Discover a collection of reference workflows that use vision language models to deliver rich, interactive visual perception capabilities for a wide range of industries.
Workloads
Computer Vision / Video Analytics
Industries
Retail/ Consumer Packaged Goods
Manufacturing
Smart Cities/Spaces
Healthcare and Life Sciences
Business Goal
Return on Investment
Innovation
Products
NVIDIA Metropolis
NVIDIA AI Enterprise
Traditional video analytics applications and their development workflows 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 and foundation models, you can now build applications with fewer models that have incredibly complex and broad perception and rich contextual understanding. This newer generation of vision language models (VLMs) is giving rise to smart, powerful video analytics AI agents.
A video analytics AI agent can combine both vision and language modalities to understand natural language prompts and perform visual question-answering. For example, answering a broad range of questions in natural language that can be applied against a recorded or live video stream. This deeper understanding of video content enables more accurate and meaningful interpretations, improving the functionality of video analytics applications and analysis of real-world scenarios. These agents promise to unlock entirely new industrial application possibilities.
Highly perceptive, accurate, and interactive video analytics AI agents will be deployed throughout our factories, warehouses, retail stores, airports, traffic intersections, and more. This will have a tremendous impact on operations teams looking to make better decisions using richer insights generated from natural interactions. Managers and operations teams will communicate with these agents in natural language, all powered by generative AI and VLMs with NVIDIA NIM™ microservices at their core.
Explore the technical implementation.
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Explore the reference workflow, powered by multiple visual language models, to easily build your video analytics AI agent.