Videos are online for the 2026 Math of Data Summer School: ims.nus.edu.sg/events/ma_dat…

"The Gold Rush in AI4Math: Where Are We Now?" arxiv.org/abs/2608.24961 Is substantive AI use in math research increasing? Which subfields are most affected? What problems have been solved? Who is writing them—and which AI models are they using? An empirical study of 32,944 math arXiv submissions from Mar. 1–Aug. 20, 2026.

This University of Chicago business school professor has authored 258 academic papers in 2026 (so far). statmodeling.stat.columbia.e…

If you are interested in probabilistic combinatorics, there is going to be a workshop at Rutgers celebrating the amazing Jeff Kahn in October. The speaker list is stellar. probcomb.github.io/

Artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships, and do not know from within what love, work, friendship or responsibility mean. Nor do they have a moral conscience, since they do not judge good and evil, grasp the ultimate meaning of situations, or bear responsibility for consequences. They may imitate or even simulate, but they do not understand what they produce, for they lack the affective, relational, and spiritual perspective through which human beings grow in wisdom. #MagnificaHumanitas

Imagine if Erdos were still alive with a GPT-5.5 Pro subscription and amped up on amphetamines.

I think frontier AI labs should hire people who either: - at least pretend to care about the people affected by their products - can make good jokes? I talk to brilliant young people every day, terrified about the future. This callousness from those inside is sad.

There is a case to be made that the future of Mathematics is very bright. In my mind, proofs have always been a tool to achieve a goal. The goal was and still is to understand, and reading/writing proofs (or just know that they exist) will remain part of it.

AI is getting great at math, but how good is it at solving real research problems in areas outside of those covered by Erdős problems? Towards gauging this, I have started putting together a list of unsolved research problems in mathematical statistics and machine learning, sourced from recent papers in a leading statistics journal, the Annals of Statistics (with some bonus COLT open problems: solveall.org/. Currently >100 problems. In my view, much of the value of AI for researchers in the mathematical sciences stems from helping with their own research problems. These are problems without known solutions. There are many math benchmarks, but few with the following properties: (1) of a realistic research-level, so that solving them can potentially lead to a publication in a top journal (problems discussed in papers already, not contest math, not Millenium problems, not problems created for a benchmark, not problems that have a known solution); I'd say Erdős problems are the best example of this. (2) cover problems outside of the usual focus (combinatorics, number theory, ... ) of Erdős problems. Especially under-represented are domains of applied math, along with statistics, operations research, etc. I'm interested in statistics and ML, so that's where I started, but this could grow over time. Hope this can grow into something useful to the community! Happy to hear your thoughts...

🚨 2026 @Princeton ML Theory Summer School Mini-courses by: - Subhabrata Sen @subhabratasen90 - Lenaic Chizat @LenaicChizat - Sinho Chewi - Elliot Paquette @poseypaquet - Elad Hazan @HazanPrinceton - Surya Ganguli @SuryaGanguli August 3 - 14, 2026 Apply by March 31. Link 👇 Sponsors: @NSF, @PrincetonAInews, @EPrinceton @JaneStreetGroup, @DARPA, @PrincetonPLI, Princeton NAM, Princeton AI2, Princeton PACM Some amazing speakers from previous years: @Andrea__M, @TheodorMisiakie, @KrzakalaF, @_brloureiro, @rakhlin, @DimaKrotov, @CPehlevan, @SoledadVillar5, @SebastienBubeck, @tengyuma

If you are a midcareer or senior level world class researcher in statistics or computer science interested in moving to the University of Toronto, DM me.

🚀 Call for Papers: Special Issue on Frontiers in Statistical Learning: Data, Networks, and Knowledge Transfer Journal: Statistical Learning and Data Science (SLADS) 📅 Submission Deadline: March 31, 2026 👨‍🎓 Guest Editors: Yang Feng, Guangming Pan, Jiaming Xu, Emma Zhang

I'm hiring a Student Researcher to work on scaling laws at Google DeepMind! Project is for 16 weeks, starting spring/summer '26, in-person in SF (pic from the amazing office). If you're interested, fill out this form: forms.gle/MsgPfJumTLLobNtB7

I am recruiting PhD students at @NYU_Courant to conduct research in learning theory, algorithmic statistics, and trustworthy machine learning, starting Fall 2026. Please share widely! Deadline to apply is December 12, 2025.

ITA 2026 workshop is Feb 8-13.

UC Berkeley Department of Statistics is hiring! We’re seeking applicants for up to three approved tenure-track positions at the Assistant Professor level in Statistics, Probability and AI. Details & apply: aprecruit.berkeley.edu/JPF05… #AI #Statistics #Probability #UCBerkeley

Our team at FAIR is hiring PhD research interns for 2026 on the topics of multimodal multi-agent learning. If you are interested, feel free to DM me or directly apply using the link below! metacareers.com/jobs/1821713…

If you're a PhD student interested in interning with me or one of my amazing colleagues at Microsoft Research New England (@MSRNE, @MSFTResearch) this summer, please apply here jobs.careers.microsoft.com/g… (If you'd like to work with me, please include my name in your cover letter!)

Follow us here linkedin.com/company/bernoul…