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The article argues that even though cloud compute instances aren’t identical like gold, markets can still commoditize them by establishing a standard reference (e.g., Nvidia’s DGX spec) and trading basis spreads for performance, operator, SLA, location, and scale. It shows that non-fungibility isn’t a blocker but defines the layers a future compute commodity market would need to price.
The article explores the concept that AI advancements follow a predictable pattern, which the author refers to as “straight lines on graphs.” It discusses the uneven capabilities of AI across different tasks while suggesting that the rate of improvement remains consistent. The author also speculates on the impact of reinforcement learning and compute resources on future AI development.