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I'd still love to see a report that accurately captures training cost. Today's report[1] notably excludes training cost. Not just "one training run," but the c
by gcr 1y ago
I'd still love to see a report that accurately captures training cost. Today's report[1] notably excludes training cost.
Not just "one training run," but the cost of a thousand AI engineers starting failing runs to get to that one deployed model.
1: Link to Google's tech report: https://services.google.com/fh/files/misc/measuring_the_environmental_impact_of_delivering_ai_at_google_scale.pdf https://services.google.com/fh/files/misc/measuring_the_envi... "We leave the measurement of AI model training to future work."
- xnx 1y ago> I'd still love to see a report that accurately captures training cost. Today's report[1] notably excludes training cost. From 2022, so possibly out of date: "ML training and inference are only 10%–15% of Google’s total energy use for each of the last three years, each year split ⅗ for inference and ⅖ for training." That's probably close enough to estimate 50/50, or the full energy cost to deliver an AI result is double the inference energy. https://research.google/blog/good-news-about-the-carbon-footprint-of-machine-learning-training/ https://research.google/blog/good-news-about-the-carbon-foot...
- jeffbee 1y agoIt still kills me, every time, that the title embedded in the metadata of that original PDF is "Revamped Happy CO2e Paper".
- gcr 1y agoMy gosh you're right! The paper in question is https://arxiv.org/pdf/2204.05149 https://arxiv.org/pdf/2204.05149, "The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink"