In this episode of the ESG Insider podcast, we explore the role artificial intelligence can play in advancing sustainability outcomes — and how the energy demands from generative AI programs could change over time.
We talk with Hussein Shel, Chief Technologist and Head of Upstream Digital Transformation, Energy and Utility at Amazon Web Services (AWS), a cloud-computing and technology services company and a subsidiary of Amazon.
AI has been a major focus at sustainability events throughout 2024 and will be a topic at the UN’s COP29 climate change conference in Baku, Azerbaijan, which begins Nov. 11.
In the interview, Hussein explains how AWS is leveraging AI, machine learning and more efficient computing hardware to address sustainability challenges, particularly in optimizing energy usage and integrating renewables onto the grid.
"Most of these models are getting more and more optimized,” Hussein says. “They're becoming more and more intelligent ... reducing potentially the consumption of energy needed to retrain."
This interview took place on the sidelines of The Nest Climate Campus, where ESG Insider was an official podcast during Climate Week NYC.
Listen to our interview with the head of the Electric Power Research Institute on how AI is driving up electricity demand: https://www.spglobal.com/esg/podcasts/ceraweek-how-energy-transition-discussions-are-shifting
This piece was published by S&P Global Sustainable1, a part of S&P Global.
Copyright ©2024 by S&P Global
DISCLAIMER
By accessing this Podcast, I acknowledge that S&P GLOBAL makes no warranty, guarantee, or representation as to the accuracy or sufficiency of the information featured in this Podcast. The information, opinions, and recommendations presented in this Podcast are for general information only and any reliance on the information provided in this Podcast is done at your own risk. This Podcast should not be considered professional advice. Unless specifically stated otherwise, S&P GLOBAL does not endorse, approve, recommend, or certify any information, product, process, service, or organization presented or mentioned in this Podcast, and information from this Podcast should not be referenced in any way to imply such approval or endorsement. The third party materials or content of any third party site referenced in this Podcast do not necessarily reflect the opinions, standards or policies of S&P GLOBAL. S&P GLOBAL assumes no responsibility or liability for the accuracy or completeness of the content contained in third party materials or on third party sites referenced in this Podcast or the compliance with applicable laws of such materials and/or links referenced herein. Moreover, S&P GLOBAL makes no warranty that this Podcast, or the server that makes it available, is free of viruses, worms, or other elements or codes that manifest contaminating or destructive properties.
S&P GLOBAL EXPRESSLY DISCLAIMS ANY AND ALL LIABILITY OR RESPONSIBILITY FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, CONSEQUENTIAL OR OTHER DAMAGES ARISING OUT OF ANY INDIVIDUAL'S USE OF, REFERENCE TO, RELIANCE ON, OR INABILITY TO USE, THIS PODCAST OR THE INFORMATION PRESENTED IN THIS PODCAST.
