Yes, the FPGAs! Atlas and other experiments at CERN require such complex and hard-read time requirements, making them great applications of FPGAs. Right now, I am working on a project to try and deploy graph neural networks for track reconstruction and filtering (on the faster L1 trigger), as well as reconstructing other quantifiable measurements using graph neural networks (I believe this is not on the L1 trigger but requires some element of real-time). What's cool is they have copies of the FPGA boards that are at CERN at Fermilab, which makes remote development easier. Also, a fun fact: the detectors that surround the core are not all perfect concentric circles and are a big mix of different geometries and types of detectors, making the problem more interesting.