CERN Embeds AI Triggers In Detector Silicon
At the virtual Monster Scale Summit earlier this month, Thea Aarrestad of CERN and ETH Zurich explained that the Large Hadron Collider embeds anomaly-detection models directly into detector silicon to reduce about 40,000 EBs of unfiltered sensor data in real time. The custom FPGA/ASIC triggers make accept/reject decisions within 50 nanoseconds, saving roughly 0.02% (≈110,000 events/sec) for downstream analysis and global replication across 170 sites.
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Sources
- Read OriginalCERN eggheads burn AI into silicon to stem data delugetheregister.com
