Real-Time Processing at Scale
CERN Burns AI Into Silicon for LHC Data
Custom machine learning models process 40,000 exabytes of annual sensor data at nanosecond speeds.

A high-tech silicon microchip with light patterns representing AI processing, set against a blurred background of the Large Hadron Collider tunnel.
Photo: Avantgarde News
CERN scientists are deploying custom machine learning models directly into hardware to manage massive data streams [1]. The Large Hadron Collider (LHC) generates about 40,000 exabytes of unfiltered sensor data every year [1]. This new approach integrates AI into silicon to process information at nanosecond speeds [1]. The extremely fast models help reduce the volume of data by identifying significant events instantly [1]. By embedding AI into the hardware, researchers can filter out noise before it reaches storage [1]. This specialized silicon ensures the collider's vast output remains manageable for future scientific study [1].
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Avantgarde News Desk covers real-time processing at scale and editorial analysis for Avantgarde News.


