Abstract
The remarkable advancements in artificial intelligence have transformed industrial productivity and propelled scientific discovery. Its history and the flow of trends parallel those of physics: leveraging insights from procedural algorithms to explain empirical results and then seeking optimality for a principled understanding of the system. In this article, I will recollect some of those patterns in history and envision the progress of future understanding. A good understanding has led the community to new ideas by providing focus and setting trends for future exploration. Through mathematical insights into real-world problems, those with a background in physics can uncover novel and nontrivial knowledge in machine learning.
Published Version
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