Vision language models (VLMs) are evolving at a breakneck speed. In 2020, the first VLMs revolutionized the generative AI landscape by bringing visual understanding to large language models (LLMs) through the use of a vision encoder. These initial VLMs were limited in their abilities, only able to understand text and single image inputs. Fast-forward a few years and VLMs are now capable of…
]]>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…
]]>The exponential growth of visual data—ranging from images to PDFs to streaming videos—has made manual review and analysis virtually impossible. Organizations are struggling to transform this data into actionable insights at scale, leading to missed opportunities and increased risks. To solve this challenge, vision-language models (VLMs) are emerging as powerful tools…
]]>An exciting breakthrough in AI technology—Vision Language Models (VLMs)—offers a more dynamic and flexible method for video analysis. VLMs enable users to interact with image and video input using natural language, making the technology more accessible and adaptable. These models can run on the NVIDIA Jetson Orin edge AI platform or discrete GPUs through NIMs. This blog post explores how to build…
]]>NVIDIA Metropolis Microservices for Jetson has been renamed to Jetson Platform Services, and is now part of NVIDIA JetPack SDK 6.0. NVIDIA Metropolis Microservices for Jetson provides a suite of easy-to-deploy services that enable you to quickly build production-quality vision AI applications while using the latest AI approaches. This post explains how to develop and deploy generative AI…
]]>Efficiency is paramount in industrial manufacturing, where even minor gains can have significant financial implications. According to the American Society of Quality, “Many organizations will have true quality-related costs as high as 15-20% of sales revenue, some going as high as 40% of total operations.” These staggering statistics reveal a stark reality: defects in industrial applications not…
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