{
  "id": 6682529,
  "title": "Characterizing Job Power Elasticity for Power-Flexible AI Training",
  "url": "https://urgent.news/2026/09/10/characterizing-job-power-elasticity-for-power-flexible-ai-training",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-10T13:40:13.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.11542v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Large language model (LLM) training is among the fastest-growing sources of electricity demand in modern data centers, and power availability is a primary bottleneck to continued AI infrastructure growth. Making the power consumption of these workloads flexible could unlock additional power for AI growth, limit increases in electricity prices, and improve the utilization of existing grid…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}