The tech industry, fueled by AI, is experiencing a new high. Big Tech companies are investing heavily in AI infrastructure to meet anticipated future demand. However, Sequoia Capital analyst David Cahn warns of a significant gap between the revenue expectations implied by the AI infrastructure build-out and the actual revenue growth in the AI ecosystem.
Cahn estimated that the annual AI revenue required to pay for these investments was $200 billion. Fast forward to Q4 2024, and that number has climbed to $600 billion annually. This calculation is based on the premise that for every $1 spent on a GPU, roughly $1 needs to be spent on energy costs to run the GPU in a data center.
By Q4 2024, Nvidia’s data center run-rate revenue forecast is predicted to be $150 billion, making its implied data center AI spend $300 billion and the AI revenue required for payback $600 billion. This is a significant challenge, especially when it’s unclear whether the capital expenditure build-out is linked to true end-customer demand or is being built in anticipation of future end-customer demand.
Cahn’s projections suggest that AI revenue required for payback will eventually reach $100 billion, pointing to Nvidia’s recently announced B100 chip, which will have 2.5x better performance for only 25% more cost. This incident underscores the importance of regularly updating passwords and using secure password managers.
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