CERN operates some of the most complex scientific machinery ever built, relying on intricate control systems and generating petabyte upon petabyte of research data. Operating this equipment and performing analysis on the data gathered are both intensive tasks. Therefore, CERN is increasingly looking to the broad domain of artificial-intelligence (AI) research to address some of the challenges encountered in dealing with data, particle beam handling, and in the up keep of its facilities.
The modern domain of artificial intelligence came into existence around the same time that CERN did, in the mid-’50s. It has different meanings in different contexts, and CERN is mainly interested in task-oriented, so-called restricted AI, rather than general AI involving aspects such as independent problem-solving, or even artificial consciousness. Particle physicists were among the first groups to use AI techniques in their work, adopting Machine Learning (ML) as far back as 1990. Beyond ML, physicists at CERN are also interested in the use of Deep Learning to analyse the data deluge from the LHC.
Dealing with a data deluge
Even before the Large Hadron Collider began colliding high-energy beams of protons in 2010, the particle-physics community began to collect unprecedented quantities of data. Particles collide within the LHC’s detectors up to 40 million times a second, each collision event generating about a megabyte of data: far too much to store without some filtering.
Experimental facilities at CERN may be temporarily classified as high-radiation zones, preventing human intervention to perform repairs or to replace equipment. CERN has therefore developed autonomous robots to operate in these zones, which include the tunnel containing the LHC. The Engineering department at CERN, which builds and maintains these robots, uses AI techniques to help the robots navigate on their own and make decisions on what actions to take inside the radiation environments.
Machine Learning is also used in the CERN accelerator complex to predict and avoid equipment failures, as well as to optimize the quality of the high-energy beams of protons that CERN delivers to its experiments. Furthermore, physicists are also investigating how similar techniques could make the work of those who run accelerators more efficient, more reliable, and possibly even autonomous.
Bringing state-of-the-art techniques to CERN
In addition to using AI robotics for the maintenance of its complex machines, predicting component failure and for safety applications, CERN has recognised the importance of involving external AI expertise in projects undertaken at the laboratory.
In addition, CERN is also interested in employing its AI knowhow to create positive impact in society as a whole. The CERN Knowledge Transfer Group works with players in the automotive, finance and pharmaceutical sectors towards this effort.