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Beamr presents accelerated video AI workflows at NVIDIA GTC

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Beamr Imaging (NASDAQ: BMR) will showcase accelerated video AI workflows at NVIDIA GTC, aiming to integrate AI workflows into its Beamr Cloud SaaS solution. The company plans to offer solutions to overcome challenges in training massive video AI models, focusing on enhancing video pre-training, training, and inference capabilities. Beamr's recent technical paper demonstrated a 40% downsizing of video files without affecting training and inference results, leading to significant cost savings. Beamr Cloud, powered by NVIDIA technology, targets markets like AI, user-generated content, and autonomous cars.
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Herzliya Israel, March 19, 2024 (GLOBE NEWSWIRE) -- Beamr Imaging Ltd. (NASDAQ: BMR), a leader in video optimization technology and solutions, today announced it will present accelerated video AI workflows at NVIDIA GTC. GTC is a global AI conference for developers and business minds shaping the future of artificial intelligence (AI) and accelerated computing. At GTC, Beamr will highlight its plans for integrating AI workflows into Beamr Cloud - Beamr’s recently launched video software-as-a-service (SaaS) solution powered by NVIDIA technology - allowing easy and wide access to advanced video processing.

AI startups or even seasoned AI firms face challenges training massive video AI models. This is because of the complexity of the size and resolution of large video files. Beamr’s vision is to lower the barrier of entry to the highest level of video AI capabilities. Beamr plans to offer AI and machine learning players a variety of solutions that may enable them to overcome critical pain points, such as slow training and inferencing speed, large numbers of GPUs required to complete a task, data storage, networking  bottlenecks and high associated costs.

Beamr plans to focus its research and development efforts on providing AI and generative AI players access to video AI workflows, tailored to their needs, through Beamr Cloud. Recently, Beamr released a technical paper showing that machine learning workflows benefit from the ability to create a compressed file that looks exactly the same as the original one. Video files that were downsized by 40% on average had streamlined machine learning processes and allowed significant savings in storage and overall costs without any negative effect on training and inference results.

Beamr’s video optimization tech - integrated with NVIDIA’s 8th-generation GPU encoder (NVENC), available on NVIDIA T4 Tensor Core and NVIDIA RTX GPUs, and NVIDIA L4 Tensor CoreL40 and L40S GPUs - aims to accelerate video AI workflows and enhance video pre-training, training and inference capabilities in AI pipelines. NVENC SDK 12.1 added an API that allows external control and enables users to tightly integrate hardware encoders for AVC and HEVC video formats. In addition, it supports AOMedia Video 1 (AV1), an efficient emerging video format.

Last month, Beamr launched Beamr Cloud, enabling high-quality, high-scale video processing at attractive pricing. Beamr Cloud, operating on Amazon’s AWS and powered by NVIDIA technology, targets the expanding markets of AI, user-generated content, autonomous cars, online video editing, podcast platforms and more. Beamr Cloud is powered by NVIDIA technologies like NVIDIA CUDA, NVIDIA DeepStream SDK, and NVENC, and supports reductions in video training, inferencing, and extract, transform and load (ETL) times, while delivering cost savings in bandwidth and storage.

Image:  Beamr Cloud - High-Quality, High-Scale Video Processing at Attractive Pricing

Faster Extract, Transform and Load (ETL) with Beamr Optimized Video

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 50% reduction in bitrate with guaranteed quality. www.beamr.com

Forward-Looking Statements

This press release contains “forward-looking statements” that are subject to substantial risks and uncertainties. Forward-looking statements in this communication may include, among other things, statements about Beamr’s strategic and business plans, technology, relationships, objectives and expectations for its business, the impact of trends on and interest in its business, intellectual property or product and its future results, operations and financial performance and condition. All statements, other than statements of historical fact, contained in this press release are forward-looking statements. Forward-looking statements contained in this press release may be identified by the use of words such as “anticipate,” “believe,” “contemplate,” “could,” “estimate,” “expect,” “intend,” “seek,” “may,” “might,” “plan,” “potential,” “predict,” “project,” “target,” “aim,” “should,” “will” “would,” or the negative of these words or other similar expressions, although not all forward-looking statements contain these words. Forward-looking statements are based on the Company’s current expectations and are subject to inherent uncertainties, risks and assumptions that are difficult to predict. Further, certain forward-looking statements are based on assumptions as to future events that may not prove to be accurate. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s annual report filed with the U.S. Securities and Exchange Commission (the “SEC”) on March 4, 2024 and in subsequent filings with the SEC. Forward-looking statements contained in this announcement are made as of the date hereof and the Company undertakes no duty to update such information except as required under applicable law.

Investor Contact:

investorrelations@beamr.com

 


FAQ

What will Beamr Imaging (BMR) present at NVIDIA GTC?

Beamr will showcase accelerated video AI workflows at NVIDIA GTC.

What challenges do AI startups face in training massive video AI models?

AI startups face challenges due to the complexity of large video file sizes and resolutions.

How does Beamr plan to lower the barrier of entry to video AI capabilities?

Beamr plans to offer solutions to overcome critical pain points like slow training and inferencing speed, large GPU requirements, data storage, networking bottlenecks, and high costs.

What benefits did Beamr's downsizing of video files by 40% demonstrate?

The downsizing led to streamlined machine learning processes, significant savings in storage and costs without affecting training and inference results.

Which markets does Beamr Cloud, powered by NVIDIA technology, target?

Beamr Cloud targets markets like AI, user-generated content, autonomous cars, online video editing, podcast platforms, and more.

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