Using AI, machine learning and automation, the Efficient Particle Accelerator (EPA) project aims to boost the efficiency of CERN's accelerators for the high luminosity era and beyond

The ATLAS and CMS collaborations are using state-of-the-art machine learning techniques to search for exotic-looking collisions that could indicate new physics

The latest advancements in quantum techniques in machine learning have been presented at CERN, showcasing applications in particle physics and beyond

This report shows how CERN’s technology and expertise, paired with our partners, can drive innovation and progress for the benefit of society

CERN and software company Zenseact wrap up a joint research project that could allow autonomous-driving cars to make faster decisions, thus helping avoid accidents

Physicists at the ATLAS experiment are on the hunt for new, long-lived particles to help explain several outstanding mysteries of our Universe

The upcoming first edition of Sparks!, which will be held 17-18 September, adopts the theme of future intelligence

A new technique speeds up deep neural networks for selecting proton–proton collisions at the Large Hadron Collider for further analysis

Can machine learning assist high-energy physics in discovering and characterising new particles?

Untangle a rare particle decay from the background in LHCb data and you could win up to $7000

Competition open to find new machine-learning techniques for analysis of Higgs data produced by the ATLAS experiment