AI's Real Bottleneck: Beyond the GPU

Summary

Microsoft's planned $190 billion capital expenditure this year highlights a critical constraint not in processing power, but in the fundamental manufacturing of AI components. The bottleneck lies deep in the supply chain, affecting chips, high-bandwidth memory, packaging, and optical networking, rather than just GPUs themselves. Major tech players like Meta and Amazon are also investing massively, underscoring a shift for software companies to operate like physical infrastructure providers. This requires a new approach to vendor contracts, focusing on guaranteed capacity and allocation terms rather than traditional software agreements. Key questions for AI investments now revolve around supply chain resilience, efficient model routing, and understanding the hidden human supervision in AI workflows, as the 'intelligence economy' is built on a physical factory system, not just elastic compute.