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The Future of Compute: NVIDIA's Crown is Slipping

mohitdagarwal.substack.com · 5,626 words · saved by 1 readers

No one has benefitted from the scaling hypothesis quite like NVIDIA. On the back of an AI boom and GPU monopoly, they’ve become the fastest scaling hardware company in history–adding $2T of value in 13 months with SaaS-like margins. While the H100 generation likely represents peak pricing power (new B200s have lower margins and higher COGS), an immediate lack of alternatives means they’ll continue to print cash. The open question is long-term (>6yrs) durability1. Hyperscalers (Google, Microsoft, Amazon, and Meta) are aggressively consolidating AI demand to become the dominant consumers of AI accelerators; while developing competitive, highly-credible chip efforts. Simultaneously, the sheer scale of compute needs has hit limits on capex, power availability, and infrastructure development. This is driving an enormous shift towards distributed, vertically-integrated, and co-optimized systems (chips, racks, networking, cooling, infrastructure software, power) that NVIDIA is ill-prepared to

Jensen Huang delivering the world's first DGX-1 server to OpenAI in 2016. Credit: Tom’s Hardware No one has benefitted from the scaling hypothesis quite like NVIDIA. On the back of an AI boom and GPU monopoly, they’ve become the fastest scaling hardware company in history–adding $2T of value in 13 months with SaaS-like margins. While the H100 generation likely represents peak pricing power (new B200s have lower margins and higher COGS), an immediate lack of alternatives means they’ll continue to print cash. The open question is long-term (>6yrs) durability1. Hyperscalers (Google,…

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