CERN, 초소형 AI 모델을 FPGA에 내장해 실시간 LHC 데이터 필터링 수행

CERN's deployment of tiny AI models on FPGAs for nanosecond-level real-time LHC data filtering represents a fundamental shift from large-scale model scaling toward extreme hardware specialization and optimization. This approach demonstrates that conventional AI accelerators cannot achieve the sub-100-nanosecond latency required for detector-level decisions, forcing a rethinking of AI architecture itself. The methodology signals a new frontier for ultra-low-latency inference in autonomous systems, medical imaging, and high-frequency trading—industries where microsecond latency changes become business-critical.