AI Reading List: Sciences: Mathematics
Below is a portion of my informal list of readings related to Artificial Intelligence (AI). This started out as a very short list created for use in conjunction with an academic presentation and has now grown much larger. Please let me know if you have any corrections, additions, suggestions, etc. It is very idiosyncratic and not meant to be comprehensive. Please feel free to share with others.
Artificial Intelligence (AI) Reading List, by Philip Rubin
Sciences — Mathematics:
Kevin Hartnett. To Teach Computers Math, Researchers Merge AI Approaches. Quanta Magazine, Feb. 15, 2023.
Ben Brubaker. AI Reveals New Possibilities in Matrix Multiplication. Quanta Magazine, Nov. 23, 2022.
Charles Q. Choi. When AI “Played” Math, It Cracked an Internet Chokepoint. IEEE Spectrum, Oct. 26, 2022.
Junaid Mubeen. How Breaking the Rules of Math Will Give Us an Edge Over AI. Gizmodo, Oct. 21, 2022.
Dina Genkina. Machine Learning’s New Math New number formats and basic computations emerge to speed up AI training. IEEE Spectrum,, Oct. 18, 2022.
Alhussein Fawzi, Matej Balog, Bernardino Romera-Paredes, Demis Hassabis, and Pushmeet Kohli. Discovering novel algorithms with AlphaTensor. DeepMind.com, Oct. 5, 2022.
John Horgan. Should Machines Replace Mathematicians? Scientific American, July 8, 2022.
University of Cambridge. Mathematical paradoxes demonstrate the limits of AI. ScienceDaily, Mar. 17, 2022.
Leila Sloman. In New Math Proofs, Artificial Intelligence Plays to Win. Quanta Magazine, Mar. 7, 2022.
Ben Dickson. DeepMind’s AI can untangle knots. But does it guide human intuition? TechTalks, Dec. 13, 2021.
Alex Davies, et al. Advancing mathematics by guiding human intuition with AI. Nature, 600, 70–74, 2021.
Guillaume Lample and François Charton. Deep Learning for Symbolic Mathematics. arXiv:1912.01412, Dec. 2, 2019.