In 2018, we featured the University of Alberta’s, world-renowned AI research group, led by research scientist Richard Sutton, who left us with this quote about the distinction between human and “artificial” intelligence. For our own benefit, he said, “There shouldn’t even be a distinction, it should just be one topic: the science of mind, whether artificial or natural. It will eventually all converge.”
When I show him this quote at a press conference seven years later, he quietly admits, “That was well said.”
We’re at the Alberta Machine Intelligence Institute (Amii), where Sutton is a fellow and chief scientific adviser, and the press conference is to announce Sutton (and long-time collaborator Andrew Barto) receiving the Alan M. Turing Award from the Association of Computing Machinery. The award — which comes with $1 million — is often referred to as the Nobel Prize in computing and Sutton won it for his decades-long, fundamental work in developing the AI field of reinforcement learning, which takes a trial-and-error approach to a desirable outcome.
That outcome has shifted, and possibly profoundly. In 2018, the breakthroughs were in gaming (Sutton’s U of A team’s research contributed to AI beating checkers, chess and the Chinese board game Go). Today, they’re in AI-generated software like ChatGPT and Midjourney that’s been finely tuned by reinforcement learning.
Many of the biggest AI advancements are directly tied to the work of the Ohio-born researcher, who moved to Canada in 2003. While introducing Sutton at the press conference, Amii CEO Cam Linke mentions these and other “Sputnik moments” from around the world (like DeepSeek’s chatbot, in China), and the proliferation of local startups (RL Core, Artificial Agency) that have relied upon Sutton’s AI research in some way.
“Rich has been an incredible mentor to both his students and his community,” Linke says. “That inspiration, I think, is one of the reasons we’re seeing reinforcement learning take off today.”
But where is it headed? While text- and image-generating AI may wow the world, it’s all a long way off from Sutton’s “science of mind” convergence. To him, any AI that takes in large data sets — say, millions of pictures of cats — to correctly identify the information contained within them going forward, hasn’t learned anything beyond pattern recognition and mimicry.
“And any kind of mimicking is not going to be powerful,” says Sutton. “Influencing the world, picking your actions, solving a puzzle of ‘How do you get reward from this environment?’ — that’s what intelligence is. I don’t want to claim deep insight. I just want to claim that I’m seeing the obvious.”
It’s also obvious to Sutton that, if he’s right, the community he has helped foster will play an even bigger role in the future of AI.
“If reinforcement learning is going to be essential to AI, then the University of Alberta, far more than any other place, is going to be the leader in reinforcement learning,” he says. “It seems almost inevitable that a lot of responsibility falls to us — we’re the ones to do it or to fail to do it.”
Sutton still thinks “convergence” is inevitable, and believes the AI world is doing its part. He’s just waiting for the world of psychology to catch up. “We should already have a science of mind — I think it should be a new field. But psychology doesn’t seem interested,” he argues. “They just want to do a natural science. The lack of ambition of these people!”
Through reinforcement learning (RL), Google DeepMind’s AlphaGo plays millions of games of Go against itself to become the game’s first non-human (and unbeatable) champion in 2,500 years. Lead researcher David Silver was one of Sutton’s PhD students.
Eschewing large data sets, DeepSeek instead used nothing but trial and error (a.k.a. reinforcement learning) to achieve success in writing, editing and summarization, validating Sutton’s belief that RL would usher in the new era of AI.
The Edmonton-based startup, which combines generative AI with videogames, was co-founded by former Sutton students Brian Tanner and Alex Kearney. It launched in 2024 with US$16 million in funding.
Using RL, the company monitors waste-water control in real time and continually adapts to plant conditions, allowing human operators to focus on maintenance and emergency response. Co-founders Martha and Adam White were Sutton colleagues.
This article appears in the May 2025 issue of Edify
