In an exchange with @lemouth yesterday in one of my posts, he expressed that he's looking forward to using machine learning for developing new techniques for looking for new phenomena at particle colliders like the Large Hadron Collider.
On a personal capacity - while I do have a background in machine learning and artificial intelligence, it was based on a raw, non-modular implementation using Matlab back in 2007 - I have been out of the loop for quite some time now. Plus, I had nothing to do with deep-learning AIs. But just like anything to do with initially esoteric technologies, it's anyone's guess that it would eventually be democratized at one point where any casual researcher can do it easily as well.
So after doing some searches yesterday, I landed on this article by Steven Levy of Backchannel in Medium.com (my favourite channel ever since being able to bypass the Medium restriction in my country!): https://backchannel.com/you-too-can-become-a-machine-learning-rock-star-no-phd-necessary-107a1624d96b#.qldvmez3m
It's called BONSAI, and it's supposed to be an easy-to-use product for anyone wanting to implement ML / AI into their projects. Not sure if it'd be a good fit for LHC experiments though, as I'm still barely scratching the surface of these new ML / AI platforms!
Anyway, check it out here and sign-up for the beta: https://bons.ai/
Do you know of any other applications? Please recommend it down in the comments :)