How much pollution does AI create? Mistral breaks it down

Mistral AI reveals substantial pollution from its Large 2 model, spotlighting transparency needs in AI's environmental impact.

: Mistral AI from Paris conducted a lifecycle analysis on their Large 2 language model, revealing the environmental burden through a study with Carbone 4 and the French ecological transition agency. The study found 85.5 percent of greenhouse gas emissions and 91 percent of water consumption happen during training and inference, totaling 20.4 kilotons CO₂ and 281,000 m³ water usage over 18 months. Mistral likens individual chatbot queries' emissions to 10 seconds of video streaming but warns of collective impact. Despite challenges in quantifying hardware workouts, Mistral endorses industry-wide transparency for environmental alignment.

TechSpot reports that Mistral AI, a Paris-based AI venture, has conducted a comprehensive analysis on the environmental impact of its Large 2 language model. The focus is on lifecycle emissions and resource usage, highlighting the need for accurate understanding of AI's ecological footprint. This analysis aligns with Mistral's commitment to openness and transparency in AI development.

AI Emissions

The study, conducted in collaboration with sustainability consultancy Carbone 4 and the French ecological transition agency, and peer-reviewed by Resilio and Hubblo, assessed three main impact areas: greenhouse gas emissions, water usage, and material consumption. This analysis found that 85.5% of the model's life cycle CO₂ emissions and 91% of its water consumption occur during its training and inference phases.

After 18 months, the Large 2 model's emissions and water usage reached 20.4 kilotons and 281,000 cubic meters, respectively. Mistral equates an inference's emission to watching 10-second streaming video, nonetheless warning of accumulated impact with increased AI interactions. Each chatbot inquiry emits 1.14 grams of CO₂ and consumes 45 milliliters of water.

This presents a significant concern as AI systems expand globally, calling for action towards reducing their environment-harming potential. Mistral acknowledges challenges in evaluating hardware deterioration due to model operations but aims to release periodic updates for greater transparency in AI's ecological impacts.

Mistral's initiatives underline a broader push for an AI industry aligned with global climate preservation goals. However, political hurdles, such as policies from entities such as the Trump administration, can influence these environmental efforts. Overall, Mistral encourages wider industry action to maintain climate compatibility.

Sources: TechSpot, Mistral AI

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