Beyond FLOPs: Engineering transparency into AI’s carbon footprint

As AI models scale, so does their hidden cost: CO₂.

While few teams have the tools or methodology to accurately measure the carbon impact of inference, new frameworks are emerging to make energy use visible and actionable.

In this session, Salesforce and Scaleway will share how they’re building the foundations for transparent and standardized measurement of AI’s environmental footprint:

Salesforce will present the AI Energy Score, a standardized method developed with Hugging Face to evaluate model energy efficiency.

Scaleway will show how it translates hardware and GPU utilization data into carbon metrics through its Environmental Footprint Calculator.

The discussion will cover:

• defining system boundaries and measurement granularity (GPU, node, workload)
• linking energy data to model activity and emissions factors
• trade-offs between accuracy, overhead, and reproducibility
• how standardized measurements can inform model optimization, deployment strategy, and industry benchmarks.

A practical deep dive for ML and infra engineers who want to make “energy-efficient AI” measurable, not mythical.