Unverified50% confidenceFactExact time
From cloud computing to the mobile internet, and then to model training and inference, compute demand continues to expand over the long cycle.
1
Sources
50%
Confidence
Long-term
Relevance
10/25/2026
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.73% similarUnverifiedThe training of general-purpose large models relies on massive, publicly available, crawlable internet data.73% similarUnverifiedTraining refers to repeatedly iterating model parameters with large-scale data, an offline, long-cycle task; inference is the forward computation process by which the model responds to each user request after going live, a real-time, highly concurrent online task.70% similarUnverifiedTraining refers to the process of adjusting model parameters with massive amounts of data, requiring high-speed multi-GPU interconnection and long periods of stable operation, with extremely high demands on per-GPU compute and memory bandwidth.69% similarUnverified实时在线学习要求智能体在连续流动的时间中同步完成感知、决策与参数更新，与大语言模型训练-推理分离的范式形成对比68% similar
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