Businesses and public sector organizations around the world are developing AI agents to empower employees who rely on visual information from an increasing number of devices, including cameras, IoT sensors, and vehicles.
To support that work, the new NVIDIA AI Blueprint for Video Search and Summarization enables developers in virtually any industry to build visual AI agents that analyze video and image content. These agents can answer user questions, generate summaries, and enable alerts for specific scenarios.
This blueprint is part of NVIDIA Metropolis, a set of developer tools for building vision AI applications, a customizable workflow that combines NVIDIA computer vision and generative AI technologies.
Global systems integrators and technology solution providers, including Accenture, Dell Technologies, and Lenovo, are bringing NVIDIA AI blueprints for visual search and summarization to businesses and cities around the world to improve productivity and safety. We are accelerating the next wave of AI applications that can be deployed in Factories, warehouses, stores, airports, intersections, etc.
Announced ahead of Smart City Expo World Congress, NVIDIA AI Blueprint gives visual computing developers the tools to build and deploy generative AI-powered agents that can ingest and understand massive live video streams and data archives. , provides a complete suite of optimized software.
Users can customize these visual AI agents using natural language prompts rather than rigid software code, lowering the barrier to deploying virtual assistants across industries and smart city applications.
NVIDIA AI Blueprints leverage vision language models
Visual AI agents leverage vision language models (VLMs), a class of generative AI models that combine computer vision and language understanding to interpret the physical world and perform inference tasks.
NVIDIA AI Blueprint for Video Search and Summarization includes VLMs such as NVIDIA VILA, LLMs such as Meta’s Llama 3.1 405B, and NVIDIA AI Blueprints for AI Models for GPU-accelerated question answering and context-aware search extension generation. Can be configured using NIM microservices. Developers can easily swap in and fine-tune other VLM, LLM, and graph databases using the NVIDIA NeMo platform for their unique environments and use cases.
Adopting NVIDIA AI Blueprints can potentially save developers months of effort exploring and optimizing generative AI models for smart city applications. When deployed on NVIDIA GPUs at the edge, on-premises, or in the cloud, it significantly speeds up the process of combing through video archives to identify key moments.
In a warehouse environment, an AI agent built with this workflow can alert workers if safety protocols are violated. At busy intersections, AI agents can identify traffic incidents and generate reports to support emergency response efforts. And in the public infrastructure space, maintenance workers can ask AI agents to review aerial footage and identify deteriorating roads, tracks, and bridges to support proactive maintenance.
Beyond smart spaces, use visual AI agents to summarize videos for visually impaired people, automatically generate summaries of sporting events, and train other AI models at scale. It can also be used to help label visual datasets.
Video search and summarization workflows now a collection of NVIDIA AI blueprints that make it easy to create AI-powered digital avatars, build virtual assistants for personalized customer service, and extract enterprise insights from PDF data. I have joined.
NVIDIA AI Blueprints are free to experience and download for developers and are powered by NVIDIA AI Enterprise, an end-to-end software platform that accelerates data science pipelines and streamlines the development and deployment of generative AI. can be deployed in production across designated data centers and clouds.
AI agents deliver insights from warehouses to world capitals
Enterprise and public sector customers can also take advantage of the complete collection of NVIDIA AI Blueprints with the help of NVIDIA’s partner ecosystem.
Accenture, a global professional services company, has integrated NVIDIA AI Blueprint into Accenture AI Refinery. It is built on NVIDIA AI Foundry and enables customers to develop custom AI models trained on enterprise data.
Global system integrators in Southeast Asia, including Malaysia’s ITMAX and Vietnam’s FPT, are building AI agents based on the Video Search and Summarization NVIDIA AI Blueprint for smart city and intelligent transportation applications.
Developers can also build and deploy NVIDIA AI blueprints on the NVIDIA AI Platform using compute, networking, and software from the world’s leading server manufacturer.
Dell uses VLM and an agent approach on Dell’s NativeEdge platform to enhance existing edge AI applications and create new edge AI-enabled capabilities. Dell reference designs for Dell AI Factory powered by NVIDIA and NVIDIA AI Blueprints for Video Search and Summarization support VLM capabilities with purpose-built AI workflows for multimodal enterprise use cases in the data center, edge, and on-premises.
NVIDIA AI Blueprints are also included in Lenovo Hybrid AI Solutions powered by NVIDIA.
Companies like K2K, a smart city application provider in the NVIDIA Metropolis ecosystem, use the new NVIDIA AI Blueprint to build AI agents that analyze live traffic cameras in real time. This will allow city staff to ask questions about street activity and receive advice on how to improve operations. The company is also working with traffic managers in the city of Palermo, Italy, to deploy visual AI agents using NIM microservices and NVIDIA AI Blueprints.
To learn more about the NVIDIA AI Blueprint for Video Search and Summarization, visit the NVIDIA booth at Smart City Expo World Congress in Barcelona until November 7th.
Learn how to build visual AI agents.
