But AI is already reaching far beyond even these realms. In fact, AI is now helping particle physicists to discover new subatomic particles. Particle physicists began integrating AI in the pursuit of particles as early as the 1980s, as the process of machine learning suits the hunt for fine patterns and subatomic anomalies particularly well. But, once an unexplored and novel technique, AI is now a fully integrated and standard part of everyday life within particle physics. Pushpalatha Bhat, physicist at Fermilab, described the problem in an interview with Science Magazine.
Particle physicists are not happy with Alessandro Strumia. Last week, the particle physicist gave a talk at CERN claiming that men are innately better at physics research than women. Now, the high-energy physics community is pushing back. The presentation, in which Strumia claimed that the reason there are more male physicists than female is because the men are "over-performing", and that physics was "invented and built by men", faced widespread and immediate backlash.
We are organizing a data science competition to stimulate both the ML and HEP communities to renew the toolkit of physicists in preparation for the advent of the next generation of particle detectors in the Large Hadron Collider at CERN. With event rates already reaching hundred of millions of collisions per second, physicists must sift through ten of petabytes of data per year. Ever better software is needed for processing and filtering the most promising events. This will allow the LHC to fulfill its rich physics programme, understanding the private life of the Higgs boson, searching for the elusive dark matter, or elucidating the dominance of matter over anti-matter in the observable Universe.