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Colloquium

Mark Hughes, Brigham Young University

A three-pronged approach to using machine learning in pure mathematics

Date:
Time:
4:00 pm–4:50 pm
Avery Hall Room: 115
Additional Info: AVH
Contact:
Alex Zupan
With recent breakthroughs in AI like Chat-GPT and DALL-E 2 making headlines, it’s natural to ask what role machine learning will play in fields such as science, technology, business, and education. In this talk I will outline three broad modes through which machine learning can be applied to the field of pure mathematics. The main examples I will use come from the fields of knot theory and low-dimensional topology, though I will also include examples from other fields of pure mathematics where applicable. These applications will range from approaches that have already been successfully implemented to more speculative works-in-progress.

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This event originated in Math.