Revolutionary video compression for autonomous vehicles: Beamr sets standards!

Revolutionary video compression for autonomous vehicles: Beamr sets standards!

In the exciting world of autonomous vehicles, data storage and processing are of central importance. The increase in video data leads to challenges that urgently require innovative solutions. Beamr Imaging Ltd. Most of progress in this area and recently tested its GPU-accelerated technology for the automotive industry for autonomous driving. As globenewewswire.com the company has successfully carried out several proof of concepts (POCs), in which the use of its content adaptive Bitrate technology (Cabr) showed valid results in machine learning technology (ML).

In a world where a single autonomous vehicle produces terabytes of video data every day, the potential of Beamr's technology is remarkable. It enables savings from 20% to 50% for video data used to train ML models without affecting the visual quality. In view of the fact that up to 150 terabytes of data per day in a fleet of 150 autonomous vehicles, it is clear that this could have an enormous impact on storage costs and infrastructure that is between USD 3 and 6.5 million annually.

The explosion of the video data

The data explosion in autonomous vehicles is a serious challenge - experts like Drago Anguelov from Waymo also know that. This is also linked to the high demands on data processing, because traditional methods often do not manage to efficiently process relevant information. Beamr has developed an efficient video compression system for this problem that gives the impression that it was tailored to human perception.

With the help of Cabr, it is ensured that important details for decision -making, such as the readability of street signs or the detection of objects, are also preserved for compressed data. Studies show that this type of compression can not only reduce the file sizes by up to 50%, but also receives the performance of ML models at the same time. This is particularly relevant when you consider that training for a model with 10,000 hours 1080p video data can require up to 600 terabytes of storage space. This is only possible with effective compression methods.

innovative approaches in processing

The technology behind the compression has developed further. While traditional coding methods aim to reproduce data as precisely as possible, modern approaches, as they are also described in the work of scisimple.com will, to identify and provide relevant information. Neuronal networks help to significantly optimize the coding process.

In addition, techniques such as joint coding of various data sources are used to further increase efficiency. Swift Processing is the magic word here, because the data must be processed in real time in order to be able to fully exploit all the possibilities of autonomous vehicle technologies.

BEAMR is currently preparing to further analyze the effects of your technologies on a variety of areas of application: Object and 3D object recognition as well as the performance of driving track detection also belong to the agenda. This progress is necessary to ensure a safe and efficient environment for drivers and passengers in autonomous cars.

Overall, it can be seen that the technologies behind video compression in autonomous vehicles are not only promising, but also crucial in order to cope with the challenges of the increasing amounts of data.

Whether flying cars or smart driving - the future shines promising, and Beamr is at the forefront with his innovative technology. It remains exciting to see how the compression methods develop and support the next generation of autonomous vehicles even more smarter!