Category
7 posts on the GreenPT blog filed under Sustainability.
Sustainability
AI can cut emissions and waste, but it can also add its own footprint. A practical framework for using AI where it measurably reduces impact, with traceable assumptions.
Read article
Sustainability
A practical guide to where ML energy use really comes from, what to measure, and which efficiency techniques cut compute without quietly breaking model quality.
Read article
Sustainability
Most AI runs on someone else's coal. GreenPT runs on European wind and sun, at up to 40% lower CO₂ per query, without trading off model quality. Here's how the math works.
Read article
Sustainability
AI isn't sustainable by default. Energy use, data centres and hardware churn all carry a real footprint. Here's how to use AI that actually advances sustainable development goals.
Read articleSustainability
Every AI query has a footprint. From chip manufacturing to daily inference, the emissions add up. Here is what they look like, and why a low-impact model matters more than ever.
Read articleSustainability
Behind every AI-powered tool sits a data centre that drinks electricity, water, and rare metals. Here is what AI actually costs the planet, and how GreenPT brings the numbers down.
Read article
Sustainability
GreenPT proposes mWh per 100 tokens as a new standard for AI energy transparency. Real-time 1-second sampling supports SCI reporting and makes efficiency a product decision, not an afterthought.
Read article
