Week one at the CMSA: mathematics, computers and AI

Posted on by Chris

Harvard CMSA: Mathematics and Machine Learning

Name
Mathematics and Machine Learning Program (week 1)
Dates
3 to 6 September 2024
Venue
CMSA Room G10, 20 Garden Street, Cambridge, Massachusetts
Host
Center of Mathematical Sciences and Applications, Harvard
Programme
cmsa.fas.harvard.edu

Trip 2 to 6 September 2024 · Written up 6 September 2024 · Last expanded 29 September 2026

The opening week of the CMSA programme and my second visit to Cambridge that year, after the IAIFI workshop in August. Michael R. Douglas’s lecture series on mathematics, computers and AI set the terms for the two months: which mathematical questions are good for ML methods, what autoformalization with LLMs looks like, and how far feed-forward networks get you as universal approximators. The commute across the Charles started here. The following week, and the essay about the programme, has its own pin.

Photographs

Crimson banners on the columns of Widener Library with students on the steps
Widener steps, first week of term.
Romanesque brick facade of Austin Hall at Harvard
Austin Hall. Where the CMSA programme's afternoons started.
Lecture slide relating knot theory invariants, with a camera tripod in front of the screen
Michael Douglas, day one: knot theory invariants as a test case for ML.
Slide titled Autoformalization with LLMs showing informal and formal mathematics linked through a model
Autoformalization with LLMs. Most of why I was there, on one slide.
A full lecture room at the CMSA seen from the back rows with blackboards at the front
Room G10, week one.
A chalkboard covered in equations standing outside under a tent
The blackboard outside. Arguments continued on the lawn.

Links

The programme, and the write-up when it exists. To be added.

Open entry
This page is not finished, and is not meant to be. I add photographs, people and links as I dig them out, so it keeps growing after publication. Why the whole site works this way is on the colophon.

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Published by Chris

Data Scientist, AI Strategist, and now apparently AI researcher. Perpetual student, and also conference/workshop-surfer.