Data policies blocked collaboration. Federated AI detects signals 10x faster, syncing global observatories without exposing raw data.
A U.S. national laboratory leads multi-messenger astrophysics research, requiring the coordination of massive data streams between gravitational-wave detectors and radio telescopes globally.
Detecting and tracking cosmic events requires real-time analysis, but varying proprietary data policies prevented centralized processing and slowed...
“RADAR gives us a way to plan and adapt follow-up strategies, even when the data itself can’t be shared directly. This capability will become increasingly critical as next-generation detectors transform today’s trickle of multi-messenger detections into a flood.”
Multidisciplinary science and engineering research center for energy and security.
Collaborated to develop the RADAR framework for multi-messenger astrophysics discovery.
Drowning in 80,000 monthly alerts, analysts struggled to secure data. AI now prioritizes threats, cutting response time by 99%.
With just 300 speakers, manual translation couldn't keep pace. AI now drafts text for linguists to refine, doubling daily output.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.