Nvidia has announced a strategic collaboration with several US technology companies to facilitate the development of custom AI applications across various industries, utilising its latest NIM Agent Blueprints, NeMo, and NIM microservices. According to Nvidia, key industry players such as AT&T, Lowe's, and the University of Florida are leveraging these microservices to create data-driven AI flywheels that power custom generative AI applications.
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Collaborations with Key Industry Players
US consulting companies like Accenture, Deloitte, Quantiphi, and SoftServe are also adopting Nvidia's NIM Agent Blueprints, NeMo, and NIM microservices to support clients in sectors such as healthcare, manufacturing, and telecommunications in building custom generative AI agents and copilots.
Data and AI platform companies such as Cadence, Cloudera, DataStax, Google Cloud, NetApp, SAP, ServiceNow, and Teradata are enhancing their platforms with Nvidia's NIM.
"AI is driving transformation and shaping the future of global industries," said Jensen Huang, founder and CEO of Nvidia. "In collaboration with US companies, universities and government agencies, Nvidia will help advance AI adoption to boost productivity and drive economic growth."
Nvidia NeMo Microservices
The new Nvidia NeMo microservices simplify the customisation of AI models and workflows, enabling businesses to bring generative AI applications to market faster and at lower costs. The new NeMo microservices — Customiser, Evaluator, and Guardrails — can be paired with NIM microservices to improve data management and model evaluation, Nvidia said.
NIM Agent Blueprints
Nvidia's NIM Agent Blueprints provide developers with reference workflows to accelerate application development for critical enterprise use cases, including drug discovery, customer service, and data extraction, with a recent addition focused on software container security.
"A new blueprint for software container security is available today," the company announced on Tuesday.
Noteworthy applications include AT&T's conversational platform, enhancements to the University of Florida's learning management system, and Lowe’s initiatives to improve customer and associate experiences.
Accenture is helping clients build domain-specific AI agents, Deloitte is integrating the latest Nvidia NIM Agent Blueprint into its cybersecurity solutions, and SoftServe's generative AI Industrial Assistant, using NeMo and NIM microservices, is enhancing safety and efficiency in industrial manufacturing, Nvidia said.
Additionally, tech partners like Cloudera and Google Cloud are integrating Nvidia's microservices into their platforms, optimising the deployment of large language models.
Cloudera Unveils AI Inference Service
Cloudera unveiled an AI Inference Service with embedded NIM, allowing developers to build, customise, and deploy enterprise-grade large language models with up to 36x faster inference performance.
Nvidia is allowing developers to experiment with its AI software, including microservices, at no cost through an Nvidia Developer license, the company said.
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Terminology You Need to Know:
What Are Microservices?
Microservices are a software development approach that breaks down large applications into smaller, independent services. Each service focuses on a specific business capability and communicates with others through well-defined APIs (Application Programming Interfaces).
What Is a Blueprint?
In software development, a blueprint is a high-level design document that outlines the architecture, components, and interactions of a software system.
Nvidia NeMo (Neural Modules) is a cloud-based framework designed to accelerate the development and deployment of conversational AI applications. It provides a collection of pre-trained neural networks, along with tools and APIs, that can be used to build and customise chatbots, virtual assistants, and other AI-powered conversational experiences.
Nvidia NIM (Nvidia inference microservice) is a set of easy-to-use inference microservices that allow organisations to run AI models on any cloud or data center. It's essentially a collection of tools, blueprints, and microservices that provide developers with the infrastructure needed to create custom generative AI applications and intelligent agents, which can work together to perform complex tasks across various industries.
