Edward Conard

Top Ten New York Times Bestselling Author

  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
Upside of Inequality Oxford Unintended Consequences

AI Summary. AI infrastructure revenues across major cloud providers narrowly cover depreciation costs when compute assets are written down over 6 years. Demand for AI compute still exceeds supply, and every 10% price cut drives 12–18% more token usage, meaning total spending rises as prices fall.

Azeem Azhar, William Gildea, Hannah Petrovic, Nathan Warren, et al. Exponential View
Date Posted:

Depreciation currently absorbs ~81% of the hyperscalers’ revenue and ~68% of gross AI revenue. Depreciating AI compute assets over 6 years, Azeem Azhar argues “revenues attributable to hyperscalers just about clear the depreciation expense.”

Does AI infrastructure spending grow when compute prices fall?

Core argument: Every 10% token price cut drives 12–18% higher usage, resulting in increased total spending despite lower per-unit costs.

Over the past 12 months, the AI ecosystem generated $110 billion in revenue when you remove double-counting. Annualising the most recent month’s revenues indicates a $175 billion revenue run rate. AI revenues cover the capital investment that’s required to build the infrastructure. Our model separates AI-oriented CapEx from ordinary CapEx across the major hyperscalers and neoclouds, the specialist AI cloud providers. This adjustment is important because hyperscalers were already spending around $120 billion annually on CapEx before ChatGPT. We capture the additional investment in AI infrastructure, then depreciate compute assets over 6 years and other infrastructure over 14 years. Our modelling shows that revenues attributable to hyperscalers just about clear the depreciation expense. Six years is defensible. That longer useful life reflects that, one, demand still exceeds available AI compute, and two, operators are getting better at managing GPU fleets. Both help. The second alone is enough to justify a longer economic life.

Takeaways by Macro Roundup® AI

  1. Every 10% token price cut drives 12–18% higher usage, resulting in increased total spending despite lower per-unit costs.
  2. The State of the AIEconomy.
  3. This adjustment is important because hyperscalers were already spending around $120 billion annually on CapEx before ChatGPT.

Related Articles:

  • Semiquincententacles — Frontier AI labs are shifting to usage-based pricing that reflects total costs, raising token prices and pushing some enterprises toward cheaper open models for routine tasks, while frontier models remain essential for high-performance applications like cybersecurity and scientific discovery.
  • Why .400 Hitters Disappeared — and What It Means for AI — As AI model performance converges toward a ceiling, relative gains per improvement cycle shrink, transforming frontier capability from a pricing moat into a commodity where price becomes the primary differentiator and margin pressure intensifies across leading providers.
  • Four Takeaways from Microsoft’s Satya Nadella at WEF Today — Citing Microsoft’s Nadella’s comments on the state of frontier LLMs “at this point it’s a multi-model world” and “token pricing basically drops by a half…
Showing 91 database articles primarily about Investment