NVIDIA AI Blueprints
Businesses and government agencies worldwide are creating AI agents to improve the skills of workers who depend on visual data from an increasing number of devices, such as cameras, Internet of Things sensors, and automobiles.
Developers in almost any industry will be able to create visual AI agents that analyze image and video information with the help of a new NVIDIA AI Blueprints for video search and summarization. These agents are able to provide summaries, respond to customer inquiries, and activate alerts for particular situations.
The blueprint is a configurable workflow that integrates NVIDIA computer vision and generative AI technologies and is a component of NVIDIA Metropolis, a suite of developer tools for creating vision AI applications.
The NVIDIA AI Blueprints for visual search and summarization is being brought to businesses and cities around the world by global systems integrators and technology solutions providers like Accenture, Dell Technologies, and Lenovo. This is launching the next wave of AI applications that can be used to increase productivity and safety in factories, warehouses, shops, airports, traffic intersections, and more.
The NVIDIA AI Blueprint, which was unveiled prior to the Smart City Expo World Congress, provides visual computing developers with a comprehensive set of optimized tools for creating and implementing generative AI-powered agents that are capable of consuming and comprehending enormous amounts of data archives or live video feeds.
Deploying virtual assistants across sectors and smart city applications is made easier by the fact that users can modify these visual AI agents using natural language prompts rather than strict software code.
NVIDIA AI Blueprint Harnesses Vision Language Models
Vision language models (VLMs), a subclass of generative AI models, enable visual AI agents to perceive the physical world and carry out reasoning tasks by fusing language comprehension and computer vision.
NVIDIA NIM microservices for VLMs like NVIDIA VILA, LLMs like Meta’s Llama 3.1 405B, and AI models for GPU-accelerated question answering and context-aware retrieval-augmented generation may all be used to configure the NVIDIA AI Blueprint for video search and summarization. The NVIDIA NeMo platform makes it simple for developers to modify other VLMs, LLMs, and graph databases to suit their particular use cases and settings.
By using the NVIDIA AI Blueprints, developers may be able to avoid spending months researching and refining generative AI models for use in smart city applications. It can significantly speed up the process of searching through video archives to find important moments when installed on NVIDIA GPUs at the edge, on-site, or in the cloud.
An AI agent developed using this methodology could notify employees in a warehouse setting if safety procedures are broken. An AI bot could detect traffic accidents at busy crossroads and provide reports to support emergency response activities. Additionally, to promote preventative maintenance in the realm of public infrastructure, maintenance personnel could request AI agents to analyze overhead imagery and spot deteriorating roads, train tracks, or bridges.
In addition to smart places, visual AI agents could be used to automatically create video summaries for visually impaired individuals, classify large visual datasets for training other AI models, and summarize videos for those with visual impairments.
The workflow for video search and summarization is part of a set of NVIDIA AI blueprints that facilitate the creation of digital avatars driven by AI, the development of virtual assistants for individualized customer support, and the extraction of enterprise insights from PDF data.
With NVIDIA AI Enterprise, an end-to-end software platform that speeds up data science pipelines and simplifies the development and deployment of generative AI, developers can test and download NVIDIA AI Blueprints for free. These blueprints can then be implemented in production across accelerated data centers and clouds.
AI Agents to Deliver Insights From Warehouses to World Capitals
With the assistance of NVIDIA’s partner ecosystem, enterprise and public sector clients can also utilize the entire library of NVIDIA AI Blueprints.
With its Accenture AI Refinery, which is based on NVIDIA AI Foundry and allows clients to create custom AI models trained on enterprise data, the multinational professional services firm Accenture has integrated NVIDIA AI Blueprints.
For smart city and intelligent transportation applications, global systems integrators in Southeast Asia, such as ITMAX in Malaysia and FPT in Vietnam, are developing AI agents based on the NVIDIA AI Blueprint for video search and summarization.
Using computing, networking, and software from international server manufacturers, developers can also create and implement NVIDIA AI Blueprints on NVIDIA AI systems.
In order to improve current edge AI applications and develop new edge AI-enabled capabilities, Dell will combine VLM and agent techniques with its NativeEdge platform. VLM capabilities in specialized AI workflows for data center, edge, and on-premises multimodal corporate use cases will be supported by the NVIDIA AI Blueprint for video search and summarization and the Dell Reference Designs for the Dell AI Factory with NVIDIA.
Lenovo Hybrid AI solutions powered by NVIDIA also utilize NVIDIA AI blueprints.
The new NVIDIA AI Blueprint will be used by businesses such as K2K, a smart city application supplier in the NVIDIA Metropolis ecosystem, to create AI agents that can evaluate real-time traffic camera data. City officials will be able to inquire about street activities and get suggestions on how to make things better with to this. Additionally, the company is utilizing NIM microservices and NVIDIA AI blueprints to deploy visual AI agents in collaboration with city traffic management in Palermo, Italy.
NVIDIA booth at the Smart Cities Expo World Congress, which is being held in Barcelona until November 7, to learn more about the NVIDIA AI Blueprints for video search and summarization.
