Event Details

Speakers: Roy Schwartz and Loïc Lannelongue - Energy impacts of ML/AI Roy is a senior lecturer at the School of Computer Science and Engineering at The Hebrew University of Jerusalem (HUJI) and Loïc is doing a PhD at the University of Cambridge

Title: Green AI

Abstract

The computations required for deep learning research have been doubling every few months, resulting in an estimated 300,000x increase from 2012 to 2018. This trend has led to unprecedented success in a range of AI tasks. In this talk I will discuss a few troubling side-effects of this trend, touching on issues of lack of inclusiveness within the research community, challenges in adoption of the technology, and an increasingly large environmental footprint.

I will then present Green AI – an alternative approach to help mitigate these concerns. Green AI is composed of two main ideas: increased reporting of computational budgets, and making efficiency an evaluation criterion for research alongside accuracy and related measures. I will discuss these two ideas, presenting recent efforts and open questions.

This is joint work with Dallas Card, Jesse Dodge, Oren Etzioni, Suchin Gururangan and Noah A. Smith.

Bio

Roy Schwartz is a senior lecturer at the School of Computer Science and Engineering at The Hebrew University of Jerusalem (HUJI). Roy studies natural language processing and artificial intelligence. Prior to joining HUJI, Roy was a postdoc (2016-2019) and then a research scientist (2019-2020) at the Allen institute for AI and at the School of Computer Science and Engineering at The University of Washington, where he worked with Noah A. Smith. Roy completed his Ph.D. in 2016 at the School of Computer Science and Engineering at HUJI, where he worked with Ari Rappoport. Roy’s work has appeared on the cover of the CACM magazine, and has been featured, among others, in the New York Times, MIT Tech Review, and Forbes.

Title: Green computing made easy

Abstract

The carbon footprint of (scientific) computing is a growing source of concern, and there is widespread interest in the research community; so why is this issue still often overlooked? One reason is the perceived barrier to entry to green computing, both in terms of time and resources needed to estimate and reduce the environmental impact of our work. Tackling this issue and reducing frictions for scientists is what motivated the Green Algorithms project. We will discuss what we learned along the way, what still needs to be done as well as simple and impactful ways by which scientists and institutions can make their research more sustainable.

Bio

Loïc Lannelongue is finishing a PhD at the University of Cambridge working at the intersection of AI and biology. In parallel of his research, he has led the development of the Green Algorithms project, which aims at raising awareness about the carbon footprint of computational research across all fields of science. He has also published “Ten simple rules to make your computing more environmentally sustainable” and recently a blog article in BCS' IT Now about the impact of High Performance Computing. Prior to that, Loïc was at the University of Oxford and ENSAE Paris in France.

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