Companies looking to harness the power of AI need custom models tailored to the specific needs of their industry.
NVIDIA AI Foundry is a service that enables companies to use data, accelerated computing, and software tools to create and deploy custom models that can power their generative AI initiatives.
Just as TSMC makes 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, base models, NVIDIA NeMo software, NVIDIA expertise, and 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.
Companies can use AI Foundry to customize NVIDIA and open community models, including the new Call 3.1 collection, as well as NVIDIA NemotronGoogle DeepMind CodeGemma, CodeLlama, Google DeepMind Gemma, Mistral, Mixtral, Phi-3, StarCoder2 and others.
Industry pioneers drive AI innovation
Industry Leaders amdocs DocumentsCapital One, Getty Images, KT, Hyundai Motor Company, SAPServiceNow and Snowflake are among the first to use NVIDIA AI Foundry. These pioneers are laying the groundwork for a new era of AI-driven innovation in enterprise software, technology, communications, and media.
“Organizations deploying AI can gain a competitive advantage with custom models that incorporate industry and business insights,” said Jeremy Barnes, vice president of AI products at ServiceNow. “ServiceNow is using NVIDIA AI Foundry to refine and deploy models that can be easily integrated into customers’ existing workflows.”
The pillars of the NVIDIA AI Foundry
NVIDIA AI Foundry is backed by the key pillars of foundational models, enterprise software, accelerated computing, expert support, and a broad partner ecosystem.
Its software includes core AI models from NVIDIA and the AI community, as well as the full software NVIDIA NeMo Software platform for rapid model development.
The computing power of NVIDIA AI Foundry is NVIDIA DGX Clouda network of accelerated computing resources designed in conjunction 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 tune custom generative AI applications with unprecedented ease and efficiency, and scale their AI initiatives as needed without significant upfront hardware investments. This flexibility is crucial for enterprises looking to stay agile in a rapidly changing marketplace.
If an NVIDIA AI Foundry customer needs assistance, NVIDIA AI Enterprise experts are available to help. NVIDIA experts can guide customers through each of the steps required to build, tune, and deploy their models with proprietary data, ensuring that the models align perfectly with their business requirements.
NVIDIA AI Foundry customers have access to a global ecosystem of partners who can provide a full range of support. Accenture, Deloitte, Infosys, and Wipro are among NVIDIA partners offering AI Foundry consulting services spanning the design, implementation, and management of AI-powered digital transformation projects. Accenture is the 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 environments, ensuring 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, Artificial intelligence violinistNew Relic, Scale and Weights and Biases.
Customers can generate their AI Foundry models as NVIDIA NIM inference microservices, including custom model, optimized engines, and a standard API, to run on your preferred accelerated infrastructure.
Infer solutions such as NVIDIA TensorRT-LLM Delivering increased efficiency for Llama 3.1 models to minimize latency and maximize throughput. This allows businesses to generate tokens faster while reducing the overall cost of running models in production. Enterprise-grade support and security are provided by NVIDIA AI for Business Software package.
The wide 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.
Besides, Together AIa leading AI acceleration cloud, today announced that 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, more efficient, and lower-cost user experience,” said Vipul Ved Prakash, founder and CEO of Together AI. “Now, developers and enterprises using Together Inference Engine can maximize performance, scalability, and security on NVIDIA DGX Cloud.”
NVIDIA NeMo speeds up and simplifies custom model development
With NVIDIA NeMo Integrated into AI Foundry, developers have the tools to curate data, customize base models, and evaluate performance. NeMo technologies include:
- NeMo Curator is a GPU-accelerated data curation library that improves generative AI model performance by preparing large-scale, high-quality datasets for pretraining and fine-tuning.
- NeMo Customizer is a scalable, high-performance microservice that simplifies tuning and aligning LLM for domain-specific use cases.
- NeMo Evaluator Provides automatic evaluation of generative AI models on academic and custom benchmarks on any cloud or accelerated data center.
- NeMo Railings Orchestrates dialogue management, supporting accuracy, appropriateness, and safety in intelligent applications with large language models to provide protection for generative AI applications.
By using the NeMo platform on NVIDIA AI Foundry, companies can build custom AI models that precisely fit their needs. This customization enables better alignment with strategic goals, greater decision-making accuracy, and increased operational efficiency. For example, companies can develop models that understand industry-specific jargon, meet regulatory requirements, and integrate seamlessly with existing workflows.
“As the next step in our partnership, SAP plans to use NVIDIA’s NeMo platform to help businesses accelerate AI-driven productivity with SAP Business AI,” said Philipp Herzig, chief AI officer at SAP.
Companies can deploy their custom AI models into production with NVIDIA NeMo NIM File Recovery Inference microservices. These help developers obtain proprietary data to generate informed answers for their AI applications with Generation increased by recovery (RAG).
“Safe and reliable AI is a non-negotiable for companies leveraging generative AI, as retrieval accuracy directly impacts the relevance and quality of answers generated in RAG systems,” said Baris Gultekin, director of AI at Snowflake. “Snowflake Cortex AI leverages NeMo Retriever, a component of NVIDIA AI Foundry, to provide companies with easy, efficient, and reliable answers using their custom data.”
Customized models drive competitive advantage
One of the key advantages of NVIDIA AI Foundry is its ability to address the unique challenges businesses face when adopting AI. Generic AI models may not meet specific business needs and data security requirements. On the other hand, custom AI models offer superior flexibility, adaptability, and performance, making them ideal for businesses looking to gain a competitive advantage.
Learn more about how NVIDIA AI Foundry Enables businesses to boost productivity and innovation.
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