Image credit: Envato elements
Beamr, listed as BMR on the NASDAQ exchange, is at the forefront of leveraging machine learning for video enhancement. The burgeoning field of machine learning and artificial intelligence for video already constitutes a market valued at over $20 billion – a staggering figure that is only set to soar in the years to come.
One of the most significant hurdles impeding progress in this field is the management of vast video files and libraries. These files, due to their sheer size, pose a formidable challenge for training computer networks to identify moving objects.
Consider the task of recognizing a car or a human – a feat easily achieved by humans but formidable for computers, especially within a video. Each slight movement alters an object’s appearance, placing immense demands on computer networks to analyze numerous videos in order to excel in recognition.
The upshot of these intricate technical hurdles is a clear and burdensome bottom line for countless companies and startups operating in this domain: excessive expenses hindering their growth.
Tamar Shoham, the CTO of Beamr, outlined how Beamr’s technology offers a compelling solution to alleviate this cost burden: “The key lies in Beamr’s capability to thoroughly analyze each frame of a video file and determine the optimal compression level without compromising quality.”
In a recent experiment, Shoham led a demonstration illustrating how machine learning workflows benefit from Beamr’s ability to produce a compressed file that mirrors the original. These optimized files exhibited an average size reduction of 40%, streamlining machine learning processes and yielding significant cost savings. Notably, this experiment reaffirmed that people detection conducted on the smaller, optimized files produced virtually identical results.
Image credit: Envato elements
The tests were conducted using the NVIDIA DeepStream SDK, a revered tool for AI-based multi-sensor processing and video, audio, and image understanding. This partnership was a natural choice for Beamr, given its status as an NVIDIA Metropolis partner.
Shoham conveyed, “The video optimization process, focusing on reducing file sizes, did not compromise the detection performance achieved with the DeepStream SDK – a pivotal enabler for vision AI applications and services. We are grateful to the Nvidia DeepStream team for their support in our research.”
Over the past decade, Beamr’s innovative technology – lauded with an Emmy award for Technology and Engineering in 2021 and backed by 53 patents – has consistently aimed to optimize the trade-off between video quality and compression. This technology has found widespread use, whether for streaming films on platforms like Netflix, a long-standing Beamr customer, or fulfilling the exacting demands of professionals in various applications.
About Beamr
Beamr, under the ticker BMR, is a leading provider of content-adaptive video solutions. Garnering 53 granted patents and honored with the 2021 Technology and Engineering Emmy® award and the 2021 Seagate Lyve Innovator of the Year award, Beamr’s perceptual optimization technology allows for up to a 50% reduction in bitrate while ensuring quality.
For more details, visit www.beamr.com
This post was authored by an external contributor and does not represent Benzinga’s opinions and has not been edited for content. This contains sponsored content and is for informational purposes only and not intended to be investing advice.