New study drops bomb: AI data centers could spew 80M tons of CO2 this year, rivaling NYC’s footprint with zero transparency from Big Tech.
If you’re running LLMs in prod, buckle up – today’s study reveals AI data centers might match a small European country’s carbon output in 2025 alone, guzzling water like the bottled industry and hiding behind vague reports from Google, Meta, and co.[3]
This matters to us devs because our models are the culprits. 32-80 million tons CO2? That’s on us scaling without metrics. Big Tech admits AI spikes energy use but won’t break out AI-specific footprints – transparency fail.[3]
Practical move: Optimize now. Quantize models, inference on edge devices, or hunt green clouds with PUE under 1.1. Tools like MLflow for carbon tracking are free – start logging your deploys. Europe wins on cleaner grids, so hybrid setups? Opinion: Hype trains ignore this; time we build sustainable AI stacks. What’s your go-to for low-carbon inference?[3]
Source: Euronews