Nvidia recently announced the launch of its latest AI blueprint, aimed at helping developers across various industries to easily build intelligent agents that analyze video and image content. With this technology, users in any industry can efficiently search and summarize large volumes of visual data.
Global renowned companies like Accenture, Dell, and Lenovo have already started leveraging Nvidia's AI blueprint to develop visual AI agents, aiming to enhance productivity, optimize processes, and create safer environments. Various enterprises and public sector organizations are working on developing intelligent agents to strengthen the capabilities of jobs reliant on visual information, sourced from an increasing number of devices such as cameras, IoT sensors, and vehicles.
Nvidia's AI blueprint offers a comprehensive set of optimized software for video search and summarization. Developers can use it to build and deploy generative AI agents capable of understanding large volumes of real-time video streams or data archives. These agents can not only answer user queries but also generate summaries and issue alerts for specific scenarios.
As part of Nvidia Metropolis, the Nvidia AI blueprint provides a customizable workflow that combines Nvidia's computer vision and generative AI technologies. Developers can customize these visual AI agents through natural language prompts instead of complex code, thereby lowering the barriers to deploying virtual assistants in various industries and smart city applications.
The visual AI agents in Nvidia's AI blueprint are powered by Visual Language Models (VLMs), a type of generative AI model that combines computer vision and language understanding to interpret the physical world and perform reasoning tasks. Developers can flexibly configure and fine-tune Nvidia NIM microservices with other VLMs, LLMs, and graph databases to suit specific environments and use cases.
Adopting Nvidia's AI blueprint can help developers save months of work, avoiding the cumbersome process of researching and optimizing generative AI models for smart city applications. Whether on edge computing, on-premises, or in the cloud, solutions deployed on Nvidia GPUs can significantly speed up the screening of video archives and the identification of critical moments.
In warehouse environments, AI agents built on this workflow can issue alerts when safety protocols are violated; at busy intersections, AI agents can identify traffic accidents and generate reports to assist emergency responses. Additionally, visual AI agents can be used to summarize video content for visually impaired individuals, automatically generate sports event recaps, and help annotate large visual datasets to train other AI models.
The launch of Nvidia's AI blueprint provides developers with a free platform for experience and download, and can be deployed in production through Nvidia AI Enterprise in accelerated data centers and cloud environments, thereby simplifying the data science process and generative AI development.
Key Points:
🌟 Nvidia's AI blueprint helps developers easily build intelligent agents to analyze video and image content.
🏙️ Global companies like Accenture, Dell, etc., are already applying this technology to enhance productivity and safety.
🛠️ Developers can customize AI agents through natural language prompts, lowering the technical threshold.