Unverified60% confidenceTradeoffExact time
Training and running large models requires enormous computing power and electricity, and the surge in energy demand from data centers creates tension with global carbon neutrality goals.
2
Sources
60%
Confidence
Long-term
Relevance
9/13/2026
First Seen
Sources
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Related Claims
UnverifiedAs demand for large model training and inference grows, power consumption at data centers worldwide continues to rise.79% similarVerifiedTraining a frontier large model requires hundreds of millions of dollars in compute, data cleaning, and human labor.77% similarUnverifiedThe demand for GPU computing power to train and run inference on large models is growing explosively, making data centers and their supporting power supply the scarcest resources in the industry75% similarVerifiedTraining frontier large models requires enormous computational investment, and there are diminishing marginal returns as model scale increases.73% similarUnverifiedTraining and running large models requires large GPU clusters, high-speed interconnect networks, and supporting power facilities, and these investments carry extremely high fixed costs and long construction cycles.71% similar
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