While observers have marveled at the abilities of new generative AI tools such as ChatGPT, BERT, LaMDA, GPT-3, DALL-E-2, MidJourney, and Stable Diffusion, the hidden environmental costs and impact of these models are often overlooked. The development and use of these systems have been hugely energy intensive and maintaining their physical infrastructure entails power consumption. Right now, these tools are just beginning to gain mainstream traction, but it’s reasonable to think that these costs are poised to grow — and dramatically so — in the near future.
How to Make Generative AI Greener
Eight steps companies can take to reduce the carbon footprint of this powerful new technology.
July 20, 2023
Illustration by Alex William
Summary.
Generative AI is impressive, but the hidden environmental costs and impact of these models are often overlooked. Companies can take eight steps to make these systems greener: Use existing large generative models, don’t generate your own; fine-tune train existing models; use energy-conserving computational methods; use a large model only when it offers significant value; be discerning about when you use generative AI; evaluate the energy sources of your cloud provider or data center; re-use models and resources; include AI activity in your carbon monitoring.