In Episode 2 of the Control in AI Series, we deconstruct the AI stack (Model → System → Interface) and explore how control at the model layer dictates access, capabilities, integration, and ultimately who wins the AI economy. We discuss the economies of scale, learning effects, and scope that make the model layer the main bottleneck. We compare it with Apple’s ecosystem and discuss the two competing visions of AI as open infrastructure versus AI as a tightly controlled platform.
By the end of this episode, you’ll know why governance is the key question in AI today—it’s not about who builds the best model; it’s about who gets to decide the rules of the whole system.
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