Exploring the potential of quantum information science and technologies for high-energy physics.
SKAO director-general Philip Diamond describes how the world's largest radio telescope went from concept to construction.
Headed by two ATLAS physicists, gluoNNet applies data-mining and machine-learning techniques to benefit wider society.
A new CMS analysis searches for anomalies in top-quark interactions with the Z boson using an effective-field-theory framework.
Erik Verlinde sizes up the Standard Model, gravity and intelligence as candidates for future explanation as emergent phenomena.
Time-stamped files stated by Tim Berners-Lee to contain the original source code for the web and digitally signed by him, have sold for US$5.4 million at auction.
Jesse Thaler argues that particle physicists must go beyond deep learning and design AI capable of deep thinking.
Leaders in artificial-intelligence research spoke to the Courier about what's next for the field, and how developments may impact fundamental science.
Jennifer Ngadiuba and Maurizio Pierini describe how ‘unsupervised’ machine learning could keep watch for signs of new physics at the LHC that have not yet been dreamt up by physicists.
The LHC Olympics and Dark Machines data challenges stimulated innovation in the use of machine learning to search for new physics, write Benjamin Nachman and Melissa van Beekveld.