Environmental Impact of Generative and Agentic AI: An in-Depth Analysis and Green Solutions
cs.CY, cs.AI
Submitted: 2026-09-26
Updated: 2026-09-26
Terminology
Sources
- Attention Is All You Need
- LLaMA: Open and Efficient Foundation Language Models
- Scaling Laws for Neural Language Models
- Training Compute-Optimal Large Language Models
- GPT-4 Technical Report
- Gemini: A Family of Highly Capable Multimodal Models
- AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
- HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
- Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
- Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models
- Energy Usage Reports: Environmental awareness as part of algorithmic accountability
- Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Models
- Fine-Tuning Language Models from Human Preferences
- Parameter-Efficient Transfer Learning for NLP
- Training language models to follow instructions with human feedback
- LoRA: Low-Rank Adaptation of Large Language Models
- Constitutional AI: Harmlessness from AI Feedback
- Carbon Emissions and Large Neural Network Training
- Fast Inference from Transformers via Speculative Decoding
- FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
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