3 Tools to Measure Your AI Carbon Footprint

Hosted by Pascal Joly

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What you'll learn

Understand the magnitude of AI's environmental impact

Current state, growth scenarios, training vs. inference footprint, beyond energy.

What steps should you take to measure AI's carbon footprint

Measuring the carbon footprint of AI is the first step before taking action. We'll cover key metrics you need to track.

3 tools to get you started

You will learn and see live demos of 3 open source tools to get you started on measuring AI training and inference.

Why this topic matters

According to the IEA, data centers could consume as much electricity as the Netherlands by 2027. Most of this growth is driven by GenAI. Despite green pledges, data center operators still rely significantly on fossil fuel power—in many regions, over 50% of their energy comes from coal and gas. Understanding your AI's carbon footprint isn't optional—it's a prerequisite to defining solutions.

You'll learn from

Pascal Joly

Sustainability Consultant. 25 year veteran in the IT industry.

Pascal combines deep expertise in data center operations with a focus on AI sustainability. As a Terra.do fellow and certified AI/ML professional, he bridges the gap between technical efficiency and environmental impact. His years of experience optimizing data centers through automation, as an engineer and product leader, gives him unique insights into measuring and reducing AI's carbon footprint.

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