{"id":4277,"date":"2025-09-22T19:40:55","date_gmt":"2025-09-22T19:40:55","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2025\/09\/22\/nvidia-openai-announce-the-biggest-ai-infrastructure-deployment-in-history\/"},"modified":"2025-09-22T19:40:55","modified_gmt":"2025-09-22T19:40:55","slug":"nvidia-openai-announce-the-biggest-ai-infrastructure-deployment-in-history","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2025\/09\/22\/nvidia-openai-announce-the-biggest-ai-infrastructure-deployment-in-history\/","title":{"rendered":"NVIDIA, OpenAI Announce \u2018the Biggest AI Infrastructure Deployment in History\u2019"},"content":{"rendered":"
\n\t\t<\/span> <\/span> <\/span><\/span><\/p>\n

OpenAI and NVIDIA just announced a landmark AI infrastructure partnership<\/a> \u2014 an initiative that will scale OpenAI\u2019s compute with multi-gigawatt data centers powered by millions of NVIDIA GPUs.<\/p>\n

To discuss what this means for the next generation of AI development and deployment, the two companies\u2019 CEOs, and the president of OpenAI, spoke this morning with CNBC\u2019s Jon Fortt.<\/p>\n

\u201cThis is the biggest AI infrastructure project in history,\u201d said NVIDIA founder and CEO Jensen Huang in the interview. \u201cThis partnership is about building an AI infrastructure that enables AI to go from the labs into the world.\u201d<\/p>\n

Through the partnership, OpenAI will deploy at least 10 gigawatts of NVIDIA systems for OpenAI\u2019s next-generation AI infrastructure, including the NVIDIA Vera Rubin platform. NVIDIA also intends to invest up to $100 billion in OpenAI progressively as each gigawatt is deployed.<\/p>\n

\u201cThere\u2019s no partner but NVIDIA that can do this at this kind of scale, at this kind of speed,\u201d said Sam Altman, CEO of OpenAI.<\/p>\n

\"\"<\/p>\n

The million-GPU AI factories built through this agreement will help OpenAI meet the training and inference demands of its next frontier of AI models.<\/p>\n

\u201cBuilding this infrastructure is critical to everything we want to do,\u201d Altman said. \u201cThis is the fuel that we need to drive improvement, drive better models, drive revenue, drive everything.\u201d<\/p>\n

\"\"
(L to R): OpenAI President Greg Brockman, NVIDIA Founder and CEO Jensen Huang, and OpenAI CEO Sam Altman<\/figcaption><\/figure>\n

Building Million-GPU Infrastructure to Meet AI Demand<\/b><\/h2>\n

Since the launch of OpenAI\u2019s ChatGPT \u2014 which in 2022 became the fastest application in history to reach 100 million users \u2014 the company has grown its user base to more than 700 million weekly active users and delivered increasingly advanced capabilities, including support for agentic AI, AI reasoning, multimodal data and longer context windows.<\/p>\n

To support its next phase of growth, the company\u2019s AI infrastructure must scale up to meet not only training but inference demands of the most advanced models for\u00a0 agentic and reasoning AI users worldwide.<\/p>\n

\u201cThe cost per unit of intelligence will keep falling and falling and falling, and we think that\u2019s great,\u201d said Altman. \u201cBut on the other side, the frontier of AI, maximum intellectual capability, is going up and up. And that enables more and more use \u2014 and a lot of it.\u201d<\/p>\n

\"\"<\/p>\n

Without enough computational resources, Altman explained, people would have to choose between impactful use cases, for example either researching a cancer cure or offering free education.<\/p>\n

\u201cNo one wants to make that choice,\u201d he said. \u201cAnd so increasingly, as we see this, the answer is just much more capacity so that we can serve the massive need and opportunity.\u201d<\/p>\n

\"NVIDIA
In 2016, NVIDIA CEO Jensen Huang hand-delivered the first NVIDIA DGX system to OpenAI\u2019s headquarters in San Francisco.<\/figcaption><\/figure>\n

The first gigawatt of NVIDIA systems built with NVIDIA Vera Rubin GPUs will generate their first tokens<\/a> in the second half of 2026.<\/p>\n

The partnership expands on a long-standing collaboration between NVIDIA and OpenAI, which began with Huang hand-delivering the first NVIDIA DGX system to the company in 2016.<\/p>\n

\u201cThis is a billion times more computational power than that initial server,\u201d said Greg Brockman, president of OpenAI. \u201cWe\u2019re able to actually create new breakthroughs, new models\u2026to empower every individual and business because we\u2019ll be able to reach the next level of scale.\u201d<\/p>\n

Huang emphasized that though this is the start of a massive buildout of AI infrastructure around the world, it\u2019s just the beginning.<\/p>\n

\u201cWe\u2019re literally going to connect intelligence to every application, to every use case, to every device \u2014 and we\u2019re just at the beginning,\u201d Huang said. \u201cThis is the first 10 gigawatts, I assure you of that.\u201d<\/p>\n

Watch the CNBC interview<\/a>.<\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

https:\/\/blogs.nvidia.com\/blog\/openai-nvidia\/<\/p>\n","protected":false},"author":0,"featured_media":4278,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4277"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=4277"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4277\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/4278"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=4277"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=4277"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=4277"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}