Rich looks every bit the quintessential researcher. A guy who has devoted his life to figuring out ways to teach a machine to learn, through trial and error. That’s his specialty — reinforcement learning.
“This sounds like a Canadian edition of OpenAI,” I suggest. Rich agrees: “That is actually a pretty good way to think about it. Open AI as it used to be. Open AI when it was non-profit, before it became commercial.” Then he qualifies his point: “But who am I? … I don’t have the conceit of claiming that I know what business decisions should be made or what political decisions should be made. Those are for other people. I just know what I should do. I want to work on the prize: Understanding intelligence.”
He is uniquely suited for the task. He checks off all the academic boxes. He’s a known known in the world of AI. He’s also libertarian and thinks, deeply, about why and how it’s OK for people to want different things and be unconstrained in their individual choices. And he applies this thinking to AI.