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The technology reduces video file sizes by up to 50% using NVIDIA accelerated computing, aiding storage and cost efficiency

As reported in a press release on June 11, Beamr Imaging is set to launch a new high-performance video compression solution specifically designed for autonomous vehicles at the NVIDIA GTC Paris, part of the Viva Technology 2025 event. This development addresses the substantial video data needs of autonomous vehicles, which generate vast amounts of data. Beamr's technology, known for high-efficiency video compression, offers a solution for managing large volumes of video data used in training autonomous vehicle models, which demand significant storage and infrastructure.

The company's Content-Adaptive Bitrate (CABR) technology, leveraging NVIDIA accelerated computing, can reduce video file sizes by up to 50% while maintaining the visual quality necessary for model training. This reduction aids in alleviating storage, compute and bandwidth challenges within AI pipelines, thereby cutting down operational costs. The process begins with advanced driver assistance systems capturing real-world driving footage, which is stored in datacenters. However, real-world data alone is insufficient for comprehensive model training, prompting the generation of synthetic video through platforms such as NVIDIA Omniverse and NVIDIA Cosmos.

Recent benchmark tests on raw driving footage using real-time object detection models highlighted CABR's capabilities of achieving top-tier compression rates without compromising detection accuracy. This technology notably preserves visual details and ensures machine learning performance is unaffected while providing significant savings in storage space.

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