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Efficiency Will Not Lead to Sustainable Reasoning AI

arXiv 2511.15259 ↗First posted 19 Nov 2025cs.AI cs.CYcited by 0

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Abstract (arXiv)

AI research is increasingly moving toward complex problem solving, where models are optimized not only for pattern recognition but for multi-step reasoning. Historically, computing's global energy footprint has been stabilized by sustained efficiency gains and natural saturation thresholds in demand. But as efficiency improvements are approaching physical limits, emerging reasoning AI lacks comparable saturation points: performance is no longer limited by the amount of available training data but continues to scale with exponential compute investments in both training and inference. This paper argues that efficiency alone will not lead to sustainable reasoning AI and discusses research and policy directions to embed explicit limits into the optimization and governance of such systems.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 20 of its 45 references that are in the map. First posted on arXiv 19 Nov 2025.

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References · 20

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  4. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  5. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,211
  6. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  7. 2024A Survey on LLM-as-a-Judgecited by 1,423
  8. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 886
  9. 2025DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decompositioncited by 287
  10. 2023Large Language Model Guided Tree-of-Thoughtcited by 221
  11. 2023Self-Evaluation Guided Beam Search for Reasoningcited by 196
  12. 2025Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learningcited by 180
8 more
  1. 2025Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correctioncited by 154
  2. 2019The role of artificial intelligence in achieving the Sustainable Development Goalscited by 100
  3. 2021Carbon-Aware Computing for Datacenterscited by 41
  4. 2023Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thoughtcited by 41
  5. 2025From Efficiency Gains to Rebound Effects: The Problem of Jevons' Paradox in AI's Polarized Environmental Debatecited by 23
  6. 2020Energy Efficient Computing Systems: Architectures, Abstractions and Modeling to Techniques and Standardscited by 6
  7. 2022Sustainable Computing -- Without the Hot Aircited by 4
  8. 2024Carbon-Aware Quality Adaptation for Energy-Intensive Servicescited by 3

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