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.

By Avantgarde News Desk··1 min read
A high-tech silicon microchip with light patterns representing AI processing, set against a blurred background of the Large Hadron Collider tunnel.

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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Drafted with LLM; human-edited

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The risk level is set to high because the story relies on a single source domain (The Register), failing the requirement for three independent domains.

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About the author

Avantgarde News Desk covers real-time processing at scale and editorial analysis for Avantgarde News.