Sounds interesting. Do you have any links to information about how they use machine learning?

Just the slides in the two big announcement presentations. I don't have links but I imagine they're up on a CERN webpage somewhere.

ML is used pervasively. At the top level they use monte-carlo to simulate the device as well as to train ML classifiers (boosted decision trees of some flavor) that select what data from the detectors can be safely ignored.

My Ph.D thesis was titled "Distributed Machine Learning" and focused on boosted decision trees - this was 1997. Ok, I am small beer and I will get lost in any discussion with the smart folk at Cern in about 2 seconds flat, but I feel it necessary to say whenever I can that I was astonished when I read that the LHC was using a learned model over boosted decision trees as a noise filter. A large number of trees induced in data will find co-incidental outcomes; think about running trials - run 10 and the likelihood of a false positive is low, run 1000 and it's very high! Boost a decision tree and you will bring all sorts of things out of the margins; some of them will even be real. Is the bump in the higgs signal real? There were 15 events that generated that bump, out of n billion. What are the odds of a boosted tree regularizing the noise into that bin - I would say pretty decent.

But I am an old man, who knows little and does less. I shall return to my beer and vegetables.