The Hidden Costs Behind Generative AI's Economics

TL;DR Summary
Ed Zitron argues that the economics of generative AI are fundamentally broken: subscription pricing conceals the true per-token costs, data-center capitalism is brutally capital-intensive with slim margins and heavy debt, and OpenAI/Anthropic depend on unsustainable burn rates and venture funding. As token-based billing spreads (e.g., Copilot), the industry faces a reckoning where profitability seems unattainable, media coverage often understates real costs, and investors may rethink AI bets as revenue targets appear impossible to reach.
- AI's Economics Don't Make Sense Ed Zitron's Where's Your Ed At
- Changes to GitHub Copilot Individual plans The GitHub Blog
- GitHub will start charging Copilot users based on their actual AI usage Ars Technica
- Microsoft’s GitHub Changes AI Prices Again in Shift to Consumption-Based Fees The Information
- Microsoft's GitHub shifts to metered AI billing amid cost crisis theregister.com
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