Here’s what you need to know about the AI and processor giant’s latest product and company news.
When it comes to innovation and the technology to drive it, few companies today rival Nvidia. The company has leveraged its GPU expertise to become a dominant player in the AI market. Nvidia’s GPU pedigree dates back decades to high-powered processors originally built for gaming systems. Those GPUs have evolved to drive scientific simulations, data analysis, machine learning and other high-performance computing tasks.
Today, Nvidia’s processors and AI platform are pushing the boundaries of business transformation across industries from healthcare and finance to transportation and manufacturing. And its list of partners reads like a who’s who of technology giants.
Follow this page for the latest news, analysis and features about Nvidia and its impact on enterprise innovation.
Nvidia contributes Blackwell rack design to Open Compute Project
October 15, 2024: Nvidia contributed to the Open Compute Project its Blackwell GB200 NVL72 electro-mechanical designs – including the rack architecture, compute and switch tray mechanicals, liquid cooling and thermal environment specifications, and Nvidia NVLink cable cartridge volumetrics –.
As global AI energy usage mounts, Nvidia claims efficiency gains of up to 100,000X
October 08, 2024: As concerns over AI energy consumption ratchet up, chip maker Nvidia is defending what it calls a steadfast commitment to sustainability. The company reports that its GPUs have experienced a 2,000X reduction in energy use over the last 10 years in training and a 100,000X energy reduction over that same time in generating tokens.
Accenture forms new Nvidia business group focused on agentic AI adoption
October 4, 2024: Accenture and Nvidia announced an expanded partnership focused on helping customers rapidly scale AI adoption. Accenture said the new group will use Accenture’s AI Refinery platform — built on the Nvidia AI stack, including Nvidia AI Foundry, Nvidia AI Enterprise, and Nvidia Omniverse — to help clients create a foundation for use of agentic AI.
IBM expands Nvidia GPU options for cloud customers
October 1, 2024: IBM expanded access to Nvidia GPUs on IBM Cloud to help enterprise customers advance their AI implementations, including large language model (LLM) training. IBM Cloud users can now access Nvidia H100 Tensor Core GPU instances in virtual private cloud and managed Red Hat OpenShift environments.
Oracle to offer 131,072 Nvidia Blackwell GPUs via its cloud
September 12, 2024: Oracle started taking pre-orders for 131,072 Nvidia Blackwell GPUs in the cloud via its Oracle Cloud Infrastructure (OCI) Supercluster to aid large language model (LLM) training and other use cases, the company announced at the CloudWorld 2024 conference. The launch of an offering that provides these many Blackwell GPUs, also known as Grace Blackwell (GB) 200, is significant as enterprises globally are faced with the unavailability of high-bandwidth memory (HBM) — a key component used in making GPUs.
Why is the DOJ investigating Nvidia?
September 11, 2024: After a stock sell-off following its quarterly earnings report, Nvidia’s pain was aggravated by news that the Department of Justice is escalating its investigation into the company for anticompetitive practices. According to a Bloomberg report, the DOJ sent a subpoena to Nvidia as part of a probe into alleged antitrust practices.
Cisco, HPE, Dell announce support for Nvidia’s pretrained AI workflows
September 4, 2024: Cisco, HPE, and Dell are using Nvidia’s new AI microservices blueprints to help enterprises streamline the deployment of generative AI applications. Nvidia’s announced its NIM Agent Blueprints, a catalogue of pretrained, customizable AI workflows that are designed to provide a jump-start for developers creating AI applications. NIM Agent Blueprints target a number of use cases, including customer service, virtual screening for computer-aided drug discovery, and a multimodal PDF data extraction workflow for retrieval-augmented generation (RAG) that can ingest vast quantities of data.
Nvidia reportedly trained AI models on YouTube data
August 4, 2024: Nvidia scraped huge amounts of data from YouTube to train its AI models, even though neither Youtube nor individual YouTube channels approved the move, according to leaked documents. Among other things, Nvidia reportedly used the YouTube data to train its deep learning model Cosmos, an algorithm for automated driving, a human-like AI avatar, and Omniverse, a tool for building 3D worlds.
Can Intel’s new chips compete with Nvidia in the AI universe?
June 9, 2024: Intel is aiming its next-generation X86 processors at AI tasks, even though the chips won’t actually run AI workloads themselves.mAt Computex, Intel announced its Xeon 6 processor line, talking up what it calls Efficient-cores (E-cores) that it said will deliver up to 4.2 times the performance of Xeon 5 processors. The first Xeon 6 CPU is the Sierra Forest version (6700 series) a more performance-oriented line, Granite Rapids with Performance cores (P-cores or 6900 series), will be released next quarter.
Everyone but Nvidia joins forces for new AI interconnect
May 30, 2024: A clear sign of Nvidia’s dominance is when Intel and AMD link arms to deliver a competing product. That’s what happened when AMD and Intel – along with Broadcom, Cisco, Google, Hewlett Packard Enterprise, Meta and Microsoft – formed the Ultra Accelerator Link (UALink) Promoter Group to develop high-speed interconnections between AI processors.
Nvidia to build supercomputer for federal AI research
May 15, 2024: The U.S. government will use an Nvidia DGX SuperPOD to provide researchers and developers access to much more computing power than they have had in the past to produce generative AI advances in areas such as climate science, healthcare and cybersecurity.
Nvidia, Google Cloud team to boost AI startups
April 11, 2024: Alphabet’s Google Cloud unveiled a slew of new products and services at Google Cloud Next 2024, among them a program to help startups and small businesses build generative AI applications and services. The initiative brings together the Nvidia Inception program for startups and the Google for Startups Cloud Program.
Nvidia GTC 2024 wrap-up: Blackwell not the only big news
March 29, 2024: Nvidia’s GDC is in our rearview mirror, and there was plenty of news beyond the major announcement of the Blackwell architecture and the massive new DGX systems powered by it. Here’s a rundown of some of the announcements you might have missed.
Nvidia expands partnership with hyperscalers to boost AI training and development
March 19, 2024: Nvidia extended its existing partnerships with hyperscalers Amazon Web Services (AWS), Google Cloud Platform, Microsoft Azure, and Oracle Cloud Infrastructure, to make available its latest GPUs and foundational large language models and to integrate its software across their platforms.
Nvidia launches Blackwell GPU architecture
March 18, 2024: Nvidia kicked off its GTC 2024 conference with the formal launch of Blackwell, its next-generation GPU architecture due at the end of the year. Blackwell uses a chiplet design, to a point. Whereas AMD’s designs have several chiplets, Blackwell has two very large dies that are tied together as one GPU with a high-speed interlink that operates at 10 terabytes per second, according to Ian Buck, vice president of HPC at Nvidia.
Cisco, Nvidia target secure AI with expanded partnership
February 9, 2024: Cisco and Nvidia expanded their partnership to offer integrated software and networking hardware that promises to help customers more easily spin up infrastructure to support AI applications. The agreement deepens both companies’ strategy to expand the role of Ethernet networking for AI workloads in the enterprise. It also gives both companies access to each other’s sales and support systems.
Nvidia and Equinix partner for AI data center infrastructure
January 9, 2024: Nvidia partnered with data center giant Equinix to offer what the vendors are calling Equinix Private AI with Nvidia DGX, a turnkey solution for companies that are looking to get into the generative AI game but lack the data center infrastructure and expertise to do it.
