Moore's Law
moore-s-law-f331f3f0·2 events·first seen 28d agoAliases: Moore's Law
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AI and Compute: OpenAI Analysis of Exponential Growth in Training Compute Since 2012
OpenAI published an analysis in May 2018 showing that compute used in the largest AI training runs has been doubling every 3.4 months since 2012, far outpacing Moore's Law's 2-year doubling period. Over the 2012–2018 period, this metric grew by more than 300,000x. The analysis frames compute scaling as a key driver of AI progress and argues for preparing for systems with capabilities well beyond those of the time.
AI and Efficiency: Algorithmic Progress Halving Training Compute Every 16 Months Since 2012
OpenAI released an analysis showing that compute required to match AlexNet-level ImageNet performance has decreased 44x since 2012, with algorithmic efficiency doubling every 16 months. This outpaces Moore's Law, which would have yielded only an 11x improvement over the same period. The findings suggest that for heavily-invested AI tasks, algorithmic progress is a larger driver of efficiency gains than hardware improvements alone.