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.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Argonne National Laboratory's Astronomical signal detection is part of this use case:
Related implementations across industries and use cases
Legacy tools stalled on sensor data. A secure AI supercomputer now lets researchers model maritime weather with 1-km precision.
Simulations were stuck in 2D and took hours. Physics-informed AI now models 3D urban airflow in seconds.
Traditional modeling bottlenecked stress tests with limited data. Now, generative AI rapidly scales massive threat scenarios agency-wide.
Traditional modeling bottlenecked stress tests with limited data. Now, generative AI rapidly scales massive threat scenarios agency-wide.
Physics simulations took weeks to screen libraries. Boltz-2 runs 1,000x faster, cutting this to hours with 2x precision.
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
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.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Argonne National Laboratory's Astronomical signal detection is part of this use case:
Related implementations across industries and use cases
Legacy tools stalled on sensor data. A secure AI supercomputer now lets researchers model maritime weather with 1-km precision.
Simulations were stuck in 2D and took hours. Physics-informed AI now models 3D urban airflow in seconds.
Traditional modeling bottlenecked stress tests with limited data. Now, generative AI rapidly scales massive threat scenarios agency-wide.
Traditional modeling bottlenecked stress tests with limited data. Now, generative AI rapidly scales massive threat scenarios agency-wide.
Physics simulations took weeks to screen libraries. Boltz-2 runs 1,000x faster, cutting this to hours with 2x precision.
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.