AI RESEARCH
AI Cap-and-Trade: Efficiency Incentives for Accessibility and Sustainability
arXiv CS.AI
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ArXi:2601.19886v2 Announce Type: replace-cross The race for artificial intelligence (AI) dominance often prioritizes scale over efficiency. Hyper-scaling is the common industry approach: larger models, data, and as many computational resources as possible. Using resources is a simpler path to improved AI performance. Thus, efficiency has been de-emphasized. Consequently, the need for costly computational resources has marginalized academics and smaller companies. Simultaneously, increased energy expenditure, due to growing AI use, has led to mounting environmental costs.