Detectors upgraded to 100,000 images per second left annotators drowning. AI now delivers labeled 3D volumes live, at the beamline.
One of the US Department of Energy's premier research laboratories, home to the Advanced Light Source, a football field-sized X-ray facility whose upgraded detectors have gone from capturing one image every six seconds to 100,000 images per second.
Upgraded detectors now generate orders of magnitude more data than a decade ago, far outpacing what scientists can analyze manually. Each dataset...
“By seamlessly combining AI, advanced computing, and experimental systems, SYNAPS-I analyzes data as it's produced and guides experiments in real time, replacing slow manual steps with adaptive, automated decision-making. This compresses discovery time from days to moments and establishes a continuous, self-improving model of science that will be essential to realizing the full potential of the Genesis Mission.”
Department of Energy national laboratory conducting scientific research.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Lawrence Berkeley National Laboratory's Scientific image analysis is part of this use case:
Related implementations across industries and use cases
Data policies blocked collaboration. Federated AI detects signals 10x faster, syncing global observatories without exposing raw data.
LiDAR missed 30% of the canopy. Researchers now use computer vision to map individual trees at 1-meter resolution.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
LiDAR missed 30% of the canopy. Researchers now use computer vision to map individual trees at 1-meter resolution.
Previous AI lost intra-species variations at scale. Researchers curated 214M images to train a model that preserves fine physical traits.
High incident volumes across complex IT/OT networks overwhelmed security teams. Now, AI agents triage alerts so analysts can hunt threats.
Tendering documents took weeks to draft and varied in quality across ministries. Copilot now generates a compliant first draft in minutes.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Detectors upgraded to 100,000 images per second left annotators drowning. AI now delivers labeled 3D volumes live, at the beamline.
One of the US Department of Energy's premier research laboratories, home to the Advanced Light Source, a football field-sized X-ray facility whose upgraded detectors have gone from capturing one image every six seconds to 100,000 images per second.
Upgraded detectors now generate orders of magnitude more data than a decade ago, far outpacing what scientists can analyze manually. Each dataset...
“By seamlessly combining AI, advanced computing, and experimental systems, SYNAPS-I analyzes data as it's produced and guides experiments in real time, replacing slow manual steps with adaptive, automated decision-making. This compresses discovery time from days to moments and establishes a continuous, self-improving model of science that will be essential to realizing the full potential of the Genesis Mission.”
Department of Energy national laboratory conducting scientific research.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Lawrence Berkeley National Laboratory's Scientific image analysis is part of this use case:
Related implementations across industries and use cases
Data policies blocked collaboration. Federated AI detects signals 10x faster, syncing global observatories without exposing raw data.
LiDAR missed 30% of the canopy. Researchers now use computer vision to map individual trees at 1-meter resolution.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
LiDAR missed 30% of the canopy. Researchers now use computer vision to map individual trees at 1-meter resolution.
Previous AI lost intra-species variations at scale. Researchers curated 214M images to train a model that preserves fine physical traits.
High incident volumes across complex IT/OT networks overwhelmed security teams. Now, AI agents triage alerts so analysts can hunt threats.
Tendering documents took weeks to draft and varied in quality across ministries. Copilot now generates a compliant first draft in minutes.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.