Vision language models (VLMs) have transformed video analytics by enabling broader perception and richer contextual understanding compared to traditional computer vision (CV) models. However, challenges like limited context length and lack of audio transcription still exist, restricting how much video a VLM can process at a time. To overcome this, the NVIDIA AI Blueprint for video search and…
]]>This post was originally published July 29, 2024 but has been extensively revised with NVIDIA AI Blueprint information. Traditional video analytics applications and their development workflow are typically built on fixed-function, limited models that are designed to detect and identify only a select set of predefined objects. With generative AI, NVIDIA NIM microservices…
]]>Whether it’s a warehouse looking to balance product distribution and optimize traffic, a factory assembly line inspection, or hospital management, making sure that employees and caregivers use personal protection equipment (PPE) while attending to patients, advanced intelligent video analytics (IVA) turn out to be useful. At the foundational layer, there are billions of cameras and IoT…
]]>Designing new custom hardware accelerators for deep learning is clearly popular, but achieving state-of-the-art performance and efficiency with a new design is a complex and challenging problem. Two years ago, NVIDIA opened the source for the hardware design of the NVIDIA Deep Learning Accelerator (NVDLA) to help advance the adoption of efficient AI inferencing in custom hardware designs.
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