arXiv (All)
open access
Environmental Impact of Generative and Agentic AI: An in-Depth Analysis and Green Solutions
The proliferation of generative and agentic artificial intelligence (AI) systems has introduced computational demands whose environmental consequences are substantial yet underexamined. This paper examines the environmental footprint of modern AI systems across energy consumption, carbon emissions,
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Sustainable science mapping: benchmarking green AI against transformers for cross-disciplinary abstract classification using arXiv.#375555
- A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling#820851
- Quantifying AI impact in energy transitions: The Energy Justice Impact Assessment (EJIA) framework#1078081
- Artificial Intelligence and Climate Risk Shocks#1181267
- Artificial Intelligence and Sustainable Transformation#1181269
Record · ID 1117672
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive