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Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, Applied AI

Stanford Online · 49:15 · 1 months ago

Baseten enables companies to build profitable and defensible AI businesses by shifting their reliance from expensive, centralized frontier models toward customized, open-source models that the companies own themselves.

  • Inference economics — Roughly 95% of AI spending currently goes to frontier labs, but moving to post-trained, open-source models helps companies improve profit margins and retain control over their proprietary user data .
  • Market defensibility — Relying solely on external frontier models creates a dangerous dependency, effectively handing over trade secrets to entities that could eventually use that data to compete directly with their own customers .
  • Compute scarcity — GPU access is an extreme seller's market where demand far outstrips supply, causing rental costs to double and lead times to extend over a year .
    • Rental prices are becoming untenable, pushing the company to transition from renting to owning its hardware infrastructure .
  • Infrastructure strategy — Baseten acts as an abstraction layer that manages reliability, performance, and multi-cloud access, essentially making disparate GPUs fungible for customers who lack internal hardware teams .
  • Future infrastructure — To maintain service levels amid projected growth, the company estimates it will require 150,000 advanced chip equivalents within the next two years to meet demand .
  • Hardware dominance — Nvidia currently holds a massive advantage due to the deep integration of its CUDA software ecosystem, making it the primary choice for rapid development, though heterogeneous computing architectures are likely the long-term future .

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