model economics - Adjacent

Jul 8

Microsoft builds proprietary AI to escape model licensing costs

Microsoft's shift from licensing OpenAI and Anthropic models to deploying its own defends margins by reducing dependency on external model vendors. The move directly threatens the unit economics of pure-play model companies reliant on enterprise licensing revenue. It signals that scale—Microsoft's installed base and cloud infrastructure—now matters more than frontier model capabilities for many commercial applications. Cloud providers are becoming their own AI suppliers, collapsing what was briefly a thriving independent model layer.

theme-ai model economics cost efficiency llm capabilities

Jun 1

Why AI's Cost Collapse Won't Arrive as Promised

Source: Big Technology

Sam Altman's prediction that AI compute will converge to electricity costs assumes datacenter production automation will proceed at current timelines—a premise that ignores physical infrastructure bottlenecks, power grid constraints, and geopolitical competition for semiconductor supply. The question isn't whether AI gets cheaper; it's when the infrastructure and supply chains required to build that cheapness will actually materialize, and whether any single company can capture the economics of that transition. The friction point isn't Moore's Law math—it's the concrete problem of building enough fabs, securing enough power, and navigating nation-state interventions faster than AI model improvements actually demand compute.