Can your AI save more energy than it uses?
Projects that use AI to optimise things rarely count the AI's own energy. Without that number, a 'green' AI project can be net negative.
GreenCode worked out the energy cost of its own AI, and it turns down work that would not pay that back.
GreenCode helps tackle this by setting its own AI footprint against the saving it makes, in its climate case. It measures reductions in absolute terms and shows owners where capacity can be retired, so a saving is banked rather than spent. More on this.
Can your AI save more energy than it uses? Many projects use AI to make things more efficient. But they rarely count the energy the AI itself uses. Without that number, you cannot tell if you are ahead. A green AI project can end up using more than it saves. Here is the fix you can use today. Estimate the AI's energy for each run, from the provider's published figures. Tools like CodeCarbon and the AI Energy Score help you put a number on it. Set that against the saving, over the years the result is in use. Skip runs where the return does not justify the AI's energy. GreenCode worked out the energy cost of its own AI. It turns down work that would not pay that back. GreenCode helps tackle this by measuring each saving in absolute terms, in its climate case. It shows where capacity can be retired, so the saving is kept, not spent. That was GreenCode Tech Tip number nineteen. Follow for the next tip, and find more on greencode.ai/tech-tips.
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