Google has a lot of ML experts. Lot of fields can potentially benefit from ML and also contribute data and concept to ML but these fields don't have ML experts. I was thinking about this only a few days ago. I am so glad google is looking to personally contribute to every field possible.
Though property predicting is a hard problem,I think there are low hanging fruits in other fields. For example, Anthropology where only partial skeletons are found but we know there is symmetry there. Software regeneration is slow and expensive and doesn't exploit the symmetry a lot.
A joint project between google and CERN also sounds really cool to me. Or maybe google can set up a system where researchers with large data can approach google and see if a symbiotic relationship can be formed.
A personal anecdote to support your point: The first company I worked for in Europe was a well-established ML company that had been doing predictive analytics long (10+ years) before the current fad.
Founded by a former professor from CERN, and staffed about 90% from CERN postdocs. I was the only member of my team who was not a co-author on the Higgs boson discovery paper.
So yeah, people at CERN are pretty well aware of what can be done with ML.
I never said CERN doesn't use ML. But I would imagine google has more ML experts and computational capacity then CERN. Correct me if i'm wrong. There is nothing wrong with collaboration.
Though property predicting is a hard problem,I think there are low hanging fruits in other fields. For example, Anthropology where only partial skeletons are found but we know there is symmetry there. Software regeneration is slow and expensive and doesn't exploit the symmetry a lot.
A joint project between google and CERN also sounds really cool to me. Or maybe google can set up a system where researchers with large data can approach google and see if a symbiotic relationship can be formed.