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The Environmental Impact of Artificial Intelligence: Mistral AI’s Transparent Analysis

Article Highlights:
  • Mistral AI analyzes the environmental impact of language models
  • Training and inference are the most polluting phases
  • CO₂ emissions and water consumption tracked throughout the lifecycle
  • A single chatbot query has a marginal impact, but cumulative effects matter
  • Mistral AI advocates for transparency and sustainability in the AI sector
The Environmental Impact of Artificial Intelligence: Mistral AI’s Transparent Analysis

Artificial Intelligence and Its Impact on the Planet

The global adoption of Artificial Intelligence (AI) is transforming industries and daily life, but it also raises crucial questions about the environmental footprint of these technologies. Mistral AI, a French startup specializing in open-source language models, recently published a detailed lifecycle analysis of one of its models, highlighting the need for greater transparency in the sector.

A Study Driven by Transparency

To assess the environmental impact of the Mistral AI Large 2 model, the company partnered with Carbone 4 and the French ecological transition agency, with results peer-reviewed by environmental experts. The study focused on three key areas: greenhouse gas emissions, water use and depletion, and material consumption.

The Most Impactful Phases: Training and Inference

The research confirmed that training and inference are the most environmentally demanding stages. According to Mistral, 85.5% of total CO₂ emissions and 91% of water consumption occur during model development and user interaction.

  • 20.4 kilotons of CO₂ emitted in 18 months
  • 281,000 cubic meters of water consumed
  • A single chatbot query equals 1.14 grams of CO₂ and 45 ml of water

Marginal but Cumulative Impact

A single interaction with the “Le Chat” chatbot produces emissions comparable to 10 seconds of streaming video in the US. However, the cumulative effect of millions of users can become significant for the environment.

Limitations and Future Perspectives

Mistral AI acknowledges the challenges in accurately quantifying hardware degradation caused by data center workloads. Nevertheless, the reported figures align with estimates from other studies and institutions.

"Tackling complex problems by breaking them down, verifying answers, and self-correcting in real time—traits that bring AI closer to human reasoning."

Sam Altman, CEO OpenAI

Towards Greater Transparency and Sustainability

Mistral AI is committed to regularly updating its environmental impact reports and calls on the entire industry to embrace transparency. The goal is to align AI development with global climate objectives, despite diverging policies from some governments.

Artificial Intelligence and Its Impact on the Planet The global adoption of Artificial Intelligence (AI) is transforming industries and daily life, but it [...] Evol Magazine
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