深度学习的现状与未来展望 -- 2023
Perspectives on the State and Future of Deep Learning -- 2023
December 7, 2023
作者: Micah Goldblum, Anima Anandkumar, Richard Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson
cs.AI
摘要
本系列的目标是记录机器学习领域的观点和问题，包括当前的情况以及随着时间的推移发生的变化。计划定期举办这项调查，直到人工智能的奇点、纸夹狂热驱动的世界末日，持续更新主题问题列表，并为每期采访新的社区成员。在本期中，我们探讨了人们对可解释人工智能、现代自然语言处理中基准测试的价值、对深度学习理解进展的现状，以及学术界的未来。
English
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.