Perspectives on the State and Future of Deep Learning - 2023
Micah Goldblum
A. Anandkumar
Richard Baraniuk
Tom Goldstein
Kyunghyun Cho
Zachary Chase Lipton
Melanie Mitchell
Preetum Nakkiran
Max Welling
Andrew Gordon Wilson

Abstract
The goal of this series is to chronicle opinions and issues in the field of machine learning as they stand today and as they change over time. The plan is to host this survey periodically until the AI singularity paperclip-frenzy-driven doomsday, keeping an updated list of topical questions and interviewing new community members for each edition. In this issue, we probed people's opinions on interpretable AI, the value of benchmarking in modern NLP, the state of progress towards understanding deep learning, and the future of academia.
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