AI is changing the grid. Could it help more than it harms? Massive data centers are pushing energy demand higher. Some people claim that AI will be a net benefit for the grid. The rising popularity of AI is driving an increase in electricity demand so significant it has the potential to reshape our grid. Energy consumption by data centers has gone up by 80% from 2020 to 2025 and is likely to keep growing.

The Twelfth International Conference on Learning Representations (ICLR2024) took place from 7-11 May in Vienna. The program included workshops, contributed talks, affinity group events, and socials. There were also seven invited talks that covered a broad range of topics. In this post, we give a summary of the talk by Priya Donti. Priya's research focuses on machine learning for forecasting, optimization, and control in power grids. She is an Assistant Professor and the Silverman (1968) Family Career Development Professor at MIT.

This post contains a list of the AI-related seminars that are scheduled to take place between 11 July and 31 August 2023. All events detailed here are free and open for anyone to attend virtually. APOLLO: an AI driven national platform for CT coronary angiography for clinical and industrial applications Speaker: Lee Hwee Kuan Organised by: Cambridge Centre for AI in Medicine Sign up here. Title to be confirmed Speaker: To be confirmed Organised by: I can't believe it's not better (ICBINB) Check the website nearer the time for instructions on how to join. Distributed communication-constrained learning Speakers: Alexander Jung (Aalto University), Danijela Cabric (UCLA), Stefan Vlaski (Imperial College London), Lara Dolecek (UCLA), Yonina Eldar (Weizmann Institute of Science) Organised by: One World Signal Processing To receive the link to attend, sign up to the mailing list.

It's this indistinct picture of both what the technology is and what it can do that might engender a look of uncertainty on someone's face when asked the question, "Can AI solve climate change?" "Well," we think, "it must be able to do something," while entirely unsure of just how algorithms are meant to pull us back from the ecological brink. The question is loaded, faulty in its assumptions, and more than a little misleading. It is a vital one, however, and the basic premise of utilizing one of the most powerful tools humanity has ever built to address the most existential threat it has ever faced is one that warrants our genuine attention. Machine learning -- the subset of AI that allows for machines to learn from data without explicit programming -- and climate change advocacy and action are relatively new bedfellows.

This month marks a year since we launched our focus series on the UN sustainable development goals (SDGs). Since then, we've published AI work pertaining to eight of the goals. We've had the pleasure of hearing from many experts with interesting stories to tell about their research. Here, we compile some of our favourite interviews and articles from the across the series. Interview with Lily Xu – applying machine learning to the prevention of illegal wildlife poaching Lily Xu tells us about her work applying machine learning and game theory to wildlife conservation.

The most recent webinar in the Climate Change AI series covered machine learning for climate science and Earth observation. We heard from two experts in the field, and you can watch the recording below. Maike Sonnewald spoke about trustworthy AI for climate analysis, and Gustau Camps-Valls talked about physics-aware machine learning for Earth sciences. In her presentation, Maike put forward a blueprint for a transparent machine learning application that reveals 3D ocean current structures from surface fields in climate models. She talked about how she applies this to predict ocean current changes.

Welcome to our June 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. In this edition we cover RoboCup 2021, take a look at a new comic series, ask "what is AI?", and treat our ears to some music composed with the help of AI. This month saw the running of RoboCup 2021 as a fully remote event with competitions and activities taking place all over the world. In this article, RoboCup President Peter Stone wrote about RoboCup and its role in the history and future of AI. In the run up to the event we had the pleasure of talking to members of the executive and organising committees for four different leagues within the RoboCup family.

In December 2020 we launched a focus series AI for Good: UN sustainable development goals (SDGs). Each month we pick a different sustainable development goal (SDG) and highlight work in that area. February was the turn of UN SDG number 13: climate action. In this summary article we highlight some of work at the intersection of AI and climate science. Climate Change AI (CCAI) is a volunteer-led effort bringing together people from academia, industry, and the public sector.

Konstantin Klemmer is a PhD student at the University of Warwick working at the intersection of machine learning and geographic data. He also serves as the Communications Chair for Climate Change AI. We talked about his research and the Climate Change AI organisation. Climate Change AI (CCAI) is a volunteer run organisation that catalyses impactful work at the intersection of climate change and machine learning by providing education and infrastructure, building a community, and advancing discourse. We also run a forum and regular community events like our fortnightly happy hour.

While artificial intelligence (AI) is often associated with the spawning of robots that will take our jobs, Terminator's Skynet, or the unblinking red eyes of Hal 9000 in 2001: A Space Odyssey, its true and immediate effects are best seen by simply observing the innovations -- ones that prove that software can do a variety of tasks better than humans can. If one thing is clear, it's that artificial intelligence has the potential to disrupt every industry, which leads to a big question that should matter to all of us: To what extent can a powerful technology like artificial intelligence be used to help us tackle climate change? To learn more about how we can leverage artificial intelligence to tackle climate change, I had to chat with Priya Donti, who's completing a Ph.D. in Computer Science and Public Policy at Carnegie Mellon University, focused on the role machine learning can play in climate change mitigation solutions. Donti is also a co-chair of Climate Change AI, an organization that unites "volunteers from academia and industry who believe in using machine learning, where it is relevant, to help tackle the climate crisis." Our conversation, which has been edited for length and clarity, discusses the risks, the rewards, and the limitations of using artificial intelligence to combat climate change.