The environmental cost of generative AI

In recent months, excitement about -- and use of -- generative AI tools such as ChatGPT, BERT, LaMDA, GPT-3, DALL-E-2, MidJourney, and Stable Diffusion has grown exponentially. On the other hand, very little attention has been given to the environmental costs of these tools. But with pressure on to monitor carbon emissions and report ESG issues, companies cannot afford to ignore this important issue. Learn why training a single AI model can emit as much carbon as five cars in their lifetimes and what companies should do to create greener AI systems. Join TechTarget's Diann Daniel as she discusses these important issues with Sajjad Moazeni, Assistant Professor of Electrical and Computer Engineering at the University of Washington, and Shaolei Ren, Associate Professor of Electrical and Computer Engineering at the University of California, Riverside. For more on sustainability and ESG visit https://www.techtarget.com/sustainability/ and for more on AI, visit https://www.techtarget.com/searchenterpriseai/ Moderator: Diann Daniel - TechTarget Editorial Panelists: • Sajjad Moazeni - Assistant Professor of Electrical and Computer Engineering (ECE), Emerging Integrated Technologies & Systems Lab (EMIT Lab) at the University of Washington, Seattle • Shaolei Ren - Associate Professor of Electrical and Computer Engineering, Cooperating Faculty of Computer Science and Engineering at the University of California, Riverside