In this episode of Toronto Talks, we look beneath the surface of artificial intelligence — and examine the physical systems that determine how far, how fast, and how evenly AI can actually scale.

AI is often described as a software revolution: better models, faster tools, more powerful capabilities. But at scale, intelligence depends on something much heavier.

Power.
Data centers.
Grid access.
Land.
Cooling.
Permitting.
Construction timelines.
And the ability to coordinate all of it before demand moves again.

We explore:

• Why AI progress depends on more than model capability
• How infrastructure is being built ahead of demand
• Why power and geography are becoming strategic constraints
• How data center capacity shapes access to intelligence
• Why AI may scale unevenly across regions
• And why the real challenge may not be building intelligence — but delivering it

Because the future of AI may not be defined only by who creates the best models.

It may be defined by who can make intelligence available, reliable, and scalable in the real world.

Toronto Talks — where big ideas come to life…
and curiosity never sleeps.

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