AGI than pre-trained models

The four core principles of The Alberta Plan and why they matter

How AI-driven bionic prosthetics are revolutionizing human-machine integration

The battle between reinforcement learning and traditional control systems in robotics

Why continual learning is critical for AI to avoid catastrophic forgetting

How reinforcement learning is already powering real-world breakthroughs in plasma control, industrial automation, and beyond

The future of AI isn’t just about more data—it’s about AI that thinks, adapts, and learns from experience.

If you're curious about the next frontier of AI, the rise of reinforcement learning, and the quest for true intelligence, this episode is a must-watch.

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(00:00) The Alberta Plan: A Roadmap to AGI  

(02:22) Introducing Patrick Pilarski

(05:49) Breaking Down The Alberta Plan’s Core Principles  

(07:46) The Role of Experience-Based Learning in AI  

(08:40) Reinforcement Learning vs. Pre-Trained Models  

(12:45) The Relationship Between AI, the Environment, and Learning  

(16:23) The Power of Reward in AI Decision-Making  

(18:26) Continual Learning & Avoiding Catastrophic Forgetting  

(21:57) AI in the Real World: Applications in Fusion, Data Centers & Robotics  

(27:56) AI Learning Like Humans: The Role of Predictive Models  

(31:24) Can AI Learn Without Massive Pre-Trained Models?  

(35:19) Control Theory vs. Reinforcement Learning in Robotics  

(40:16) The Future of Continual Learning in AI  

(44:33) Reinforcement Learning in Prosthetics: AI & Human Interaction  

(50:47) The End Goal of The Alberta Plan