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Moore's Law for AI Compute

Moore's law for AI compute is an analogy used to discuss recurring improvements in the cost or capability of computing available for AI.

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The original semiconductor observation does not directly predict end-to-end AI progress, which also depends on algorithms, memory, networking, energy, data, and utilization. Any claimed trend therefore needs a defined metric and time period.

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