# Compute Scarcity **Entity class:** Infrastructure constraint **Domain:** Artificial intelligence / science / political economy **Maturity:** Developed ## Definition **Compute Scarcity** is the condition in which demand for chips, memory, inference, and training capacity exceeds available supply even as algorithms and hardware become more efficient. ## Mechanism and Consequence The scarcity moves the AI bottleneck down the stack. Model access gives way to chip allocation, energy delivery, cooling, construction, and capital as the limiting factors of deployment. ## Relationships - [[wiki/AI Infrastructure|AI Infrastructure]] - [[wiki/Energy-Compute Nexus|Energy-Compute Nexus]] - [[wiki/Compute Sovereignty|Compute Sovereignty]] - [[wiki/AI Price-Performance|AI Price-Performance]] ## Source Dossiers - [[research/AI Is Now So Good They Will Pay You to Quit|AI Is Now So Good They Will Pay You to Quit]] - [[research/Super Intelligence Week Index of Statements from the White House Luncheon|Super Intelligence Week Index of Statements from the White House Luncheon]] - [[research/Jensen Pushes Back on Doomers Moonshots Live|Jensen Pushes Back on Doomers Moonshots Live]] ## Simple Reminders, Quotations, and Thoughts > "Energy is already the bottleneck. The United States is short roughly sixty gigawatts of energy for the next two years." > **— Peter Diamandis**, *MOONSHOTS Live, September 25, 2026* [[reminders/AI Infrastructure/Energy Is Already the AI Bottleneck by Peter Diamandis|Energy Is Already the AI Bottleneck by Peter Diamandis]] > "Both things can be true: a generalized model can drive a car or inhabit and build a robot, while a specialized model may still perform the task more efficiently. The missing question is how much compute the general model used. Compute will remain starved; chip prices have risen, and high-bandwidth memory has increased fivefold in price. AI is so valuable that people want the compute, so using more compute for the same task is a serious failure." > **— Dave Blundin**, *MOONSHOTS Live, September 25, 2026* [[reminders/AI Infrastructure/General Models Must Still Justify Their Compute Costs by Dave Blundin|General Models Must Still Justify Their Compute Costs by Dave Blundin]] > "The AI bottleneck is shifting from models down the stack to compute, and then eventually to energy." > **— Salim Ismail**, *MOONSHOTS Live, September 25, 2026* [[reminders/AI Infrastructure/The AI Bottleneck Moves From Models to Compute to Energy by Salim Ismail|The AI Bottleneck Moves From Models to Compute to Energy by Salim Ismail]]