NVIDIA NIM Revolutionizes Model Deployment, Now Available to Transform World’s Millions of Developers Into Generative AI Developers
NVIDIA has launched NIM (NVIDIA Inference Microservices) at COMPUTEX, enabling 28 million developers to easily deploy generative AI applications. NIM allows for rapid deployment of models as optimized containers on various infrastructures, significantly enhancing developer productivity. Enterprises can leverage NIM to maximize their infrastructure, with companies like Meta, Hugging Face, and over 150 partners integrating NIM to accelerate AI deployments. The tool supports various applications, including text, image, video generation, and digital human avatars, with free access for NVIDIA Developer Program members starting next month. NIM's robust ecosystem includes integrations with AWS, Google Cloud, and Azure, helping enterprises across sectors like healthcare, retail, and manufacturing enhance their AI capabilities.
- NVIDIA NIM reduces AI application deployment time from weeks to minutes.
- Developer productivity is significantly boosted by NIM’s standardized approach.
- NIM enhances infrastructural efficiency, generating up to 3x more AI tokens.
- 150+ technology partners, including industry leaders like Meta and Hugging Face, are implementing NIM.
- Free access for NVIDIA Developer Program members starting next month for R&D.
- Over 40 pre-built NVIDIA and community models available for deployment.
- Wide range of industry applications, including healthcare, retail, and manufacturing.
- NIM integration with major cloud providers like AWS, Google Cloud, and Azure.
- Enhanced AI capabilities for enterprises without dedicated AI teams.
- Potential risk of oversaturation in the AI deployment market.
- Possible increase in competition among AI service providers leveraging NIM.
- Cost implications for enterprises scaling AI deployments.
- Dependence on NVIDIA infrastructure might limit flexibility for some developers.
Insights
NVIDIA NIM introduces a substantial leap in the ease and speed of deploying generative AI solutions. By providing fully optimized containers ready for deployment, NVIDIA significantly reduces the development overhead for companies looking to integrate generative AI into their products. This is particularly intriguing for developers who now have immediate access to efficient, scalable AI tools.
The supported integration with multiple major platforms like Amazon Web Services, Google Cloud and Microsoft Azure ensures vast accessibility. Developers can now deploy AI models without extensive expertise in AI infrastructure, democratizing advanced AI capabilities. This can foster innovation across various industries, as smaller companies can now harness the power of AI without needing large-scale AI teams.
Moreover, the mention of substantial partners like Foxconn and Siemens leveraging NIM underscores the trust and reliability of NVIDIA's solution, positioning it as a key player in the AI sector. However, businesses need to consider the dependency on NVIDIA's ecosystem, which could limit flexibility.
From a financial standpoint, NVIDIA's NIM has enormous potential to drive revenue growth by expanding its market reach. By making AI deployment more accessible, NVIDIA can tap into a broader customer base, including small and medium-sized enterprises. The efficiency gains cited, such as producing 3x more generative AI tokens with the same infrastructure, offer significant cost reductions for enterprises. This makes NIM a compelling investment for companies looking to enhance operational efficiencies and reduce costs.
Given the extensive partner network, including tech giants and global system integrators, NVIDIA's NIM stands to establish a dominant position in the AI market. This could translate into sustained revenue streams from both new and existing customers who seek to leverage these advanced AI tools. However, the reliance on partner platforms can be a double-edged sword, as it might expose NVIDIA to competitive pressures and revenue-sharing constraints.
Overall, the financial prospects look promising, provided NVIDIA can maintain its technological edge and continue to innovate in this rapidly evolving space.
From a market research perspective, the introduction of NIM could potentially reshape the AI deployment landscape. By simplifying the process of integrating generative AI, NVIDIA is likely to see increased adoption across diverse sectors, including retail, healthcare, manufacturing and financial services. The ability to deploy complex AI models quickly and efficiently lowers the entry barriers for companies looking to leverage AI, thereby expanding the overall market size.
The strong endorsement from industry leaders and the integration with popular platforms suggest that NIM has practical, real-world applications. This widespread adoption and validation are important for building credibility and trust among prospective users. For retail investors, the broad applicability and endorsements indicate a robust market opportunity, with NVIDIA positioned to capture significant market share.
However, it's also important to monitor how competitors respond. Companies like Google and Microsoft, which are heavily invested in AI, might introduce similar solutions, potentially intensifying competition. Investors should keep an eye on market trends and competitor actions to gauge the long-term impact.
- 150+ Partners Across Every Layer of AI Ecosystem Embedding NIM Inference Microservices to Speed Enterprise AI Application Deployments From Weeks to Minutes
- NVIDIA Developer Program Members Gain Free Access to NIM for Research, Development and Testing
TAIPEI, Taiwan, June 02, 2024 (GLOBE NEWSWIRE) -- COMPUTEX -- NVIDIA today announced that the world’s 28 million developers can now download NVIDIA NIM™ — inference microservices that provide models as optimized containers — to deploy on clouds, data centers or workstations, giving them the ability to easily build generative AI applications for copilots, chatbots and more, in minutes rather than weeks.
These new generative AI applications are becoming increasingly complex and often utilize multiple models with different capabilities for generating text, images, video, speech and more. NVIDIA NIM dramatically increases developer productivity by providing a simple, standardized way to add generative AI to their applications.
NIM also enables enterprises to maximize their infrastructure investments. For example, running Meta Llama 3-8B in a NIM produces up to 3x more generative AI tokens on accelerated infrastructure than without NIM. This lets enterprises boost efficiency and use the same amount of compute infrastructure to generate more responses.
Nearly 200 technology partners — including Cadence, Cloudera, Cohesity, DataStax, NetApp, Scale AI and Synopsys — are integrating NIM into their platforms to speed generative AI deployments for domain-specific applications, such as copilots, code assistants and digital human avatars. Hugging Face is now offering NIM — starting with Meta Llama 3.
“Every enterprise is looking to add generative AI to its operations, but not every enterprise has a dedicated team of AI researchers,” said Jensen Huang, founder and CEO of NVIDIA. “Integrated into platforms everywhere, accessible to developers everywhere, running everywhere — NVIDIA NIM is helping the technology industry put generative AI in reach for every organization.”
Enterprises can deploy AI applications in production with NIM through the NVIDIA AI Enterprise software platform. Starting next month, members of the NVIDIA Developer Program can access NIM for free for research, development and testing on their preferred infrastructure.
40+ NIM Microservices Power Gen AI Models Across Modalities
NIM containers are pre-built to speed model deployment for GPU-accelerated inference and can include NVIDIA CUDA® software, NVIDIA Triton Inference Server™ and NVIDIA TensorRT™-LLM software.
Over 40 NVIDIA and community models are available to experience as NIM endpoints on ai.nvidia.com, including Databricks DBRX, Google’s open model Gemma, Meta Llama 3, Microsoft Phi-3, Mistral Large, Mixtral 8x22B and Snowflake Arctic.
Developers can now access NVIDIA NIM microservices for Meta Llama 3 models from the Hugging Face AI platform. This lets developers easily access and run the Llama 3 NIM in just a few clicks using Hugging Face Inference Endpoints, powered by NVIDIA GPUs on their preferred cloud.
Enterprises can use NIM to run applications for generating text, images and video, speech and digital humans. With NVIDIA BioNeMo™ NIM microservices for digital biology, researchers can build novel protein structures to accelerate drug discovery.
Dozens of healthcare companies are deploying NIM to power generative AI inference across a range of applications, including surgical planning, digital assistants, drug discovery and clinical trial optimization.
With new NVIDIA ACE NIM microservices, developers can easily build and operate interactive, lifelike digital humans in applications for customer service, telehealth, education, gaming and entertainment.
Hundreds of AI Ecosystem Partners Embedding NIM
Platform providers including Canonical, Red Hat, Nutanix and VMware (acquired by Broadcom) are supporting NIM on open-source KServe or enterprise solutions. AI application companies Hippocratic AI, Glean, Kinetica and Redis are also deploying NIM to power generative AI inference.
Leading AI tools and MLOps partners — including Amazon SageMaker, Microsoft Azure AI, Dataiku, DataRobot, deepset, Domino Data Lab, LangChain, Llama Index, Replicate, Run.ai, Saturn Cloud, Securiti AI and Weights & Biases — have also embedded NIM into their platforms to enable developers to build and deploy domain-specific generative AI applications with optimized inference.
Global system integrators and service delivery partners Accenture, Deloitte, Infosys, Latentview, Quantiphi, SoftServe, TCS and Wipro have created NIM competencies to help the world’s enterprises quickly develop and deploy production AI strategies.
Enterprises can run NIM-enabled applications virtually anywhere, including on NVIDIA-Certified Systems™ from global infrastructure manufacturers Cisco, Dell Technologies, Hewlett-Packard Enterprise, Lenovo and Supermicro, as well as server manufacturers ASRock Rack, ASUS, GIGABYTE, Ingrasys, Inventec, Pegatron, QCT, Wistron and Wiwynn. NIM microservices have also been integrated into Amazon Web Services, Google Cloud, Azure and Oracle Cloud Infrastructure.
Titans of Industry Amp Up Generative AI With NIM
Industry leaders Foxconn, Pegatron, Amdocs, Lowe’s, ServiceNow and Siemens are among the businesses using NIM for generative AI applications in manufacturing, healthcare, financial services, retail, customer service and more:
- Foxconn — the world’s largest electronics manufacturer — is using NIM in the development of domain-specific LLMs embedded into a variety of internal systems and processes in its AI factories for smart manufacturing, smart cities and smart electric vehicles.
- Pegatron — a Taiwanese electronics manufacturing company — is leveraging NIM for Project TaME, a Taiwan Mixtral of Experts model designed to advance the development of local LLMs for industries.
- Amdocs — a leading global provider of software and services to communications and media companies — is using NIM to run a customer billing LLM that significantly lowers the cost of tokens, improves accuracy by up to
30% and reduces latency by80% , driving near real-time responses. - Lowe’s — a FORTUNE® 50 home improvement company — is using generative AI for a variety of use cases. For example, the retailer is leveraging NVIDIA NIM inference microservices to elevate experiences for associates and customers.
- ServiceNow — the AI platform for business transformation — announced earlier this year that it was one of the first platform providers to access NIM to enable fast, scalable and more cost-effective LLM development and deployment for its customers. NIM microservices are integrated within the Now AI multimodal model and are available to customers that have ServiceNow’s generative AI experience, Now Assist, installed.
- Siemens — a global technology company focused on industry, infrastructure, transport and healthcare — is integrating its operational technology with NIM microservices for shop floor AI workloads. It is also building an on-premises version of its Industrial Copilot for Machine Operators using NIM.
Availability
Developers can experiment with NVIDIA microservices at ai.nvidia.com at no charge. Enterprises can deploy production-grade NIM microservices with NVIDIA AI Enterprise running on NVIDIA-Certified Systems and leading cloud platforms. Starting next month, members of the NVIDIA Developer Program will gain free access to NIM for research and testing.
Watch Huang’s COMPUTEX keynote to learn more about NVIDIA NIM.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing.
For further information, contact:
Anna Kiachian
NVIDIA Corporation
+1-650-224-9820
akiachian@nvidia.com
Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance, features, and availability of NVIDIA’s products and technologies, including NVIDIA NIM, NVIDIA CUDA, NVIDIA Triton Inference Server, NVIDIA TensorRT-LLM software, NVIDIA Developer program, NVIDIA BioNeMo, NVIDIA-Certified Systems, and NVIDIA AI Enterprise; our collaborations and partnerships with third parties and the benefits and impacts thereof; third parties using or adopting our products or technologies; every enterprise looking to add generative AI to its operations; and NVIDIA NIM helping the technology industry put generative AI in reach for every organization are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
© 2024 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, BioNeMo, CUDA, NVIDIA NIM, NVIDIA Triton Inference Server and TensorRT are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.
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