About
Neural architectures designed for machine translation can be used to solve problems of mathematics, by considering that solving amounts to translating the problem, a sentence in some mathematical language, into its solution, another sentence in mathematical language. Presenting examples from symbolic and numerical mathematics, and theoretical physics, I show how such techniques can be applied to develop AI for Science, and help understand the inner workings of language models.
Francois Charton is a research engineer in Meta AI, working on applications of language models to mathematics and science. He is a former student of Ecole Polytechnique, and ENSAE (Ecole Nationale de la Statistique et de l'Administration Economique). He has been in Meta since 2019, and had a career in industry prior to that.
Coffee will be served at 10:30. .
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The talk
Credits and licence
- Institution
- CERN
- Department
- EP-IT Data Science Seminars
- Speaker
- Francois Charton
- Year
- 2024
- Language
- English
- Subjects
- Computer science
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed