Tamar Shoham
Introduction Machine learning for Video is an expanding field, garnering vast interest, with generative AI for video picking up speed. However there are significant pain points for these technologies such as storage and bandwidth bottlenecks when dealing with video content, as well as training and inferencing speeds. In the following case study, we show that […]
Tamar Shoham
By reducing video size but not perceptual quality, Beamr’s Content Adaptive Bit Rate optimized encoding can make video used for vision AI easier to handle thus reducing workflow complexity
