It's official: NVIDIA delivered the world's fastest platform in industry-standard tests for inference on generative AI. In the latest MLPerf benchmarks, NVIDIA TensorRT-LLM—software that speeds and simplifies the complex job of inference on large language models—boosted the performance of NVIDIA Hopper architecture GPUs on the GPT-J LLM nearly 3x over their results just six months ago. The dramatic speedup demonstrates the power of NVIDIA's full-stack platform of chips, systems and software to handle the demanding requirements of running generative AI. Leading companies are using TensorRT-LLM to optimize their models. And NVIDIA NIM—a set of inference microservices that includes inferencing engines like TensorRT-LLM—makes it easier than ever for businesses to deploy NVIDIA's inference platform.

Raising the Bar in Generative AI
TensorRT-LLM running on NVIDIA H200 Tensor Core GPUs—the latest, memory-enhanced Hopper GPUs—delivered the fastest performance running inference in MLPerf's biggest test of generative AI to date. The new benchmark uses the largest version of Llama 2, a state-of-the-art large language model packing 70 billion parameters. The model is more than 10x larger than the GPT-J LLM first used in the September benchmarks. The memory-enhanced H200 GPUs, in their MLPerf debut, used TensorRT-LLM to produce up to 31,000 tokens/second, a record on MLPerf's Llama 2 benchmark. The H200 GPU results include up to 14% gains from a custom thermal solution. It's one example of innovations beyond standard air cooling that systems builders are applying to their NVIDIA MGX designs to take the performance of Hopper GPUs to new heights.

After giving a vivid GTC talk, NVIDIA's CEO Jensen Huang took on a Q&A session with many interesting ideas for debate. One of them is addressing the pressing concerns surrounding AI hallucinations and the future of Artificial General Intelligence (AGI). With a tone of confidence, Huang reassured the tech community that the phenomenon of AI hallucinations—where AI systems generate plausible yet unfounded answers—is a solvable issue. His solution emphasizes the importance of well-researched and accurate data feeding into AI systems to mitigate these occurrences. "The AI shouldn't just answer; it should do research first to determine which of the answers are the best," noted Mr. Huang as he added that for every single question, there should be a rule that makes AI research the answer. This also refers to Retrieval-Augmented Generation (RAG), where LLMs fetch data from external sources, like additional databases, for fact-checking.

Another interesting comment made by the CEO is that the pinnacle of AI evolution—Artificial General Intelligence—is just five years away. Many people working in AI are divided between the AGI timeline. While Mr. Huang predicted five years, some leading researchers like Meta's Yann LeCunn think we are far from the AGI singularity threshold and will be stuck with dog/cat-level AI systems first. AGI has long been a topic of both fascination and apprehension, with debates often revolving around its potential to exceed human intelligence and the ethical implications of such a development. Critics worry about the unpredictability and uncontrollability of AGI once it reaches a certain level of autonomy, raising questions about aligning its objectives with human values and priorities. Timeline-wise, no one knows, and everyone makes their prediction, so time will tell who was right.

Jensen Huang has been talking to media outlets following the conclusion of his keynote presentation at NVIDIA's GTC 2024 conference—an NBC TV "exclusive" interview with the Team Green boss has caused a stir in tech circles. Jim Cramer's long-running "Squawk on the Street" trade segment hosted Huang for just under five minutes—NBC's presenter labelled the latest edition of GTC the "Woodstock of AI." NVIDIA's leader reckoned that around $1 trillion of industry was in attendance at this year's event—folks turned up to witness the unveiling of "Blackwell" B200 and GB200 AI GPUs. In the interview, Huang estimated that his company had invested around $10 billion into the research and development of its latest architecture: "we had to invent some new technology to make it possible."

Industry watchdogs have seized on a major revelation—as disclosed during the televised NBC report—Huang revealed that his next-gen AI GPUs "will cost between $30,000 and $40,000 per unit." NVIDIA (and its rivals) are not known to publicly announce price ranges for AI and HPC chips—leaks from hardware partners and individuals within industry supply chains are the "usual" sources. An investment banking company has already delved into alleged Blackwell production costs—as shared by Tae Kim/firstadopter: "Raymond James estimates it will cost NVIDIA more than $6000 to make a B200 and they will price the GPU at a 50-60% premium to H100...(the bank) estimates it costs NVIDIA $3320 to make the H100, which is then sold to customers for $25,000 to $30,000." Huang's disclosure should be treated as an approximation, since his company (normally) deals with the supply of basic building blocks.

At GTC on Monday, Microsoft Corp. and NVIDIA expanded their longstanding collaboration with powerful new integrations that leverage the latest NVIDIA generative AI and Omniverse technologies across Microsoft Azure, Azure AI services, Microsoft Fabric and Microsoft 365.

"Together with NVIDIA, we are making the promise of AI real, helping to drive new benefits and productivity gains for people and organizations everywhere," said Satya Nadella, Chairman and CEO, Microsoft. "From bringing the GB200 Grace Blackwell processor to Azure, to new integrations between DGX Cloud and Microsoft Fabric, the announcements we are making today will ensure customers have the most comprehensive platforms and tools across every layer of the Copilot stack, from silicon to software, to build their own breakthrough AI capability."

"AI is transforming our daily lives - opening up a world of new opportunities," said Jensen Huang, founder and CEO of NVIDIA. "Through our collaboration with Microsoft, we're building a future that unlocks the promise of AI for customers, helping them deliver innovative solutions to the world."

NVIDIA today announced its next-generation AI supercomputer—the NVIDIA DGX SuperPOD powered by NVIDIA GB200 Grace Blackwell Superchips—for processing trillion-parameter models with constant uptime for superscale generative AI training and inference workloads.

Featuring a new, highly efficient, liquid-cooled rack-scale architecture, the new DGX SuperPOD is built with NVIDIA DGX GB200 systems and provides 11.5 exaflops of AI supercomputing at FP4 precision and 240 terabytes of fast memory—scaling to more with additional racks.

Powering a new era of computing, NVIDIA today announced that the NVIDIA Blackwell platform has arrived—enabling organizations everywhere to build and run real-time generative AI on trillion-parameter large language models at up to 25x less cost and energy consumption than its predecessor.

The Blackwell GPU architecture features six transformative technologies for accelerated computing, which will help unlock breakthroughs in data processing, engineering simulation, electronic design automation, computer-aided drug design, quantum computing and generative AI—all emerging industry opportunities for NVIDIA.

NVIDIA today announced that TSMC and Synopsys are going into production with NVIDIA's computational lithography platform to accelerate manufacturing and push the limits of physics for the next generation of advanced semiconductor chips. TSMC, the world's leading foundry, and Synopsys, the leader in silicon to systems design solutions, have integrated NVIDIA cuLitho with their software, manufacturing processes and systems to speed chip fabrication, and in the future support the latest-generation NVIDIA Blackwell architecture GPUs.

"Computational lithography is a cornerstone of chip manufacturing," said Jensen Huang, founder and CEO of NVIDIA. "Our work on cuLitho, in partnership with TSMC and Synopsys, applies accelerated computing and generative AI to open new frontiers for semiconductor scaling." NVIDIA also introduced new generative AI algorithms that enhance cuLitho, a library for GPU-accelerated computational lithography, dramatically improving the semiconductor manufacturing process over current CPU-based methods.

Jensen Huang's opening GTC 2024 keynote is scheduled to happen tomorrow afternoon (13:00 Pacific time)—many industry experts believe that the NVIDIA boss will take the stage and formally introduce his company's B100 "Blackwell" GPU architecture. An enlightened few have been treated to preview (AI and HPC) units—including Dell's CEO, Jeff Clarke—but pre-introduction leaks have not flowed out. Team Green is likely enforcing strict conditions upon a fortunate selection of trusted evaluators, within a pool of ecosystem partners and customers.

Today, a brave soul has broken that silence—tech tipster, AGF/XpeaGPU, fears repercussions from the leather-jacketed one. They revealed a handful of technical details, a day prior to Team Green's highly anticipated unveiling: "I don't want to spoil NVIDIA B100 launch tomorrow, but this thing is a monster. 2 dies on (TSMC) CoWoS-L, 8x8-Hi HBM3E stacks for 192 GB of memory." They also crystal balled an inevitable follow-up card: "one year later, B200 goes with 12-Hi stacks and will offer a beefy 288 GB. And the performance! It's... oh no Jensen is there... me run away!" Reuters has also joined in on the fun, with some predictions and insider information: "NVIDIA is unlikely to give specific pricing, but the B100 is likely to cost more than its predecessor, which sells for upwards of $20,000." Enterprise products are expected to arrive first—possibly later this year—followed by gaming variants, maybe months later.

Samsung Electronics is all set to discuss the future of AI, alongside Jensen Huang, at NVIDIA's upcoming GTC 2024 conference. South Korean insiders have leaked the company's intentions, only days before the event's March 18 kickoff time. Their recently unveiled 36 GB HBM3E 12H DRAM product is expected to be the main focus of official presentations—additionally, a new storage subscription service is marked down for a possible live introduction. An overall "Redefining AI Infrastructure" presentation could include—according to BusinessKorea—a planned launch of: "petabyte (PB)-level SSD solution, dubbed 'PBSSD,' along with a subscription service in the US market within the second quarter (of 2024) to address the era of ultra-high-capacity data."

A Samsung statement—likely sourced from leaked material—summarized this business model: "the subscription service will help reduce initial investment costs in storage infrastructure for our customers and cut down on maintenance expenses." Under agreed upon conditions, customers are not required to purchasing ultra-high-capacity SSD solutions outright: "enterprises using the service can flexibly utilize SSD storage without the need to build separate infrastructure, while simultaneously receiving various services from Samsung Electronics related to storage management, security, and upgrades." A special session—"The Value of Storage as a Service for AI/ML and Data Analysis"—is alleged to be on the company's GTC schedule.

NVIDIA's GTC 2024 AI conference will set the stage for another leap forward in AI. At the heart of this highly anticipated event: the opening keynote by Jensen Huang, NVIDIA's visionary founder and CEO, who speaks on Monday, March 18, at 1 p.m. Pacific, at the SAP Center in San Jose, California.

Planning Your GTC Experience
There are two ways to watch. Register to attend GTC in person to secure a spot for an immersive experience at the SAP Center. The center is a short walk from the San Jose Convention Center, where the rest of the conference takes place. Doors open at 11 a.m., and badge pickup starts at 10:30 a.m. The keynote will also be livestreamed at www.nvidia.com/gtc/keynote/.

During the 2024 SIEPR Economic Summit, NVIDIA CEO Jensen Huang acknowledged that the company's next-generation DGX systems, designed for AI and high-performance computing workloads, will require liquid cooling due to their immense power consumption. Huang also hinted that these new systems are set to be released in the near future. The revelation comes as no surprise, given the increasing power of GPUs needed to satisfy AI and machine learning applications. As computational requirements continue to grow, so does the need for more powerful hardware. However, with great power comes great heat generation, necessitating advanced cooling solutions to maintain optimal performance and system stability. Liquid cooling has long been a staple in high-end computing systems, offering superior thermal management compared to traditional air cooling methods.

By implementing liquid cooling in the upcoming DGX systems, NVIDIA aims to push the boundaries of performance while ensuring the hardware remains reliable and efficient. Although Huang did not provide a specific release date for the new DGX systems, his statement suggests that they are on the horizon. Whether the next generation of DGX systems uses the current NVIDIA H200 or the upcoming Blackwell B100 GPU as their primary accelerator, the performance will undoubtedly be delivered. As the AI and high-performance computing landscape continues to evolve, NVIDIA's position continues to strengthen, and liquid-cooled systems will certainly play a crucial role in shaping the future of these industries.

Nations have long invested in domestic infrastructure to advance their economies, control their own data and take advantage of technology opportunities in areas such as transportation, communications, commerce, entertainment and healthcare. AI, the most important technology of our time, is turbocharging innovation across every facet of society. It's expected to generate trillions of dollars in economic dividends and productivity gains. Countries are investing in sovereign AI to develop and harness such benefits on their own. Sovereign AI refers to a nation's capabilities to produce artificial intelligence using its own infrastructure, data, workforce and business networks.

Why Sovereign AI Is Important
The global imperative for nations to invest in sovereign AI capabilities has grown since the rise of generative AI, which is reshaping markets, challenging governance models, inspiring new industries and transforming others—from gaming to biopharma. It's also rewriting the nature of work, as people in many fields start using AI-powered "copilots." Sovereign AI encompasses both physical and data infrastructures. The latter includes sovereign foundation models, such as large language models, developed by local teams and trained on local datasets to promote inclusiveness with specific dialects, cultures and practices. For example, speech AI models can help preserve, promote and revitalize indigenous languages. And LLMs aren't just for teaching AIs human languages, but for writing software code, protecting consumers from financial fraud, teaching robots physical skills and much more.

2024 will be the year generative AI gets personal, the CEOs of NVIDIA and HP said today in a fireside chat, unveiling new laptops that can build, test and run large language models. "This is a renaissance of the personal computer," said NVIDIA founder and CEO Jensen Huang at HP Amplify, a gathering in Las Vegas of about 1,500 resellers and distributors. "The work of creators, designers and data scientists is going to be revolutionized by these new workstations."

Greater Speed and Security
"AI is the biggest thing to come to the PC in decades," said HP's Enrique Lores, in the runup to the announcement of what his company billed as "the industry's largest portfolio of AI PCs and workstations." Compared to running their AI work in the cloud, the new systems will provide increased speed and security while reducing costs and energy, Lores said in a keynote at the event. New HP ZBooks provide a portfolio of mobile AI workstations powered by a full range of NVIDIA RTX Ada Generation GPUs. Entry-level systems with the NVIDIA RTX 500 Ada Generation Laptop GPU let users run generative AI apps and tools wherever they go. High-end models pack the RTX 5000 to deliver up to 682 TOPS, so they can create and run LLMs locally, using retrieval-augmented generation (RAG) to connect to their content for results that are both personalized and private.

NVIDIA is offering a new professional certification in generative AI to enable developers to establish technical credibility in this important domain. Generative AI is revolutionizing industries worldwide, yet there's a critical skills gap and need to uplevel employees to more fully harness the technology. Available for the first time from NVIDIA, this new professional certification enables developers, career professionals, and others to validate and showcase their generative AI skills and expertise. Our new professional certification program introduces two associate-level generative AI certifications, focusing on proficiency in large language models and multimodal workflow skills.

"Generative AI has moved to center stage as governments, industries and organizations everywhere look to harness its transformative capabilities," NVIDIA founder and CEO Jensen Huang recently said. The certification will become available starting at GTC, where in-person attendees can also access recommended training to prepare for a certification exam. "Organizations in every industry need to increase their expertise in this transformative technology," said Greg Estes, VP of developer programs at NVIDIA. "Our goals are to assist in upskilling workforces, sharpen the skills of qualified professionals, and enable individuals to demonstrate their proficiency in order to gain a competitive advantage in the job market."

NVIDIA is reported to be setting up an AI-focused semi-custom chip design business unit, according to inside sources known to Reuters—it is believed that Team Green leadership is adapting to demands leveraged by key data-center customers. Many companies are seeking cheaper alternatives, or have devised their own designs (budget/war chest permitting)—NVIDIA's current range of AI GPUs are simply off-the-shelf solutions. OpenAI has generated the most industry noise—their alleged early 2024 fund-raising pursuits have attracted plenty of speculative/kind-of-serious interest from notable semiconductor personalities.

Team Green is seemingly reacting to emerging market trends—Jensen Huang (CEO, president and co-founder) has hinted that NVIDIA custom chip designing services are on the cusp. Stephen Nellis—a Reuters reporter specializing in tech industry developments—has highlighted select NVIDIA boss quotes from an incoming interview piece: "We're always open to do that. Usually, the customization, after some discussion, could fall into system reconfigurations or recompositions of systems." The Team Green chief teased that his engineering team is prepared to take on the challenge meeting exact requests: "But if it's not possible to do that, we're more than happy to do a custom chip. And the benefit to the customer, as you can imagine, is really quite terrific. It allows them to extend our architecture with their know-how and their proprietary information." The rumored NVIDIA semi-custom chip design business unit could be introduced in an official capacity at next month's GTC 2024 Conference.

NVIDIA (NASDAQ: NVDA) today reported revenue for the fourth quarter ended January 28, 2024, of $22.1 billion, up 22% from the previous quarter and up 265% from a year ago. For the quarter, GAAP earnings per diluted share was $4.93, up 33% from the previous quarter and up 765% from a year ago. Non-GAAP earnings per diluted share was $5.16, up 28% from the previous quarter and up 486% from a year ago.

For fiscal 2024, revenue was up 126% to $60.9 billion. GAAP earnings per diluted share was $11.93, up 586% from a year ago. Non-GAAP earnings per diluted share was $12.96, up 288% from a year ago. "Accelerated computing and generative AI have hit the tipping point. Demand is surging worldwide across companies, industries and nations," said Jensen Huang, founder and CEO of NVIDIA.

NVIDIA today announced it will host its flagship GTC 2024 conference at the San Jose Convention Center from March 18-21. More than 300,000 people are expected to register to attend in person or virtually. NVIDIA founder and CEO Jensen Huang will deliver the keynote from the SAP Center on Monday, March 18, at 1 p.m. Pacific time. It will be livestreamed and available on demand. Registration is not required to view the keynote online. Since Huang first highlighted machine learning in his 2014 GTC keynote, NVIDIA has been at the forefront of the AI revolution. The company's platforms have played a crucial role in enabling AI across numerous domains including large language models, biology, cybersecurity, data center and cloud computing, conversational AI, networking, physics, robotics, and quantum, scientific and edge computing.

The event's 900 sessions and over 300 exhibitors will showcase how organizations are deploying NVIDIA platforms to achieve remarkable breakthroughs across industries, including aerospace, agriculture, automotive and transportation, cloud services, financial services, healthcare and life sciences, manufacturing, retail and telecommunications. "Generative AI has moved to center stage as governments, industries and organizations everywhere look to harness its transformative capabilities," Huang said. "GTC has become the world's most important AI conference because the entire ecosystem is there to share knowledge and advance the state of the art. Come join us."

Every country needs to own the production of their own intelligence, NVIDIA founder and CEO Jensen Huang told attendees Monday at the World Governments Summit in Dubai. Huang, who spoke as part of a fireside chat with the UAE's Minister of AI, His Excellency Omar Al Olama, described sovereign AI—which emphasizes a country's ownership over its data and the intelligence it produces—as an enormous opportunity for the world's leaders. "It codifies your culture, your society's intelligence, your common sense, your history - you own your own data," Huang told Al Olama during their conversation, a highlight of an event attended by more than 4,000 delegates from 150 countries.

"We completely subscribe to that vision," Al Olama said. "That's why the UAE is moving aggressively on creating large language models and mobilizing compute." Huang's appearance in the UAE comes as the Gulf State is moving rapidly to transform itself from an energy powerhouse into a global information technology hub. Dubai is the latest stop for Huang in a global tour that has included meetings with leaders in Canada, France, India, Japan, Malaysia, Singapore and Vietnam over the past six months. The Middle East is poised to reap significant benefits from AI, with PwC projecting a $320 billion boost to the region's economy by 2030.

This week, Cisco and NVIDIA have announced plans to deliver AI infrastructure solutions for the data center that are easy to deploy and manage, enabling the massive computing power that enterprises need to succeed in the AI era. "AI is fundamentally changing how we work and live, and history has shown that a shift of this magnitude is going to require enterprises to rethink and re-architect their infrastructures," said Chuck Robbins, Chair and CEO, Cisco. "Strengthening our great partnership with NVIDIA is going to arm enterprises with the technology and the expertise they need to build, deploy, manage, and secure AI solutions at scale." Jensen Huang, founder and CEO of NVIDIA said: "Companies everywhere are racing to transform their businesses with generative AI. Working closely with Cisco, we're making it easier than ever for enterprises to obtain the infrastructure they need to benefit from AI, the most powerful technology force of our lifetime."

A Powerful Partnership
Cisco, with its industry-leading expertise in Ethernet networking and extensive partner ecosystem, together with NVIDIA, the inventor of the GPU that fueled the AI boom, share a vision and commitment to help customers navigate the transitions for AI with highly secure Ethernet-based infrastructure. Cisco and NVIDIA have offered a broad range of integrated product solutions over the past several years across Webex collaboration devices and data center compute environments to enable hybrid workforces with flexible workspaces, AI-powered meetings and virtual desktop infrastructure.

AI is reshaping industries, society and the "very fabric of innovation"—and Canada is poised to play a key role in this global transformation, said NVIDIA founder and CEO Jensen Huang during a fireside chat with leaders from across Canada's thriving AI ecosystem. "Canada, as you know, even though you're so humble, you might not acknowledge it, is the epicenter of the invention of modern AI," Huang told an audience of more than 400 from academia, industry and government gathered Thursday in Toronto.

In a pivotal development, Canada's Industry Minister François-Philippe Champagne shared Friday on X, formerly known as Twitter, that Canada has signed a letter of intent with NVIDIA. Nations including Canada, France, India and Japan are discussing the importance of investing in "sovereign AI capabilities," Huang said in an interview with Bloomberg Television in Canada. Such efforts promise to enhance domestic computing capabilities, turbocharging local economies and unlocking local talent. "Their natural resource, data, should be refined and produced for their country. The recognition of sovereign AI capabilities is global," Huang told Bloomberg.

In a major stride toward building a shared national research infrastructure, the U.S. National Science Foundation has launched the National Artificial Intelligence Research Resource pilot program with significant support from NVIDIA. The initiative aims to broaden access to the tools needed to power responsible AI discovery and innovation. It was announced Wednesday in partnership with 10 other federal agencies as well as private-sector, nonprofit and philanthropic organizations. "The breadth of partners that have come together for this pilot underscores the urgency of developing a National AI Research Resource for the future of AI in America," said NSF Director Sethuraman Panchanathan. "By investing in AI research through the NAIRR pilot, the United States unleashes discovery and impact and bolsters its global competitiveness."

NVIDIA's commitment of $30 million in technology contributions over two years is a key factor in enlarging the scale of the pilot, fueling the potential for broader achievements and accelerating the momentum toward full-scale implementation. "The NAIRR is a vision of a national research infrastructure that will provide access to computing, data, models and software to empower researchers and communities," said Katie Antypas, director of the Office of Advanced Cyberinfrastructure at the NSF. "Our primary goals for the NAIRR pilot are to support fundamental AI research and domain-specific research applying AI, reach broader communities, particularly those currently unable to participate in the AI innovation ecosystem, and refine the design for the future full NAIRR," Antypas added.

"This year, every industry will become a technology industry," NVIDIA founder and CEO Jensen Huang told attendees last Wednesday during the annual J.P. Morgan Healthcare Conference. "You can now recognize and learn the language of almost anything with structure, and you can translate it to anything with structure—so text-protein, protein-text," Huang said in a fireside chat with Martin Chavez, partner and vice chairman of global investment firm Sixth Street Partners and board chair of Recursion, a biopharmaceutical company. "This is the generative AI revolution."

The conversation, which took place at the historic San Francisco Mint, followed a presentation at the J.P. Morgan conference Monday by Kimberly Powell, NVIDIA's VP of healthcare. In her talk, Powell announced that Recursion is the first hosting partner to offer a foundation model through the NVIDIA BioNeMo cloud service, which is advancing into beta this month. She also said that Amgen, one of the first companies to employ BioNeMo, plans to advance drug discovery with generative AI and NVIDIA DGX SuperPOD—and that BioNeMo is used by a growing number of techbio companies, pharmas, AI software vendors and systems integrators. Among them are Deloitte, Innophore, Insilico Medicine, OneAngstrom, Recursion and Terray Therapeutics.

NVIDIA's presence at CES 2024 has focused mainly on the introduction of new GeForce RTX 40-series SUPER graphics cards—TPU spent some quality time over at Team Green's Las Vegas Convention Center booth where a plethora of the latest Ada Lovelace gaming products were on display. To coincide with this event, interested punters on social media or in-person can enter a competition—NVIDIA is giving away two Founders Edition GeForce RTX 4080 SUPER graphics cards (valued at $999 per unit) with something extra courtesy of the technology company's esteemed CEO.

The competition page states: "We have two Founders Edition GeForce RTX 4080 SUPER graphics cards signed by NVIDIA's founder and CEO, Jensen Huang, that we're giving away, one for our social channels and one for CES attendees. The first chance to win is by following our GeForce social channels on X, Facebook, Instagram, TikTok, and by looking for key prompts and instructions (please check the complete set of rules for the giveaway here)."

The United States is softening restrictions on the significant GPU maker NVIDIA, selling artificial intelligence chips to China. While still limiting advanced chip exports deemed strategically threatening, Commerce Secretary Gina Raimondo clarified this week that NVIDIA could supply some AI processors to Chinese commercial companies. Previously, Raimondo had sharply criticized NVIDIA for attempting to sidestep regulations on selling powerful GPUs abroad. Her comments followed rumors that NVIDIA tweaked chip designs to avoid newly imposed export controls narrowly. However, after discussions between Raimondo and NVIDIA CEO Jensen Huang, the Commerce Department says NVIDIA and other US firms will be permitted to export AI chips to China for general commercial use cases. Exports are still banned on the very highest-end GPUs that could enable China to train advanced AI models rivaling American developments.

Raimondo said NVIDIA will collaborate with the US to comply with the export rules. Huang reaffirmed the company's commitment to adherence. The clarification may ease pressures on NVIDIA, as China accounts for up to 25% of its revenue. While optimistic about recent Chinese approvals for US joint ventures, Raimondo noted frustrations linger around technology controls integral to national security. The nuanced recalibration of restrictions illustrates the balances the administration must strike between economic and security interests. As one of the first big US technology exporters impacted by tightened restrictions, NVIDIA's ability to still partly supply the valuable Chinese chip market points to a selective enforcement approach from regulators in the future.

Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), and NVIDIA (NASDAQ: NVDA) today announced an expansion of their strategic collaboration to deliver the most-advanced infrastructure, software and services to power customers' generative artificial intelligence (AI) innovations. The companies will bring together the best of NVIDIA and AWS technologies—from NVIDIA's newest multi-node systems featuring next-generation GPUs, CPUs and AI software, to AWS Nitro System advanced virtualization and security, Elastic Fabric Adapter (EFA) interconnect, and UltraCluster scalability—that are ideal for training foundation models and building generative AI applications.

The expanded collaboration builds on a longstanding relationship that has fueled the generative AI era by offering early machine learning (ML) pioneers the compute performance required to advance the state-of-the-art in these technologies.