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.

AI-developed models of this sort are used by computers to determine the extent and nature of climate changes in specific areas of the globe. Climate informatics experts find that by cross-referencing multiple AI models and predictions, they can accurately determine the short-term effects of climate change. Unfortunately, different AI models will disagree on long-term predictions. The farther into the future a change could take place, the less reliably any individual model could predict such distant events. Minimizing the margin of error for such environmental predictive technology would be an important improvement for future research.

The summer of 2019 gave us some of the clearest examples yet of how climate change is transforming our world. The hottest June ever was followed up with the hottest July ever -- which also turned out to be the hottest month in recorded history. Scientists memorialized the first Icelandic glacier to lose glacier status and predicted the country would be glacier-free in 200 years. And unprecedented wildfires raged in the normally frozen Arctic, throwing up a smoke cloud nearly the size of Europe. The 2018 report from the International Panel on Climate Change gives us a stark time horizon: 20 years.

AI could strip emerging markets of their competitive edge, keep inflation low despite QE, cause huge labour market disruption and drive populism according to a new report. The report – Future proofing your asset allocation in an age of megatrends published by BNY Mellon – shows a huge range of complex challenges facing economies, markets and thus investors from two megatrends – AI and climate change. To compile the report, Create Research conducted detailed interviews with 45 chief investment officers, investment strategists and portfolio managers among asset owners, asset managers and pension consultants in 16 countries. AI is seen as a risk and opportunity by 52%, a risk alone by 33% and a pure opportunity by 7%. The report says that investment-specific challenges related to climate change centre on areas that are unknowable, requiring judgemental calls about the future.

This week I talk to John Platt, a Distinguished Scientist at Google, about twin problems: finding cheap zero-carbon energy sources and mitigating global warming. John is a polymath, having discovered asteroids, helped put the touch in computer touchpads and even won an Academy Award for scientific and technical achievements in computer animation. Now, he is part of a growing movement of machine learning researchers tackling climate change.