How Beamr Technology Can Boost Machine Learning
- Beamr's technology has the potential to significantly reduce the size of video files without compromising quality, leading to cost savings for companies and startups in the Machine Learning field.
- The recent experiment led by Beamr's CTO showed an average file size reduction of 40% with essentially the same results obtained in people detection on the optimized files.
- The company's technology has been tested on NVIDIA DeepStream SDK, showing no negative impact on the detection results.
- Beamr has a history of innovative technology, backed by 53 patents and a winner of the Emmy award for Technology and Engineering in 2021.
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The revelation by Beamr regarding its advancements in Machine Learning (ML) for video compression is poised to have a significant impact on the computer vision market. This technology sector, already valued at over $20 billion, is experiencing rapid growth due to the increasing reliance on artificial intelligence and ML in various industries. Beamr's innovation addresses a critical challenge in ML: the management of large video files, which are essential for training algorithms in object recognition tasks.
As a Market Research Analyst, it is clear that Beamr's technology could reduce operational costs for companies specializing in computer vision and ML. This cost-saving measure is likely to enhance the scalability of ML applications, potentially leading to broader adoption and innovation. Furthermore, the partnership with NVIDIA and the use of the DeepStream SDK highlights Beamr's strategic positioning within the ecosystem, potentially attracting interest from investors and stakeholders looking for companies at the forefront of AI and ML advancements.
From a financial perspective, Beamr's technology, which reportedly achieves a 40% reduction in video file sizes without compromising quality, could lead to substantial cost savings in storage and data transfer for its clients. This is particularly relevant for high-growth sectors like streaming services, where data management is a significant portion of operational expenses. By potentially reducing these costs, Beamr could enhance its competitive advantage and market share.
Investors may view Beamr's progress as a catalyst for future revenue growth, especially considering its existing clientele, which includes industry giants like Netflix. The ability to maintain video quality while compressing file sizes is a unique value proposition that could lead to new contracts and partnerships, further boosting Beamr's financial performance and attractiveness to shareholders.
Beamr's portfolio of 53 patents is a critical asset that underpins its competitive edge in the video compression space. The company's intellectual property (IP) rights serve as a moat against competitors, ensuring that its technological advancements remain proprietary. For businesses and investors, such a strong IP position is reassuring, as it suggests a long-term potential for market exclusivity and the ability to defend against infringement.
Moreover, the acknowledgment of Beamr's technology through an Emmy award for Technology and Engineering signifies industry recognition of its innovation, which could bolster its reputation and strengthen its negotiating power in licensing discussions or technology partnerships. The legal protection of its technology, combined with industry accolades, positions Beamr favorably in the fast-evolving landscape of video ML and AI.
HERZLIYA, ISRAEL / ACCESSWIRE / January 16, 2024 / Beamr (NASDAQ:BMR) is advancing on a new front and reveals its capability to boost Machine Learning for video. Machine Learning and Artificial Intelligence for video have demonstrated immense achievements and have even more tremendous potential. This hot field is expanding fast as part of the computer vision market that is already estimated at more than
But one of the biggest pain points that slows down progress is managing extremely large files and libraries. That is because video files are relatively large, and for training computer networks to recognize moving objects, you need lots and lots of them.
Think of how you recognize a car or a human. For us, it is an easy task, but not for a computer, either in a single image and certainly in a video. Each movement changes how the object looks, its shape, size and angle. That's why computer networks must scan and analyze countless videos to learn how to recognize if there is a human, a car, a cat or anything else in them. Players in Machine Learning deal with, not to say are stuck with, large clusters of video files that are extremely difficult to manage, store and transfer.
All these technical details sum up to a very clear bottom line for the many companies and start-ups in this field: heavy expenses that hinder their growth.
Tamar Shoham, Beamr CTO, explained how Beamr technology can help such enterprises cut their cost: "Overcoming one of the most difficult and expensive challenges of Machine Learning rests on Beamr technology's proven and tested ability to perform a remarkable thing, scanning each and every frame of a video file and concluding how much it can be compressed without losing its quality".
Shoham recently led an experiment that showed that Machine Learning workflows benefit from Beamr's proven ability to create a compressed file that looks exactly the same as the original one. These files were downsized on average by
The tests were conducted on NVIDIA DeepStream SDK - a tool for AI-based multi-sensor processing, video, audio and image understanding, which was a natural choice for Beamr as an NVIDIA Metropolis partner.
Shoham said: "We showed that the video optimization process, which cuts down the file size, didn't affect the detection results obtained with the DeepStream SDK, an enabler for vision AI applications and services. We are thankful to the Nvidia DeepStream team for supporting our research".
In the last decade, Beamr's inventive technology, a winner of the Emmy award for Technology and Engineering in 2021 and backed by 53 patents, aims to provide the best possible tradeoffs between quality and compression of video files, whether it is used for streaming films on Netflix, which is a long-time customer of Beamr, or examined by professionals who scan every pixel and in a wide range of use-cases.
About Beamr
Beamr (NASDAQ:BMR) is a world leader in content-adaptive video solutions. Backed by 53 granted patents, and winner of the 2021 Technology and Engineering Emmy® award and the 2021 Seagate Lyve Innovator of the Year award, Beamr's perceptual optimization technology enables up to a
For more details, visit www.beamr.com
Contact:
Sharon Carmel
investorrelations@beamr.com
SOURCE: Beamr Imaging Ltd
View the original press release on accesswire.com
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