NVIDIA Launches AI Foundry Service to Accelerate Enterprise AI Model Development

Nvidia's latest AI offering could spark a custom model gold rush

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia quietly unveiled its new AI Foundry service on Tuesday, aiming to help businesses create and deploy custom large language models tailored to their specific needs. The move signals Nvidia's push to capture a larger share of the booming enterprise AI market. The AI Foundry combines Nvidia's hardware, software tools, and expertise to enable companies to develop customized versions of popular open-source models like Meta's recently released Llama 3.1. This service arrives as businesses increasingly seek to harness the power of generative AI while maintaining control over their data and applications. "This is really the moment we've been waiting for," said Kari Briski, Nvidia's VP of AI Software, in a call with VentureBeat. "Enterprises scrambled to learn about generative AI. But something else happened that was probably equally important: the availability of open models." Customization drives accuracy: How Nvidia's AI Foundry boosts model performance Nvidia's new offering aims to simplify the complex process of adapting these open models for specific business use cases. The company claims significant improvements in model performance through customization. "We've seen almost a ten point increase in accuracy by simply customizing models," Briski explained. The AI Foundry service provides access to a vast array of pre-trained models, high-performance computing resources through Nvidia's DGX Cloud, and NeMo toolkit for model customization and evaluation. Expert guidance from Nvidia's AI specialists is also part of the package. "We provide the infrastructure and the tools for other companies to develop and customize AI models," Briski said. "Enterprises bring their data, we have DGX cloud that has capacity across many of our cloud partners." NIM: Nvidia's unique approach to AI model deployment Alongside the AI Foundry, Nvidia introduced NIM (Nvidia Inference Microservices), which packages customized models into containerized, API-accessible formats for easy deployment. This development represents a significant milestone for the company. "NIM is a model, a customized model and a container accessed by standard API," Briski said. "This is the culmination of years of work and research that we've done." Industry analysts view this move as a strategic expansion of Nvidia's AI offerings, potentially opening up new revenue streams beyond its core GPU business. The company is positioning itself as a full-stack AI solutions provider, not just a hardware manufacturer. Enterprise AI adoption: Nvidia's strategic bet on custom models The timing of Nvidia's announcement is particularly significant, happening the same day as Meta's Llama 3.1 release and amid growing concerns about AI safety and governance. By offering a service that allows companies to create and control their own AI models, Nvidia may be tapping into a market of enterprises that want the benefits of advanced AI without the risks associated with using public, general-purpose models. However, the long-term implications of widespread custom AI model deployment remain unclear. Potential challenges include fragmentation of AI capabilities across industries and the difficulty of maintaining consistent standards for AI safety and ethics. As competition in the AI sector intensifies, Nvidia's AI Foundry represents a significant bet on the future of enterprise AI adoption. The success of this gamble will largely depend on how effectively businesses can leverage these custom models to drive real-world value and innovation in their respective industries.

How NVIDIA AI Foundry Lets Enterprises Forge Custom Generative AI Models

Businesses seeking to harness the power of AI need customized models tailored to their specific industry needs. NVIDIA AI Foundry is a service that enables enterprises to use data, accelerated computing and software tools to create and deploy custom models that can supercharge their generative AI initiatives. Just as TSMC manufactures chips designed by other companies, NVIDIA AI Foundry provides the infrastructure and tools for other companies to develop and customize AI models -- using DGX Cloud, foundation models, NVIDIA NeMo software, NVIDIA expertise, as well as ecosystem tools and support. The key difference is the product: TSMC produces physical semiconductor chips, while NVIDIA AI Foundry helps create custom models. Both enable innovation and connect to a vast ecosystem of tools and partners. Enterprises can use AI Foundry to customize NVIDIA and open community models, including the new Llama 3.1 collection, as well as NVIDIA Nemotron, CodeGemma by Google DeepMind, CodeLlama, Gemma by Google DeepMind, Mistral, Mixtral, Phi-3, StarCoder2 and others. Industry leaders Amdocs, Capital One, Getty Images, KT, Hyundai Motor Company, SAP, ServiceNow and Snowflake are among the first using NVIDIA AI Foundry. These pioneers are setting the stage for a new era of AI-driven innovation in enterprise software, technology, communications and media. "Organizations deploying AI can gain a competitive edge with custom models that incorporate industry and business knowledge," said Jeremy Barnes, vice president of AI Product at ServiceNow. "ServiceNow is using NVIDIA AI Foundry to fine-tune and deploy models that can integrate easily within customers' existing workflows." NVIDIA AI Foundry is supported by the key pillars of foundation models, enterprise software, accelerated computing, expert support and a broad partner ecosystem. Its software includes AI foundation models from NVIDIA and the AI community as well as the complete NVIDIA NeMo software platform for fast-tracking model development. The computing muscle of NVIDIA AI Foundry is NVIDIA DGX Cloud, a network of accelerated compute resources co-engineered with the world's leading public clouds -- Amazon Web Services, Google Cloud and Oracle Cloud Infrastructure. With DGX Cloud, AI Foundry customers can develop and fine-tune custom generative AI applications with unprecedented ease and efficiency, and scale their AI initiatives as needed without significant upfront investments in hardware. This flexibility is crucial for businesses looking to stay agile in a rapidly changing market. If an NVIDIA AI Foundry customer needs assistance, NVIDIA AI Enterprise experts are on hand to help. NVIDIA experts can walk customers through each of the steps required to build, fine-tune and deploy their models with proprietary data, ensuring the models tightly align with their business requirements. NVIDIA AI Foundry customers have access to a global ecosystem of partners that can provide a full range of support. Accenture, Deloitte, Infosys and Wipro are among the NVIDIA partners that offer AI Foundry consulting services that encompass design, implementation and management of AI-driven digital transformation projects. Accenture is first to offer its own AI Foundry-based offering for custom model development, the Accenture AI Refinery framework. Additionally, service delivery partners such as Data Monsters, Quantiphi, Slalom and SoftServe help enterprises navigate the complexities of integrating AI into their existing IT landscapes, ensuring that AI applications are scalable, secure and aligned with business objectives. Customers can develop NVIDIA AI Foundry models for production using AIOps and MLOps platforms from NVIDIA partners, including Cleanlab, DataDog, Dataiku, Dataloop, DataRobot, Domino Data Lab, Fiddler AI, New Relic, Scale and Weights & Biases. Customers can output their AI Foundry models as NVIDIA NIM inference microservices -- which include the custom model, optimized engines and a standard API -- to run on their preferred accelerated infrastructure. Inferencing solutions like NVIDIA TensorRT-LLM deliver improved efficiency for Llama 3.1 models to minimize latency and maximize throughput. This enables enterprises to generate tokens faster while reducing total cost of running the models in production. Enterprise-grade support and security is provided by the NVIDIA AI Enterprise software suite. The broad range of deployment options includes NVIDIA-Certified Systems from global server manufacturing partners including Cisco, Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro, as well as cloud instances from Amazon Web Services, Google Cloud and Oracle Cloud Infrastructure. Additionally, Together AI, a leading AI acceleration cloud, today announced it will enable its ecosystem of over 100,000 developers and enterprises to use its NVIDIA GPU-accelerated inference stack to deploy Llama 3.1 endpoints and other open models on DGX Cloud. "Every enterprise running generative AI applications wants a faster user experience, with greater efficiency and lower cost," said Vipul Ved Prakash, founder and CEO of Together AI. "Now, developers and enterprises using the Together Inference Engine can maximize performance, scalability and security on NVIDIA DGX Cloud." With NVIDIA NeMo integrated into AI Foundry, developers have at their fingertips the tools needed to curate data, customize foundation models and evaluate performance. NeMo technologies include: Using the NeMo platform in NVIDIA AI Foundry, businesses can create custom AI models that are precisely tailored to their needs. This customization allows for better alignment with strategic objectives, improved accuracy in decision-making and enhanced operational efficiency. For instance, companies can develop models that understand industry-specific jargon, comply with regulatory requirements and integrate seamlessly with existing workflows. "As a next step of our partnership, SAP plans to use NVIDIA's NeMo platform to help businesses to accelerate AI-driven productivity powered by SAP Business AI," said Philipp Herzig, chief AI officer at SAP. Enterprises can deploy their custom AI models in production with NVIDIA NeMo Retriever NIM inference microservices. These help developers fetch proprietary data to generate knowledgeable responses for their AI applications with retrieval-augmented generation (RAG). "Safe, trustworthy AI is a non-negotiable for enterprises harnessing generative AI, with retrieval accuracy directly impacting the relevance and quality of generated responses in RAG systems," said Baris Gultekin, Head of AI, Snowflake. "Snowflake Cortex AI leverages NeMo Retriever, a component of NVIDIA AI Foundry, to further provide enterprises with easy, efficient, and trusted answers using their custom data." One of the key advantages of NVIDIA AI Foundry is its ability to address the unique challenges faced by enterprises in adopting AI. Generic AI models can fall short of meeting specific business needs and data security requirements. Custom AI models, on the other hand, offer superior flexibility, adaptability and performance, making them ideal for enterprises seeking to gain a competitive edge.

NVIDIA : How NVIDIA AI Foundry Lets Enterprises Forge Custom Generative AI Models

Businesses seeking to harness the power of AI need customized models tailored to their specific industry needs. NVIDIA AI Foundry is a service that enables enterprises to use data, accelerated computing and software tools to create and deploy custom models that can supercharge their generative AI initiatives. Just as TSMC manufactures chips designed by other companies, NVIDIA AI Foundry provides the infrastructure and tools for other companies to develop and customize AI models - using DGX Cloud, foundation models, NVIDIA NeMo software, NVIDIA expertise, as well as ecosystem tools and support. The key difference is the product: TSMC produces physical semiconductor chips, while NVIDIA AI Foundry helps create custom models. Both enable innovation and connect to a vast ecosystem of tools and partners. Enterprises can use AI Foundry to customize NVIDIA and open community models, including the new Llama 3.1 collection, as well as NVIDIA Nemotron, CodeGemma by Google DeepMind, CodeLlama, Gemma by Google DeepMind, Mistral, Mixtral, Phi-3, StarCoder2 and others. Industry leaders Amdocs, Capital One, Getty Images, KT, Hyundai Motor Company, SAP, ServiceNow and Snowflake are among the first using NVIDIA AI Foundry. These pioneers are setting the stage for a new era of AI-driven innovation in enterprise software, technology, communications and media. "Organizations deploying AI can gain a competitive edge with custom models that incorporate industry and business knowledge," said Jeremy Barnes, vice president of AI Product at ServiceNow. "ServiceNow is using NVIDIA AI Foundry to fine-tune and deploy models that can integrate easily within customers' existing workflows." NVIDIA AI Foundry is supported by the key pillars of foundation models, enterprise software, accelerated computing, expert support and a broad partner ecosystem. Its software includes AI foundation models from NVIDIA and the AI community as well as the complete NVIDIA NeMo software platform for fast-tracking model development. The computing muscle of NVIDIA AI Foundry is NVIDIA DGX Cloud, a network of accelerated compute resources co-engineered with the world's leading public clouds - Amazon Web Services, Google Cloud and Oracle Cloud Infrastructure. With DGX Cloud, AI Foundry customers can develop and fine-tune custom generative AI applications with unprecedented ease and efficiency, and scale their AI initiatives as needed without significant upfront investments in hardware. This flexibility is crucial for businesses looking to stay agile in a rapidly changing market. If an NVIDIA AI Foundry customer needs assistance, NVIDIA AI Enterprise experts are on hand to help. NVIDIA experts can walk customers through each of the steps required to build, fine-tune and deploy their models with proprietary data, ensuring the models tightly align with their business requirements. NVIDIA AI Foundry customers have access to a global ecosystem of partners that can provide a full range of support. Accenture, Deloitte, Infosys and Wipro are among the NVIDIA partners that offer AI Foundry consulting services that encompass design, implementation and management of AI-driven digital transformation projects. Accenture is first to offer its own AI Foundry-based offering for custom model development, the Accenture AI Refinery framework. Additionally, service delivery partners such as Data Monsters, Quantiphi, Slalom and SoftServe help enterprises navigate the complexities of integrating AI into their existing IT landscapes, ensuring that AI applications are scalable, secure and aligned with business objectives. Customers can develop NVIDIA AI Foundry models for production using AIOps and MLOps platforms from NVIDIA partners, including Cleanlab, DataDog, Dataiku, Dataloop, DataRobot, Domino Data Lab, Fiddler AI, New Relic, Scale and Weights & Biases. Customers can output their AI Foundry models as NVIDIA NIM inference microservices - which include the custom model, optimized engines and a standard API - to run on their preferred accelerated infrastructure. Inferencing solutions like NVIDIA TensorRT-LLM deliver improved efficiency for Llama 3.1 models to minimize latency and maximize throughput. This enables enterprises to generate tokens faster while reducing total cost of running the models in production. Enterprise-grade support and security is provided by the NVIDIA AI Enterprise software suite. The broad range of deployment options includes NVIDIA-Certified Systems from global server manufacturing partners including Cisco, Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro, as well as cloud instances from Amazon Web Services, Google Cloud and Oracle Cloud Infrastructure. Additionally, Together AI, a leading AI acceleration cloud, today announced it will enable its ecosystem of over 100,000 developers and enterprises to use its NVIDIA GPU-accelerated inference stack to deploy Llama 3.1 endpoints and other open models on DGX Cloud. "Every enterprise running generative AI applications wants a faster user experience, with greater efficiency and lower cost," said Vipul Ved Prakash, founder and CEO of Together AI. "Now, developers and enterprises using the Together Inference Engine can maximize performance, scalability and security on NVIDIA DGX Cloud." With NVIDIA NeMo integrated into AI Foundry, developers have at their fingertips the tools needed to curate data, customize foundation models and evaluate performance. NeMo technologies include: Using the NeMo platform in NVIDIA AI Foundry, businesses can create custom AI models that are precisely tailored to their needs. This customization allows for better alignment with strategic objectives, improved accuracy in decision-making and enhanced operational efficiency. For instance, companies can develop models that understand industry-specific jargon, comply with regulatory requirements and integrate seamlessly with existing workflows. "As a next step of our partnership, SAP plans to use NVIDIA's NeMo platform to help businesses to accelerate AI-driven productivity powered by SAP Business AI," said Philipp Herzig, chief AI officer at SAP. Enterprises can deploy their custom AI models in production with NVIDIA NeMo Retriever NIM inference microservices. These help developers fetch proprietary data to generate knowledgeable responses for their AI applications with retrieval-augmented generation (RAG). "Safe, trustworthy AI is a non-negotiable for enterprises harnessing generative AI, with retrieval accuracy directly impacting the relevance and quality of generated responses in RAG systems," said Baris Gultekin, Head of AI, Snowflake. "Snowflake Cortex AI leverages NeMo Retriever, a component of NVIDIA AI Foundry, to further provide enterprises with easy, efficient, and trusted answers using their custom data." One of the key advantages of NVIDIA AI Foundry is its ability to address the unique challenges faced by enterprises in adopting AI. Generic AI models can fall short of meeting specific business needs and data security requirements. Custom AI models, on the other hand, offer superior flexibility, adaptability and performance, making them ideal for enterprises seeking to gain a competitive edge.