Generative AI

NVIDIA NeMo

Build, customize, and deploy large language models.

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    What Is NVIDIA NeMo?

    NVIDIA NeMo™ is an end-to-end, cloud-native framework to build, customize, and deploy generative AI models anywhere. It includes training and inferencing frameworks, guardrailing toolkits, data curation tools, and pretrained models, offering enterprises an easy, cost-effective, and fast way to adopt generative AI.

    Building and Deploying Generative AI Models

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    Explore the Benefits of NVIDIA NeMo

    End to End

    Complete solution across the LLM pipeline—from data processing, to training, to inference of generative AI models.

    Enterprise Grade

    Secure, optimized, full-stack solution designed to accelerate enterprises with support, security, and API stability available as part of NVIDIA AI Enterprise.

    Increased ROI

    NeMo allows organizations to quickly train, customize, and deploy LLMs at scale, reducing time to solution and increasing return on investment.

    Flexible

    End-to-end framework with capabilities to curate data, train large-scale models up to trillions of parameters, and deploy them in inference.

    Open Source

    Available as open source through GitHub and the NVIDIA NGC software catalog to make it easier for developers and researchers to create new LLMs.

    Accelerate Training & Inference

    Multi-node and multi-GPU training and inference to maximize throughput and minimize LLM training time.

    Complete Solution for Building
    Enterprise-Ready Large Language Models

    As generative AI models and their development rapidly evolve and expand, the complexity of the AI stack and its dependencies grows. For enterprises running their business on AI, NVIDIA AI Enterprise provides a production-grade, secure, end-to-end software platform which includes NeMo, as well as generative AI reference applications and enterprise support to streamline adoption.

    State-of-the-Art Training Techniques

    NeMo provides tooling for distributed training for LLMs that enable advanced scale, speed, and efficiency.

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    Advanced LLM Customization Tools

    Integrate real-time, domain-specific data via NeMo Retriever. This facilitates tailored responses to your business's unique challenges and allows the embedding of specialized skills to address specific customer and enterprise needs. 

    NeMo Guardrails helps define operational boundaries so the models stay within the intended domain and avoid inappropriate outputs.

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    Optimized AI Inference With NVIDIA Triton

    Deploy generative AI models with powerful optimizations using NVIDIA Triton Inference Server. Automate the deployment of multiple Triton Inference Server instances in Kubernetes with resource-efficient model orchestration using Triton Management Service.

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    Easy-to-Use Recipes and Tools for Generative AI

    NeMo makes generative AI possible from day one with prepackaged scripts, reference examples, and documentation across the entire pipeline. 

    Building foundation models is also made easy through an auto-configurator tool, which automatically searches for the best hyperparameter configurations to optimize training and inference for any given multi-GPU configuration, training, or deployment constraints.

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    Best-in-Class Pretrained Models

    Build your custom enterprise models using NeMo and NVIDIA AI Foundation models—community- and NVIDIA-built pretrained models that enable developers to create custom models faster. These NVIDIA-optimized models incorporate the latest training and inference techniques to achieve the best performance. 

    Experience NVIDIA AI Foundation Models Now
    Get Access to NVGPT-8B Model

    Optimized Retrieval-Augmented Generation

    Build powerful generative AI applications that pull information and insights from enterprise data sources. NeMo Retriever provides commercially ready NVIDIA AI Foundation Models and microservices that help customers build accelerated, enterprise AI applications.

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    NeMo Retriver workflow that includes RAG NeMo Retriver workflow that includes RAG NeMo Retriver workflow that includes RAG NeMo Retriver workflow that includes RAG

    Get Started With NVIDIA NeMo

    Download the NVIDIA NeMo Framework

    Get immediate access to training and inference tools to make generative AI model development easy, cost-effective, and fast for enterprises.

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    AI Chatbot With Retrieval Augmented Generation

    This workflow accelerates building and deploying enterprise solutions that accurately generate responses using real-time information.

    Explore the Workflow Try the Hands-On LaunchPad lab

    Experience Generative AI Models on the Fly

    The NVIDIA AI Playground offers an easy-to-use interface to quickly try generative AI models using an API or a user interface from your browser.

    Try AI Foundation Models

    Apply for NeMo Framework Multi-Modal Early Access

    Get access to build, customize, and deploy multimodal generative AI models with billions of parameters. Your application may take 2+ weeks to be reviewed.

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    Sign Up for NVIDIA AI Workbench Early Access

    With this unified, easy-to-use toolkit, developers can quickly create, test, and customize pretrained generative AI models and LLMs on a PC or workstation—then scale them to any data center, public cloud, or NVIDIA DGX Cloud.

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    Sign Up for NVIDIA NeMo ServiceEarly Access

    Apply for early access to NVIDIA NeMo service to hyper-personalize LLMs for enterprise AI applications and deploy them at scale.

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    Latest Large Language Model Innovations

    NVIDIA Brings Business Intelligence to Chatbots, Copilots and Summarization Tools With Enterprise-Grade Generative AI Microservice

    Cadence, Dropbox, SAP, ServiceNow first to access NVIDIA NeMo Retriever to optimize semantic retrieval for accurate AI inference.

    Read the Press Release

    Latest Large Language Model Innovations

    Retrieval Augmented Generation

    Retrieval augmented generation is a technique for large language models to create responses from the latest information by connecting the LLM to the company’s knowledge base. NeMo works with various third-party and community tools, including Milvus, Llama Index, and Langchain, to extract relevant snippets of information from the vector database and feed that to the LLM to generate responses in natural language.

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    Latest Large Language Model Innovations

    Easily Customize LLMs for Any Use Case

    NVIDIA NeMo SteerLM is a simple, practical, and novel technique for aligning LLMs with just a single training run. It offers faster training times, lower total cost of ownership, and optimization of accelerated computing. Developers can use it to continuously improve LLMs as well as tune and control their behavior across several dimensions at inference time. SteerLM offers unprecedented simplicity and state-of-the-art accuracy in aligning models for specific use cases.

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    Latest Large Language Model Innovations

    Silicon Volley: Designers Tap Generative AI for a Chip Assist

    Semiconductor engineers show how a specialized industry can customize large language models to gain an edge using NVIDIA NeMo.

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    Latest Large Language Model Innovations

    NeMo Guardrails Keeps AI Chatbots on Track

    Open-source software helps developers add guardrails to AI chatbots to keep applications built on large language models aligned with their safety and security requirements.

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    Latest Large Language Model Innovations

    Simplified Data Curation for Large Language Models

    NeMo Data Curator is a scalable data-curation tool that enables developers to curate trillion-token multilingual datasets for pretraining LLMs—meeting the growing needs for large datasets.

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    Customers Using NeMo to Build Custom LLMs

    Accelerate Industry Applications With LLMs

    AI Sweden facilitated regional language model applications by providing easy access to a powerful 100 billion parameter model. They digitized historical records to develop language models for commercial use.

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    Image Courtesy of Korea Telecom

    Creating New Customer Experiences With LLMs

    South Korea’s leading mobile operator builds billion-parameter LLMs trained with the NVIDIA DGX SuperPOD platform and NeMo framework to power smart speakers and customer call centers.

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    Building Generative AI Across Enterprise IT

    ServiceNow develops custom LLMs on their ServiceNow platform to enable intelligent workflow automation and boost productivity across enterprise IT processes.

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    Custom Content Generation for Enterprises

    Writer uses generative AI to build custom content for enterprise use cases across marketing, training, support, and more.

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    Harnessing Enterprise Data for Generative AI

    Snowflake lets businesses create customized generative AI applications using proprietary data within the Snowflake Data Cloud.

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    Leading Adopters Across Industries

    Check Out NeMo Resources

    Intro to NeMo and the Latest Updates

    NVIDIA recently announced general availability for NeMo. Check out the blog to see what’s new and start building, customizing, and deploying LLMs at scale.

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    Get Started With NeMo Docs

    Get everything you need to get started with NVIDIA NeMo, including tutorials, Jupyter Notebooks, and documentation.

    Review NeMo Documentation

    Explore Technical Blogs on LLMs

    Read these technical walkthroughs for NeMo and learn how to build, customize, and deploy generative AI models at scale.

    Explore NeMo Blogs

    Download the LLM Enterprise Ebook

    Learn everything you need to know about LLMs, including how they work, the possibilities they unlock, and real-world case studies.

    Download Ebook

    Get Started Now With NVIDIA NeMo

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    AI Sweden

    Accelerate Industry Applications With LLMs

    AI Sweden facilitated regional language model applications by providing easy access to a powerful 100 billion-parameter model. They digitized historical records to develop language models for commercial use.

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    Amdocs

    NVIDIA and Amdocs Bring Custom Generative AI to Global Telco Industry

    Amdocs plans to build custom LLMs for $1.7 trillion global telecommunications industry using NVIDIA AI foundry service on Microsoft Azure.

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    Dropbox

    Dropbox and NVIDIA to Bring Personalized Generative AI to Millions of Customers

    Dropbox plans to leverage NVIDIA’s AI foundry to build custom models and improve AI-powered knowledge work with Dropbox Dash universal search tool and Dropbox AI.

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    KT

    Creating New Customer Experiences With LLMs

    South Korea’s leading mobile operator builds billion-parameter LLMs trained with the NVIDIA DGX SuperPOD platform and NeMo framework to power smart speakers and customer call centers.

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    Palo Alto Networks

    Bringing Generative AI to Cybersecurity

    Palo Alto Networks builds security copilot that helps customers get the most out of its platform by optimizing security, configuration, and operations.

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    ServiceNow

    Building Generative AI Across Enterprise IT

    ServiceNow develops custom LLMs on its ServiceNow platform to enable intelligent workflow automation and boost productivity across enterprise IT processes.

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    Writer

    Startup Pens Generative AI Success Story With NVIDIA NeMo

    Using NVIDIA NeMo, Writer is building LLMs that are helping hundreds of companies create custom content for enterprise use cases across marketing, training, support, and more. 

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    AWS

    NVIDIA Powers Training for Some of the Largest Amazon Titan Foundation Models

    Amazon leveraged the NVIDIA NeMo framework, GPUs, and AWS EFAs to train its next-generation LLM, giving some of the largest Amazon Titan foundation models customers a faster, more accessible solution for generative AI.

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    Azure

    Harnessing the Power of NVIDIA AI Enterprise on Azure Machine Learning

    Get access to a complete ecosystem of tools, libraries, frameworks, and support services tailored for enterprise environments on Microsoft Azure.

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    Dell

    Dell Validated Design for Generative AI With NVIDIA

    Dell Technologies and NVIDIA announced an initiative to make it easier for businesses to build and use generative AI models on premises quickly and securely.

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    Deloitte

    Unlock the Value of Generative AI Across Enterprise Software Platforms

    Deloitte will use NVIDIA AI technology and expertise to build high-performing generative AI solutions for enterprise software platforms to help unlock significant business value.

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    Domino Data Lab

    Domino Offers Production-Ready Generative AI Powered by NVIDIA

    With NVIDIA NeMo, data scientists can fine-tune LLMs in Domino’s platform for domain-specific use cases based on proprietary data and IP—without needing to start from scratch. 

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    Google Cloud

    AI Titans Collaborate to Create Generative AI Magic

    At its Next conference, Google Cloud announced the availability of its A3 instances powered by NVIDIA H100 Tensor Core GPUs. Engineering teams from both companies have collaborated to bring NVIDIA NeMo to the A3 instances for faster training and inference.

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    Lenovo

    New Reference Architecture for Generative AI Based on LLMs

    Solution to expedite innovation by empowering global partners and customers to develop, train, and deploy AI at scale across industry verticals with utmost safety and efficiency.

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    Quantiphi

    Enabling Enterprises to Fast-Track Their AI-Driven Journeys

    Quantiphi specializes in training and fine-tuning foundation models using the NVIDIA NeMo framework, as well as optimizing deployments at scale with the NVIDIA AI Enterprise software platform, while adhering to responsible AI principles.

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    VMware

    VMware and NVIDIA Unlock Generative AI for Enterprises

    VMware Private AI Foundation with NVIDIA will enable enterprises to customize models and run generative AI applications, including intelligent chatbots, assistants, search, and summarization.

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    Weight & Biases

    Debug, Optimize, and Monitor LLM Pipelines 

    Weights & Biases helps teams working on generative AI use cases or with LLMs track and visualize all prompt-engineering experiments—helping users debug and optimize LLM pipelines—as well as provides monitoring and observability capabilities for LLMs. 

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