We discuss why AI is hard and why physics is simple. We discuss how physical intuition and the approach of theoretical physics can be brought to bear on the field of artificial intelligence and specifically machine learning. We suggest that the underlying project of machine learning and the underlying project of physics are strongly coupled through the principle of sparsity, and we call upon theoretical physicists to work on AI as physicists. As a first step in that direction, we discuss an upcoming book on the principles of deep learning theory that attempts to realize this approach.
翻译:我们讨论为什么AI是硬的,为什么物理学是简单的。我们讨论如何将物理直觉和理论物理学方法应用到人工智能领域,特别是机器学习领域。我们建议机器学习的基本项目和物理基础项目通过偏狭原则紧密结合,我们呼吁理论物理学家以物理学家的身份研究AI。 作为朝这个方向迈出的第一步,我们讨论即将出版的一本关于试图实现这一方法的深层次学习理论原则的书。