On this day in 2006, AMD confirmed its acquisition of graphics chip firm ATI. AMD stumped up a cash and stock deal worth a total of $5.4B for the Canadian PC graphics innovators. With 20/20 vision now 20 years on, we can see the deal helped AMD prosper on three fronts: continuation and innovation of Radeon GPUs, the rise of the APU, and AMD’s dominance in the console business. That’s not all, of course, and it is also interesting to recall that AMD approached Nvidia before it bought ATI.

AMD CEO Hector Ruiz and ATI CEO Dave Orton appeared together in New York on the morning of July 24, 2006, to publicly announce the deal. Ruiz told the press that the deal, unanimously approved by the directors of both companies, would "reinvent our industry." The AMD CEO went on, “We believe AMD and ATI will drive growth and innovation for the entire industry, enabling our partners to create differentiated solutions and empowering our customers to choose what is best for them.” Orton added that “Joining with AMD will enable us to innovate aggressively on the PC platform.”

In the next couple of years, the ATI graphics brand slowly melted away. For example, the ATI R600 (Terascale 1, unified shader architecture) GPU, which was in development at the time of the acquisition, would become the Radeon HD 2900 series under AMD branding. As a transition product, some HD 2900 XT boxes would still carry ATI packaging and branding. Taking the cooling solution off an AMD graphics card, you might still see an ATI GPU under the thermal paste, all the way up to around 2010. In 2011, Tom’s Hardware published its 25 Years Of Graphics History: A Farewell To ATI, In Pictures, which is a must-read for fans of the era.

While graphics card development rolled on in a tit-for-tat battle with Nvidia, AMD’s next fortuitous chunk of synergy came from integrating its Radeon IP alongside its CPU cores to create APUs. It started this journey with the AMD Fusion line in 2011. Nowadays we have APUs that have taken this vision far further, with the Ryzen AI Max / Max+ (Strix Halo and Gorgon Halo) series. The integrated graphics on these processors pack up to 40 RDNA 3.5 Compute Units and can go toe-to-toe with desktop graphics like the RTX 4060/4070, depending on workload. They also benefit from unified memory, allowing users to configure oodles of VRAM, if they have it spare.

As the Radeon developers forged ahead moving from the GCN to RDNA graphics architecture era, AMD saw an opportunity in the console space. From the early to mid 2010s, AMD made inroads into APU development that meant the processors became attractive solutions for console developers. It still holds pretty tightly to that market today, which has spilled over to handhelds. However, Intel looks far more serious in this market now, with Panther Lake and B390 iGPUs. Moreover, Nvidia could surely make a dent on consoles with Arm plus GeForce semi-custom SoCs if it wasn’t living it up in the lucrative AI market.

Red and green would never be seen

Before the AMD and ATI deal was inked, reports indicated there were chances of a similar merger involving AMD and Nvidia. Our 2012 report on this ‘missed opportunity’ suggests Jensen Huang was being quite difficult during the negotiations. Apparently the man in the leather jacket insisted that he become chief executive of the combined company. That made Hector Ruiz pretty cool on the prospect, so AMD’s attention was diverted towards ATI.

Nvidia CEO Jensen Huang thinks that American companies should be allowed to use Chinese AI models, even as Washington is trying to ban them. When Axios co-founder Mike Allen asked Huang in an interview if Americans companies should be allowed to use Chinese AI models, Huang responded with “absolutely.” The answer comes right after Chinese firm Moonshot AI released a 2.8T open-weight model called Kimi K3, which — although it isn’t as powerful as frontier models like Fable 5 — is comparable to GPT 5.5 and Claude Opus 4.8 while costing just a third of these models.

One of the biggest concerns of U.S. leaders have is that these AI models might come with vulnerabilities that the Chinese government can use to attack American interests, but Huang said that this is an incorrect assumption. “There is a misconception that somehow there are backdoors that are somehow connected to China in some way,” said the Nvidia chief. “You download the models, you can fine-tune it, you can enhance it, you can guardrail it as you desire.”

Huang shares the same sentiments about American AI models. Just last month, the U.S. enforced an export restriction on Anthropic’s Mythos and Fable 5, citing security threats — although access was eventually restored after its developer placed a filter to block these tools from identifying software vulnerabilities. OpenAI’s ChatGPT-5.6 received the same treatment, and Washington warned the firm that it should not release its latest model without getting the green light from the government. Huant argues that, instead of restricting access to these powerful models at launch, AI firms should make their models available to all and make them more secure through rapid testing and fixes.

But even as he advocated the need for everyone to have access to closed models, Jensen also noted that various industries, such as the sciences and cybersecurity, need open models as well. He claims that these models make AI more secure, as other people can inspect them to look for weaknesses and fix them as required.

“If everything just becomes one single model, one single point of attack, one single source of failure, I think the world is much, much more vulnerable,” Huang said.

As for the market’s negative reaction every time cheaper, open-weight models become available, the Nvidia CEO says that investors misunderstand their impact. Huang said that this happened when DeepSeek arrived for the first time, and it’s happening again with the arrival of Kimi. He says that these open models, which cost less to run, will encourage more people to use AI. So instead of cutting data center demand, these cheaper, more efficient models are actually good for the industry in general because they will drive demand. (And with higher demand, there’s more incentive to build data centers and buy AI GPUs, which is ultimately good for Nvidia.)

‘The Jensen Jacket: Jensen Huang's Tom Ford Leather Jacket’ achieved a hammer price of $960,000 this weekend. High-end auctioneer Sotheby’s listed the leather garment, which was claimed to have been worn at least once by the Nvidia CEO, with a far lower price estimate of $40,000 to $60,000. Happily, the bountiful proceeds of the auction are going to charity.

Bidders could be quite confident that this Tom Ford jacket was genuinely worn by Jensen Huang at one or more landmark product launches, thanks to the work of the PSA [Professional Sports Authenticator]. Specifically, PSA photomatched this jacket and its unique leather wrinkles to the Hon Hai (Foxconn) Tech Day in Taipei on October 18, 2023, where Huang wore it on stage and met with other execs. Various close-up photos in the sales catalog showed telltale signs that this was/is the real deal. Separately, a signature on the garment was authenticated by James Spence Authentication.

The near $1M hammer price achieved is many multiples of the estimate. In our earlier reporting on the sale, we guessed this would happen for a number of reasons. Firstly, we thought Sotheby’s ‘low’ estimate was intentional to draw in the crowds and stoke excitement. Secondly, we mustn’t neglect the importance of the not-so-secret ingredient - Jensanity. And, right now, the AI boom with Nvidia at its center is still growing apace.

You can buy a brand new Tom Ford SS2023 menswear collection jacket, like the one shown, without any infusion of genuine Jensanity, for around $9,000. However, we can’t begrudge the success of this auction as the proceeds are earmarked for charity. The Sotheby’s page says that the auction was organized by Long Journey Ventures to benefit the Edge Institute, a non-profit that convenes people working at the frontiers of tech, science, culture, and society in pop-up villages (Edge Cities) to live together and experiment towards a brighter future. Fellowships, grants, and residencies for the next generation of young builders will be funded by this bumper lump of cash.

One of Jensen Huang’s used leather jackets is up for auction, posted with an estimate of $40,000 to $60,000. Sotheby’s, better known as a purveyor of blockbuster fine art and historic artifacts, is auctioning this item of worn clothing. The storied auction house asserts this is a genuine article, as worn by the Nvidia CEO at an event in Taipei in 2023. It has also made sure the signature within the garment has been professionally authenticated. Having watched a few tech memorabilia auctions lately, I’d say the official estimate is on the low side.

Sotheby’s auction is titled ‘The Jensen Jacket: Jensen Huang's Tom Ford Leather Jacket.’ Its catalog notes that this signature black leather jacket has been Huang’s standard attire for more than a decade and has become “associated with some of the most consequential moments in modern technology.” This jacket, or one like it, has been on stage helping to define the rise of artificial intelligence. It may also have been worn by the Nvidia CEO visiting a humble street food vendor in a Taiwan night market.

So, it is important to understand that this is one of many jackets Huang has sported during keynotes, announcements, and special events over the years. Like any good auction house, Sotheby's has thus certified the provenance of this particular garment.

“The Jacket has been photomatched by PSA [Professional Sports Authenticator] to Jensen Huang, co-founder and chief executive officer of Nvidia Corp., during the Hon Hai [Foxconn] Tech Day in Taipei on October 18, 2023,” writes Sotheby’s in its auction catalog. A very specific array of creases and deformities in the right-breast pocket flap appears to confirm that this jacket was worn by the Nvidia CEO at the Hon Hai [Foxconn] Tech Day in Taipei in October 2023. Sotheby’s also states that “The signature has been authenticated by James Spence Authentication.”

Any readers interested in grabbing this jacket will likely be interested in the condition of the garment. There are a few pictures on the catalog page, including a close-up, which was used to ‘photomatch’ this particular 2023 Tom Ford-made sample. As a Sotheby’s account holder, I also read the condition report, which begins with the assertion that “The Jacket and signature are in pristine condition.” But there follows a lot of legal jargon which can be summed up as – the actual condition and appearance of the jacket might not be perfect, nor look exactly like the photographic representations of it.

If you do splash your cash on this old jacket, you should be pleased to know that your hard-earned money will be going to charity. Sotheby’s says that the sale was organized by Long Journey Ventures to benefit the Edge Institute, described as “a non-profit that convenes people working at the frontiers of tech, science, culture, and society in pop-up villages (Edge Cities) to live together and experiment towards a brighter future.”

A low estimate to attract bidders?

Does the $40,000 to $60,000 estimate take into account the jacket's Jensanity factor, or AI inflation? Also, we are in an AI boom right now, with skyrocketing prices and valuations, yet people might have spent more than the top estimate for a mere NFT of this jacket a few years ago.

On a cautious note, though, we aren’t sure how many of these jackets the Nvidia CEO has in his wardrobe. And if there were another 10 or 20 that may someday be released for sale, then the expected price could slide dramatically.

A brand new Tom Ford SS2023 menswear collection jacket, without a sprinkle of genuine Jensanity, costs around $9,000. In that context, Sotheby’s estimate puts only a modest premium on this verified genuine Jensen Huang-worn and signed artifact.

When not being spotted at night markets or meeting crowds of adoring fans, the hardware industry’s biggest celebrity, Nvidia CEO Jensen Huang, spent most of his time at Computex this week making the case that computing as we know it is collapsing into one repeatable pattern built for AI agents; a blueprint that now runs across the cloud, the PC, the car, and the robot.

"There's a new computing pattern," the Nvidia CEO told reporters at a press gaggle the day after his GTC Taipei keynote, describing an agent architecture he calls a harness that orchestrates reasoning, memory, and tool use the same way whether it sits in a data center or a laptop.

He tied that claim to every product Nvidia detailed at the show, from the Vera data-center CPU now in full production to RTX Spark, its first Windows PC platform, shipping in laptops this fall.

One pattern, every machine

Huang told the room that he repeats the same keynote structure on purpose. "Every time I give you a keynote, it's like Top Gun 17, and it's exactly the same architecture," he said, "because I want you to know that the future of computing is this." The pattern begins with training and inference in the cloud and pushes outward to everything else: "Every edge device will become autonomous. Every edge device will have agentic systems."

He ran that blueprint through self-driving cars, humanoid robots, Nokia base stations, and imaging satellites, casting each as the same agent profile on different hardware. Curiously, the self-driving car got quite a bit of airtime, with Huang describing Nvidia's Alpamayo driving stack as a system that reasons in language rather than reacting to images, one that could read a "skill file" and watch a tutorial video to operate unfamiliar machinery the way a person would. "That's how autonomous vehicles are going to work in the future," he said. "It's essentially that agentic computing pattern with a physical AI model."

A CPU that generates tokens, not cores

Vera, on the data center side, is an 88-core Arm processor that Nvidia is now in full production with, pitching it as a chip built for agents rather than human users. "We built Vera for agents to use," Huang said. "Until six months ago, there were no agents, so that's the definition of a $0 billion market."

A hyperscale CPU piles on cores because humans lease them by the hundred, where an agent, Huang argued, "doesn't want to rent the CPU core, the agent wants to generate tokens." That pushed Nvidia toward single-thread speed and memory bandwidth over core count, and Huang claimed Vera offers the largest step up in single-threaded performance he has seen "in 25 years." His reasoning ties back to latency: "Humans are more patient than agents. Agents, they're working at nanosecond scale, not second scale."

Nvidia claims 1.8 times faster task completion than x86 and a 1.5 times instructions-per-clock gain over its Grace predecessor, with a 256-chip liquid-cooled Vera rack it says reaches six times the throughput of a conventional CPU rack. The chip ships on the back of nearly 2.5 million Grace units sold, and Anthropic, OpenAI, xAI, ByteDance, CoreWeave, and Oracle are named as early customers. CFO Colette Kress told investors on Nvidia's latest earnings call that the company sees "nearly $20 billion in total CPU revenue this year".

Phoronix's first public Vera benchmarks in May measured it roughly 10% ahead of AMD's 64-core EPYC 9575F and about 55% ahead of Intel's 128-core Xeon 6980P across selected Linux workloads. Nvidia ran those tests on pre-production silicon at its own headquarters, limited them to workloads it considers relevant, and, by Phoronix's account, switched off CPU power and frequency monitoring for the session.

Reinventing the PC after 40 years

As for RTX Spark, Huang says that it’s the first real rethink of the PC in four decades. "We have an opportunity after 40 years to go reinvent it for the age of AI," he said, predicting the machine shifts "from your PC being a tool to now really your PC being your system." He pushed even further: "Your laptop is going to be your R2-D2."

The top RTX Spark part, internally N1X, pairs a 20-core Arm CPU built by MediaTek (10 Cortex-X925 performance cores and 10 Cortex-A725 efficiency cores) with a Blackwell GPU carrying 6,144 CUDA cores, up to 128GB of LPDDR5X unified memory, and a 600 GB/s NVLink-C2C link, all on TSMC's 3nm node. Huang justified these specs with the same impatience he applied to Vera, arguing that an agent driving the machine won’t wait, so the software it touches, from Adobe to Blender, "cannot be slow."

The platform is launching in a market that Qualcomm had effectively dominated until its Windows on Arm exclusivity with Microsoft lapsed. Fall 2026 laptops are confirmed from Microsoft, Dell, HP, ASUS, Lenovo, and MSI, with Acer and Gigabyte to follow, and Nvidia says anti-cheat engines, including Easy Anti-Cheat and Denuvo, run natively on the chip. Asked why Nvidia would enter a low-margin business it has steered clear of for years, Huang said, "We don't really have to choose. The real question is, can we make a contribution?"

Vera's 88 cores are Nvidia's own custom Olympus design, its first ground-up server core since the Denver and Carmel projects, while RTX Spark's 20 cores are Arm's off-the-shelf Cortex reference designs licensed through MediaTek, one of them already a generation old. Huang's "same pattern everywhere" runs, at the silicon level, on two different CPUs.

When asked whether the Olympus cores would come to Windows PCs, Huang declined to commit. "Our preference is to use off-the-shelf cores whenever we can, because Arm also builds good cores," he said, adding that Olympus was pushed toward single-thread speed in a way standard many-core Arm parts weren’t: "We wanted to push single-threaded performance as far as we could push it." The first PC chip using Nvidia's own cores isn’t expected until 2028. Meanwhile, Morgan Stanley estimates Vera at around $5,000 per socket inside a vertically integrated rack.

What about memory?

DRAM contract prices have climbed sharply through 2026 as makers divert wafers to high-bandwidth memory, and Nvidia remains short of supply even as it locks in capacity, by Huang's own account: "We have enough supply for very robust growth. However, we are supply constrained."

"One of the best ways to improve memory use is to use extremely, extremely low precision," Huang said, pointing to NVFP4, Nvidia's 4-bit floating-point format that scales between four, eight, 16, and 32 bits and roughly doubles the parameters that fit in a given memory pool, the trick that lets RTX Spark hold larger models in its 128GB. He paired it with neural texture compression that cuts game texture memory by up to eight times in Nvidia's demos. At SK hynix's booth during the show, Huang signed an HBM4E wafer with the words "Please Make More."

Nvidia CEO Jensen Huang called on Super Micro Computer to strengthen its export compliance controls after arriving in Taipei on Saturday, months after U.S. federal prosecutors charged the server maker's co-founder and two others with conspiring to smuggle approximately $2.5 billion worth of Nvidia-equipped servers to China through shell companies in Southeast Asia.

Huang told reporters at Songshan Airport that Nvidia insists its partners follow U.S. trade rules. "We insist our partners are compliant. We hope that they will enhance and improve their regulation compliance and prevent that from happening in the future," Huang said in an address to the media.

Huang's comments came days after Taiwan launched its first formal crackdown on illicit AI hardware exports. The Keelung District Prosecutors' Office announced earlier this week that three suspects had submitted fraudulent shipping declarations to export Super Micro servers containing Nvidia AI chips to China, Hong Kong, and Macau.

The Taiwan case is separate from, but closely related to, the much larger U.S. federal prosecution unsealed in March. That indictment charged Supermicro co-founder Yih-Shyan "Wally" Liaw and two others with conspiring to smuggle approximately $2.5 billion worth of Nvidia-equipped servers to China through shell companies in Southeast Asia. Liaw has pleaded not guilty, and Supermicro has said it’s not named as a defendant and is cooperating with the investigation.

In the same press scrum at Songshan Airport, Huang confirmed that China is included in the $200 billion addressable market he projected for Nvidia's upcoming Vera CPU during the company's earnings call on May 20th. "H200 has been licensed to ship to China. It would be terrific to be able to serve that market. The Chinese market is very important. It's very large, of course," Huang told reporters, according to Reuters.

Despite the licensing approval, not a single H200 has been delivered to a Chinese customer. While roughly 10 Chinese firms have been cleared to purchase the chip, shipments haven’t started, and President Trump's talks with Chinese President Xi Jinping in Beijing earlier this month produced no breakthrough on Nvidia chip sales.

Huang is in Taipei ahead of Nvidia's GTC Taipei event and his Computex keynote on June 1st, where he’s expected to explore the Vera Rubin platform's software stack. He described the platform as "the largest product launch, probably in the history of Taiwan," noting that each Vera Rubin NVL72 system contains nearly 2 million parts and involves around 150 Taiwanese ecosystem partners.

Nvidia CEO Jensen Huang served as a guest speaker at Stanford’s CS 153 Frontier Systems course and discussed the hardware that powers AI systems today. One of the topics covered in the YouTube session is his stance on granting “adversarial countries” access to Nvidia chips. It’s widely known that the Nvidia chief is against export controls on AI chips, saying that it was a failure and has completely backfired.

Other industry leaders do not take a similar stance, with Anthropic's head, Dario Amodei, comparing selling advanced AI chips to China to selling nuclear weapons to North Korea. Jensen did not take this comparison too kindly, saying it does not make any sense.

“What I’m fundamentally against, and it makes no sense, it makes no sense in this moment, is to compare Nvidia GPUs to atomic bombs. There are a billion people with Nvidia GPUs; I advocate Nvidia GPUs to all of you, I advocate Nvidia GPUs to my family, my kids, to people I love — but I don’t advocate atomic bombs to anybody,” the Nvidia CEO said. “So that analogy is stupid. And so, so if you start from there, you can’t finish a thought — if you start from believing that, you can’t finish the rest of the thoughts.”

Jensen Huang is a firm believer that the world should use the American tech stack and that it would be detrimental to the U.S.’s advantage if it were to block a nation from accessing it. Nvidia has a global advantage in that it’s the largest and most popular manufacturer of AI chips, and its technologies, like the CUDA architecture, drive the progress of most of the world’s AI developers. Keeping this technology widely available to anyone would mean that most of the world's AI—whether developed in the U.S. or built in China — runs on American hardware.

However, critics point out that this could fuel the nation’s adversaries, enabling them to develop and train advanced artificial intelligence for military purposes using Nvidia chips. Jensen said that the Chinese military will avoid U.S. AI tech, much like how the Pentagon does not use Chinese systems. The company also denied providing technical assistance for DeepSeek to improve its training efficiency on models, which were later used by the People’s Liberation Army (PLA). However, public documents revealed that some Chinese universities with deep ties to China’s military-industrial complex acquired Super Micro servers configured with Nvidia A100 AI GPUs.

Unlike nuclear missiles and atomic bombs, AI GPUs aren’t strictly military systems designed for a specific mission. Artificial intelligence is a powerful tool that has applications in science, research, business, and many other industries. However, its flexibility also makes it a dual-use technology, meaning it can be used in civilian and military contexts. It is the latter application that has U.S. policymakers worried, in which the same hardware and AI models can be leveraged by armed forces for operational use, such as intelligence and threat analysis, autonomous systems, simulations, and more. This could erode the U.S.’s technological and military edge and give its adversaries a strategic advantage.

Both sides of the argument have valid points — America has the advantage as the key provider of AI technologies worldwide, and it makes sense to keep it that way. However, it also does not want its rivals to have access to advanced technologies that could accelerate their capabilities and narrow the United States’ lead in defense technologies. Unfortunately, we can only tell which approach proves to be more effective years, if not decades, from today.

Nvidia CEO Jensen Huang is surprisingly not among the business leaders invited to join President Donald Trump as he visits China from May 13 to 15, 2026. One source familiar with the matter confirmed this with Bloomberg, saying that the leather-clad chief of the most valuable company in the world isn’t on the guest list, which includes Apple’s Tim Cook and Tesla’s Elon Musk. These executives represent significant business interests in China, but, for one reason or another, the White House passed over Huang this time.

Jensen is a fixture around Washington, and he’s been included in several of Trump’s state visits. He was part of the presidential entourage in the Middle East and the UK, and he was even praised by the president in London last year, where Trump said, “You’re taking over the world, Jensen.” So, his exclusion from the president’s China state visit is quite a surprise to many, especially as Trump approved Nvidia H200 exports to China in late 2025.

The AI chip maker used to be the driving force of China’s AI industry, that is, until the U.S. blocked its most advanced semiconductors over concerns that American “dual-use” technologies could be diverted towards China’s military programs. Nvidia made several adjustments to let Chinese companies have access to its hardware with the introduction of defanged versions of its latest chips, like the H20, but even that was disallowed in April 2025.

This ban caused Nvidia’s China market share to plummet from a high of 95% to essentially zero, allowing homegrown chipmakers like Huawei, Cambricon, Alibaba, and Baidu to gain ground as they fill the vacuum left behind by the American chipmaker. Even though Trump eventually allowed Chinese companies to purchase H200 chips once again (provided Nvidia secures a license to sell them to a firm), Beijing stepped in and told its customs officers to stop the chips at the border. It has been almost six months since the White House gave Nvidia the go-signal to sell the H200, but U.S. Commerce Secretary Howard Lutnick said that the company has yet to sell a single H200 AI GPU to China.

Even though Beijing understands that its AI companies need advanced hardware, like Nvidia’s Blackwell and upcoming Vera Rubin chips, it also needs to balance this with its desire to have a domestic semiconductor industry that can compete against what the U.S. offers. This is likely the reason why Nvidia’s H200 chip is still in regulatory limbo. Nevertheless, China’s access to the latest AI chips has always been a sticking point in its trade negotiations with the U.S, Bloomberg reports. American Enterprise Institute fellow Ryan Fedasiuk also told the publication that Huang’s absence from Trump’s entourage is a “strong signal” to the CCP that Washington will not budge on its stance when it comes to these high-end AI chips.

Nvidia CEO Jensen Huang said that the company's market share of AI accelerators in China has now dropped to 0%. The drop is staggering, given that the company owned the lion's share of China's AI accelerator market just two years ago.

"In China, we have now dropped to zero," Huang said in an interview with the Special Competitive Studies Project, a bipartisan initiative by American lawmakers aimed at ensuring long-term competitiveness of the U.S. "Conceding an entire market the size of China probably does not make a lot of strategic sense, so I think that has already largely backfired. Maybe it made sense at the time, but I think the policy really needs to be dynamic and needs to stay with the times."

"I think it would be fairly safe to say that having American chip companies and other companies in China makes a lot of sense."

Earlier this year, tech research firm Bernstein estimated that Nvidia’s share of China’s AI GPU market could fall from 66% in 2024 to roughly 8% in the coming years, both due to restrictions imposed by the U.S. government and because domestic vendors are moving to cover up to 80% of demand. According to Huang, this happened much later, though again, he talks only about Nvidia's direct sales to Chinese customers.

Meanwhile, Huang warns that even without leading AI GPUs and software stacks developed in America, China remains a formidable competitor when it comes to frontier AI models.

"American companies win around the world," Huang said. "The argument there is that across the five-layer cake, there's one particular layer that is too important because in the others, China can get ahead. They have cheaper energy. They have incredible talent. So, they [have] the number of science and math experts, and as a result of that, the number of AI researchers in China is quite extraordinary, it's one of their national treasures."

Given the situation, Huang also contends that U.S. export controls may be strategically counterproductive. He argues that conceding a market of that scale accelerates China's push toward self-sufficiency, while continued participation of American companies in that market would help extend the global reach of the American AI technology stack.

Indeed, Chinese developers are increasingly relying on local hardware, with companies like Huawei, Cambricon, Moore Threads, and MetaX advancing both silicon and software. In software — the so-called CUDA moat in particular — remains the main frontier of American AI technology in China that local companies have yet to conquer.

Ultimately, Huang warns that fear-driven narratives and export controls could slow the deployment of AI more broadly as China and other regions embrace it more aggressively as an economic tool. Long-term leadership will depend less on restricting global rivals and more on ensuring that the American AI ecosystem dominates globally, according to Huang.

Nvidia CEO Jensen Huang got into a heated debate during a recent podcast, during which he talked with Dwarkesh Patel about whether the U.S. should be selling chips to China. During part of the conversation, which you can see by expanding the tweet embedded below, Patel said he doesn’t know whether it’s actually good to give Chinese access to AI chips. Still, since he likes to play devil’s advocate during his interviews, where he takes an opposing stance to his guest, he asked the leather-clad chief of the world's largest AI chipmaker if doing so is a threat to American companies and national security.

Patel gave Anthropic’s Claude Mythos as an example for his argument, which apparently revealed “thousands of zero-day vulnerabilities” in “every major operating system and every major web browser.” He said that if China had access to the massive amounts of compute that Nvidia delivers, it could probably have used it to develop cyber-offensive capabilities that threaten the United States' security. Huang had a fairly nuanced response to this, but he also first pointed out that Mythos was trained on “fairly mundane capacity, and a fairly mundane amount of it."

You can expand the tweet above to see the meat of the tense exchange, which is about three minutes long.

Jensen says China already has access to a lot of compute power. Although Nvidia still makes the most advanced, most efficient chips, he argues that China can still create advanced AI models through sheer brute force, like Huawei’s AI CloudMatrix cluster. So, keeping the chipmaker out of the country would not stop its development of frontier AI models and would only result in Chinese AI being trained outside of the American tech stack.

“We want to make sure that all the AI developers in the world are developing on the American tech stack, and making the contributions, the advancements of AI — especially when it’s open source — available to the American ecosystem,” Huang said. “It would be extremely foolish to create two ecosystem: the open-source ecosystem, and it only runs on a foreign tech stack, and a closed ecosystem that runs on the American tech stack. I think that would be a horrible outcome for the United States.”

Another argument against selling advanced AI chips to China is that it will do the same thing the country did with iPhones and Tesla. While these two products are still leaders in their markets, many Chinese companies are now building products that can compete with them on price, features, and quality. This could also happen in the AI chip industry. If and when Chinese-made AI chips get the same capabilities as Nvidia’s latest offerings, couldn’t Chinese AI companies just easily switch over to a Chinese AI chip in the future, should it become available, or if Beijing forces them to?

“We have to keep innovating and, as you probably know, our share is growing, not decreasing. The premise that even if we competed in China, that we’re going to lose that market anyways… You’re not talking to somebody who woke up a loser,” Huang said. “That loser attitude, that loser premise makes no sense to me.”

He then went on to say that AI chips aren’t as simple as vehicles, where users can easily swap one brand for another daily. “Computing is not like that. There’s a reason why the x86 deal exists. There’s a reason why ARM is so sticky. These ecosystems are hard to replace; it costs an enormous amount of time and energy, and most people don’t want to do it. So, it’s our job to continue to nurture that ecosystem, to keep advancing the technology so that we can compete in the marketplace,” the Nvidia chief added.

“Conceding a marketplace based on the premise you described, I simply can’t acknowledge that. It makes no sense. Because I don’t think that the United States is a loser. Our industry is not a loser. That losing proposition, that losing mindset, makes no sense to me.”

The biggest point Jensen makes is that AI technology has five layers — energy, chips, infrastructure, models, and applications — and that none should be ignored just for the sake of one. He says, “Why are you causing one layer of the AI industry to lose an entire market so that you could benefit from another layer of the AI industry? There are five layers, and every single layer has to succeed. The layer that has to succeed most is actually the AI applications. Why are you so fixated on that AI model? That one company? For what reason?”

You can watch the complete podcast episode below.

U.S. Senators Jim Banks (R-Ind.) and Elizabeth Warren (D-Mass.) have jointly written a letter to Commerce Secretary Howard Lutnick, urging him to take “immediate action” on the diversion of American AI chips to China. According to the Financial Times, the two legislators made the written statement after three Super Micro employees, including one of its co-founders, Yih-Shyan “Wally” Liaw, have been charged with smuggling $2.5 billion worth of Nvidia hardware to China.

“We urge all necessary and appropriate actions, including the immediate pausing, suspension, or other reconsideration of all active export licenses covering advanced Nvidia AI chips and server systems destined for…China as well as intermediaries in south-east Asia, including Malaysia, Thailand, Vietnam, and Singapore,” the senators said in their correspondence to Lutnick. They also said they refuted Nvidia CEO Jensen Huang’s claims of no evidence of chip diversion of his company’s most powerful products, saying that “These statements were not simply wrong in hindsight. They were contradicted by reporting available at the time and potentially misled U.S. officials.”

Despite this, an Nvidia spokesperson told Tom’s Hardware, “Strict compliance is a top priority for Nvidia. We continue to work closely with our customers and the government on compliance programs as export regulations have expanded.” Furthermore, the company claims that “Unlawful diversion of controlled U.S. computers to China is a losing proposition across the board — Nvidia does not provide any service or support for such systems, and the enforcement mechanisms are rigorous and effective.”

Jensen Huang has been lobbying for the approval of the sale of Nvidia’s products to China, arguing that it’s advantageous for the U.S. to have Chinese companies using its technologies. All his effort finally came to fruition in December 2025, after President Donald Trump made a complete U-turn and allowed Chinese tech companies to acquire Nvidia H200 chips. After a few months of uncertainty from Beijing, the company was finally able to confirm an order for the H200 and is restarting the manufacture of these older AI chips.

Still, the lawmakers are concerned about China’s access to the U.S. latest chips, including Nvidia’s Blackwell and upcoming Vera Rubin AI GPUs. In fact, the House Foreign Affairs Committee will reportedly vote on the bill that will force chipmakers to add geo-tracking technology to their high-end gaming and AI GPUs. Although Nvidia is against such measures, it has developed a software tracking solution that will give operators a rough idea of where these Blackwell GPUs are located.

“Amazon can tell you where a package is at any given moment,” Ryan Fedasiuk, a technology security expert from the American Enterprise Institute, told the Financial Times. “There is no reason the most powerful AI hardware on earth should have a less sophisticated chain-of-custody system than a pair of sneakers.”

Nvidia CEO Jensen Huang said that he’ll be deeply alarmed if an engineer getting paid $500,000 a year does not consume at $250,000 worth of AI tokens to get their job done. The leather-clad chief of the world’s most valuable AI company said this during an episode of the All-In Podcast shot on the last day of Nvidia GTC 2026, after one of the hosts asked Huang if he’s spending around $2 billion a year on tokens for the Nvidia engineering team, with Jensen answering, “We’re trying to.”

“Let me give you a thought experiment. Let’s say you have a software engineer or AI researcher, and you pay them $500,000 a year,” the Nvidia CEO said. He also added, “At the end of the year, I’m going to ask him how much did you spend in tokens. And [if] that person said $5,000, I will go ape something else. If that $500,000 engineer did not consume at least $250,000 worth of tokens, I am going to be deeply alarmed.” Huang went on to compare an employee not using AI tokens to a chip designer saying that they will use paper and pencil and eschew CAD tools to get their work done.

Jensen compared today’s AI tools to machinery that was invented during the industrial revolution, which allowed workers to physically do things that, in the past, were either too heavy, too big, or took too long. Now, it seems that the Nvidia CEO wants to use AI for mental tasks so that Nvidia engineers can focus on creativity. “It’s just a new way of doing computer programming. In the past, we code. In the future, we’re going to write ideas, architectures, specifications,” Huang said. “I think that every engineer is going to have a hundred agents.”

It seems that the Nvidia CEO isn’t the only one investing in AI tokens for his employees to freely use. According to Business Insider, many tech companies are now starting to offer guaranteed access to AI inference power as part of the remuneration package to candidates. That thought is that by giving people generous amounts of AI tokens, they’d be able to amplify their productivity by as much as 10 times or more.

However, using AI in the corporate setting is not without its issues. There have been reports that more than half of CEOs have yet to see clear benefits from AI deployments, with only about 12% getting higher revenues and reduces costs. We’ve also seen several AI-related outages with Amazon Web Services, with one report saying that Amazon has called its engineers for a meeting to discuss issues created by “Gen-AI assisted changes” that had “high blast radius.” And although Microsoft did not say anything about AI, it promised to fix Windows 11’s most annoying flaws to restore its reputation several months after its CEO revealed that AI writes up to 30% of Microsoft’s code.

At a press Q&A with Tom's Hardware at GTC 2026, Nvidia CEO Jensen Huang downplayed criticism of DLSS 5, the company's new use of AI and neural rendering to infer how certain features of games would look if they were more photorealistic.

Since the debut of the feature, some critics have vocally complained on social media that the technology is making games look worse, homogenous, or only show Nvidia's view of the world. Much of the criticism has focused on the updated appearances of Resident Evil Requiem's Grace Ashcroft and Leon Kennedy.

"Since DLSS 5 was revealed yesterday, there's been a pretty vocal response from some of the gaming community that the technology appears to make games appear worse, homogenous, or show only NVIDIA's view of how games should look. How do you feel about that criticism?' asked Tom's Hardware editor-in-chief Paul Alcorn.

"Well, first of all, they're completely wrong," Huang said in response. "The reason for that is because, as I have explained very carefully, DLSS 5 fuses controllability of the of geometry and textures and everything about the game with generative AI," Huang continued.

He added that developers can still "fine-tune the generative AI" to make it match their style, adding that DLSS 5 adds generative capability to the existing geometry of the game, but that it "doesn't change the artistic control."

"It’s not post-processing, it’s not post-processing at the frame level, it’s generative control at the geometry level," he said.

Huang also said that developers can try the tool and see how they want to use it, suggesting that it's up to a developer to try to make a "toon shader" or see if the game should be "made of glass."

"All of that is in the control — direct control — of the game developer," he said. This is very different than generative AI; it’s content-control generative AI. That’s why we call it neural rendering."

We'll see if the vocal gamers who say they dislike what they see change their mind as we see more. DLSS 5 is set to launch in the fall, and there will likely be far more demos of this technology that are more fully baked before then.

Update 3/19/2026 4:38pm PT: Added full text of question to Jensen.

Nvidia's GTC 2026 keynote has wrapped. During the two-hour (and change) presentation, Nvidia CEO Jensen Huang delivered several announcements, from new Vera CPUs to Groq LPUs, as well as laid out a vision for AI over the next 12 months.

As with any Nvidia event these days, we heard a lot about AI, as well as learned about Vera Rubin systems and DLSS 5. See our full live blog below.

We're moments away from GTC 2026

Hello and welcome to Tom's Hardware's live blog for the GTC 2026 keynote. Jensen Huang is moments away from taking the stage. Myself, Jake Roach, will be tending the blog while our very own Paul Alcorn and Jeffrey Kampman are on the ground to cover all of the announcements in real-time.

What to expect from GTC 2026

There's always room for surprises, especially at Nvidia's own GTC event, but there are a few key announcements we're focused in on:

• Intel x Nvidia partnership — Nvidia bought $5 billion in Intel stock last year, and at the time, announced that the two companies would be working together on custom x86 processors across both the data center and consumer PCs. The deal has apparently been decades in the making. It's not clear if we'll hear about consumer or enterprise chips, or both, but there's a good chance we'll hear something from the partnership.
• The 'future of real-time rendering' — Nvidia presented at GDC (not GTC) about neural rendering, but just a week later, the company is teasing that it will reveal the "future of real-time rendering" at GTC (not GDC). Maybe it's a new DLSS feature, maybe it's something completely new. We don't know, but Nvidia has already confirmed something is coming for gamers during the keynote.
• More on Vera Rubin — Nvidia officially launched its Vera Rubin NVL72 in January, and it started shipping samples to customers just weeks ago. These next-gen AI data center boards are on-track for the second half of the year, so we expect to hear a lot about them during the keynote.
• AI agents — Since the release of OpenClaw, the tech industry has been washed in talk of AI agents. Nvidia will talk about AI agents during the keynote, that much is almost guaranteed. We could see an announcement of "NemoClaw," which is an AI agent Nvidia is reportedly developing to compete with OpenClaw.
• Nvidia N1/N1X — Perhaps the biggest rumor around Nvidia over the past year has been the N1 and N1X, which are two SoCs reportedly being developed for the consumer market. Do we finally see a reveal at this year's GTC? Perhaps, but this is the last item on this list for a reason.

T-Minus 5 Minutes

Run to the bathroom, get your drink ready, and settle in. We're just a few minutes away from the start of GTC 2026. Jensen will probably start with a short history of Nvidia's role in AI, but we expect the announcements to rapid-fire out after that point. We're sat down in the SAP Center in San Jose and ready to dig in.

Running a bit behind schedule

We're a few minutes past the top of the hour, and we're still waiting on the keynote to start. In the meantime, a quick reminder that you can watch along with us through the live stream above.

That's... a lot of country music?

We're all sitting in surprise here at Tom's Hardware at the amount of country music playing before Jensen takes the stage. We're nearly a quarter past the top of the hour at this point and still waiting for the keynote to start. There's nothing wrong with country music, but rustic Americana and enterprise AI isn't a combo I'd normally expect.

And we're off!

We may have started a few minutes late, but the keynote has officially begun. We begin with a short video about AI tokens and all the wonderful things (according to Nvidia) we've all done with them, from healthcare to space to construction.

The man of the hour is here: CEO Jensen Huang

Jensen Huang has taken the stage in a familiar leather jacket. Sorry folks, there's no special jacket this time around. Jensen is starting off the show thanking some of the people that hosted the preshow leading up to the keynote.

'We've been working on CUDA for 20 years'

CUDA is one of the major reasons Nvidia is in the position it's in today, and this GTC marks the 20th anniversary of CUDA. "The single hardest thing is to have built up our install base, we're in every cloud and computer company in every single industry," says Jensen.

Pricing of Ampere in the cloud is going up

The prevalence of CUDA has accelerated what Nvidia calls a "flywheel." Nvidia attracts developers who develop on CUDA, which leads to more people adopting Nvidia hardware, and the lifecycle continues. Because of this, Jensen says the price of GPUs using the now-dated Ampere architecture has actually gone up in the cloud.

'GeForce is Nvidia's greatest marketing campaign'

Jensen says that "GeForce is Nvidia's greatest marketing campaign." It's an interesting way to frame the conversation, and one that Nvidia has been trying to crack for the past few years. Jensen paints a picture of Nvidia creating the first programmable shader 25 years ago, which eventually led to CUDA, and used GeForce as a vehicle to drive adoption.

Nvidia is showing off the next generation of computer graphics: DLSS 5

The first announcement is a big one: DLSS 5. Nvidia is showing it off in Resident Evil: Requiem, Hogwarts Legacy, and Starfield. We're all waiting eagerly to hear more details about what DLSS 5 includes, but the side-by-side comparisons are compelling.

What is DLSS 5?

Nvidia says it combined controllable 3D graphics and structured data with generative worlds. "This concept of fusing structured data with generative AI will repeat itself in one industry after another industry after another industry."

'This is my best slide'

Jensen jokes that he's going to spend the rest of the keynote going through the slide you can see above about structured data. This is "the ground truth" of enterprise computing.

AI can solve unstructured data, says Jensen

Jensen is describing the importance of AI in unstructured data. He says this data makes up 90% of the world's data but it's been "useless" because you can't search or query it. IBM, the inventor of SQL, is accelerating WatsonX data with the cuDF acceleration framework.

More Moore's Law talk

Jensen likes to talk about the death of Moore's Law, and he's doing so once again. "Moore's Law has run out of steam, accelerated computing allows us to take giant leaps forward." Jensen is showing off an example with Google Cloud and showing how Nvidia's acceleration can be repeated across companies and industries.

Nvidia is bringing OpenAI to AWS this year

"As you know, [OpenAI] is completely compute-constrained." Jensen says that OpenAI will come to AWS this year, hopefully lightening the load on its massive infrastructure demand.

'Vertically integrated but horizontally open'

Jensen describes Nvidia as "vertically integrated but horizontally open," which may or may not raise some eyebrows at the FTC. Regardless, Nvidia says there's "no other way" it can be given what it's trying to do with accelerated computing, delivering the entire stack to customers.

Nvidia says it needs domain-specific libraries to address the needs of different industries

AI has a lot of applications, but Jensen says it isn't as simple as throwing GenAI at the wall and hoping it sticks. "We have to have domain-specific libraries that solve problems in every one of these verticals," he says.

Bringing it back to CUDA

"We are an algorithm company," says Jensen, after spending 10 minutes talking about the applications of Nvidia's software stack in just about every industry. Everything comes back to Nvidia's CUDA-X libraries, and Jensen describes them as the "crown jewel" of the company.

cuDNN is what caused the 'big bang' of AI

Nvidia says cuDNN, or CUDA Deep Neural Network, is one of the most important libraries the company has ever made, saying it caused the "big bang" of modern AI. Nvidia is showing a short video about its various CUDA-X libraries, including a life-like video that's entirely simulated.

Nvidia 'reinvented computing'

Jensen is talking about some of the many "AI native" companies, which are only possible because Nvidia "reinvented computing," says the executive. We're at the beginning of a new platform shift, he says, and it's akin to the PC revolution. This really kicked off over the past two years with ChatGPT kicking off the generative AI era.

An accelerated timeline of AI

There's been rapid AI development over the past few years. In 2023, it was ChatGPT. In 2024, it was reasoning models like o1, and in 2025, it was huge models with massive context windows like Claude Code. It's the first "agentic model," says Jensen. The executive says 100% of Nvidia is using Claude Code, along with other models. In 2026, Nvidia says we've reached an "inflection point for inference."

Nvidia says it's going to double demand through the next year

Last year, Nvidia said it saw about $500 billion of high confidence demand and purchase orders for Blackwell and Rubin through 2026. "I see through 2027 at least $1 trillion," says Jensen. "Now, does it make any sense?" Jensen says that's what he's going to spend the rest of the keynote talking about.

Nvidia is the only company that runs every domain of AI across every domain of AI models

Jensen says Nvidia is the only company that runs every domain of AI across every domain of AI models. Between Nvidia, Anthropic, and Meta SL, Jensen says that represents a third of the world's AI compute. Nvidia says it's proven that "you can build with complete confidence" as an AI infrastructure company.

Nvidia says Grace Blackwell was 'a giant bet'

Nvidia NVL72 was a "giant bet," says Jensen, and he thanked Nvidia's partners for sticking with the company. "It wasn't easy for anybody... inference is the ultimate hard." The bet paid off, according to Nvidia, which you can see in the slide above.

50x performance per watt, 35x lower cost

"Nobody believed me," says Jensen. When Nvidia says it delivered 30x better performance per watt, on NVL72, it was wrong. Apparently, it delivers 50x better performance per watt. Jensen once again goes back to Moore's Law, saying it would maybe deliver 1.5x perf in a year.

'It's now a factory to generate tokens'

Jensen says data centers used to be a place to store files, and they're now a factory to generate tokens. Inference is the workload and tokens are the new commodity, says Nvidia. Now, onto a short video showing how we got here.

Vera Rubin joins Jensen on stage

Vera Rubin NVL72 is the "engine supercharging the era of agentic AI." A new addition is the Groq 3 LPX tray, and as a whole, Nvidia says it's delivered 40 million times more compute over the past decade. Jensen is showing off Vera Rubin on stage; the whole thing. It's "one giant system."

Jensen says the Vera CPU is designed for high single-threaded performance, and the company built it go along with its racks for agentic processing.

Learn more about Nvidia's Vera CPU

The 88-core Vera CPU fits into a rack with 256 chips, each of them liquid-cooled. If you want to dig in deep on Nvidia's latest chip that aims to take on AMD and Intel, take a look at our Vera CPU deep dive.

Groq 3 LPU and Groq LPX join the fray

A new addition to the system is a Groq LPX rack, which we learned about ahead of GTC. You can read Jeffrey Kampman's breakdown of Groq 3 in Vera Rubin now.

Jensen shows off NVLink for Rubin Ultra

Jensen explains how NVLink for Rubin Ultra works, with compute sitting in the front and the scale-up fabric in the back.

This is 'the most important chart' for companies, says Nvidia

Tokens are "the new commodity," according to Nvidia. For businesses, Nvidia says that the throughput of an AI factory at iso power is something that will be "studied for years." More tokens means smarter models, and the smarter the models get, you need better token throughput. Nvidia says that, at every tier, Vera Rubin delivers much higher throughput.

Low latency and high throughput are 'enemies of each other'

Groq is important for Nvidia because it pushes beyond the limits of NVL72. With Groq LPX, Nvidia says it's able to deliver up to 10x in revenue to companies using Vera Rubin. It helps solve the problem of delivering low latency and high throughput, which Jensen described as "enemies of each other."

Nvidia combined one chip for high throughput and one for low latency, which it achieved with disaggregated inference.

Vera Rubin sampling is going 'incredibly well'

Jensen admits that the Grace Blackwell sampling had some issues, but apparently Vera Rubin sampling is going smoothly. In fact, the first Vera Rubin is system is apparently already running in Microsoft's Azure Cloud.

Vera Rubin is 7 chips across 5 rack systems

Vera Rubin is undoubtedly Nvidia's most ambitious system to date, featuring seven chips across five rack systems. Compared to x86 and Hopper, Nvidia says Vera Rubin is able to deliver 700 million tokens per second compared to just 2 million

Here's Nvidia roadmap

Jensen is teasing next-gen Feynman systems. It has a new GPU, new LPU, new CPU called Rosa, Bluefield 5, and Kyber with copper and CPO scale up. Feynman systems are on-track for 2028, so we'll hear a lot more about them throughout the year. At next year's GTC, we'll probably run back the same talking point with Feynman that we hard about with Vera Rubin this year.

Meet me in the Omniverse

Nvidia built Omniverse to meet suppliers virtually, allowing co-design in the data center at a much broader scale. The goal is to leave "no power squandered." They're blueprints for AI factories, which Nvidia calls its DSX platform.

Data centers are going into space

Nvidia is working on a system called Vera Rubin Space-1, which will be the first data center in space. Sounds like we're in early stages, but Nvidia has "a lot of great engineers" working on it.

NemoClaw makes using OpenClaw easy

Nvidia is streamlining the process of setting up an AI agent with OpenClaw. Type two lines of shell commands, and you're off to the races with an AI agent. From there, Nvidia says you just need to give it a task and let the agent run its course.

What is OpenClaw? Nvidia says it's an OS

Now Jensen is describing what OpenClaw is, which is a description no one in the room at GTC actually needs. For anyone who isn't aware, it's an agent that can connect to cloud systems. It can spawn other agents, do scheduling, decompose a problem, etc. Jensen says it's an operating system. "It's no different than how Windows allowed us to make personal computers."

Nvidia worked with OpenClaw to make it enterprise-secure

NemoClaw is enterprise-secure, helping protect sensitive information. AI agents can communicate externally and execute without intervention, which is obviously a problem. NemoClaw provides a reference software stack for businesses to keep OpenClaw secure.

Nvidia is building a Nemotron coalition

Nvidia says that Nemotron 3 Ultra will be the best base model in the world. In order to scale out Nemotron, Nvidia is creating a coalition for Nemotron 4, including companies like Black Forest Labs, Perplexity, Mistral, and Cursor.

Bringing agents to the physical world

Nvidia is showing off 110 robots at GTC, showcasing its "physical AI." Nvidia announced several new partners, including four new partners for robo-taxis, including BYD, Hyundai, and Nissian. Nvidia is also partnering with Uber, connecting robo-taxis into Uber's network in select cities.

Olaf joins Jensen on stage

In a not-at-all-awkward meeting, Olaf from Frozen joins Jensen on stage. The executive is now describing the various AI models used to make Olaf, which is... something. Anyway, Olaf is helping close out the keynote.

That's a wrap, with country song that's probably generated by AI

Well, we're done now, I guess. Nvidia closed out its keynote with an animation of several robots (plus Jensen) sitting around a fire singing a song about the keynote. It's a country song, and probably generated by AI? I don't really know what to say about this one. A rough-talking robot singing about tokens and open-source software wasn't on my bingo card.

Regulatory filings just revealed that Nvidia earmarked a $4-million bonus for its CEO, Jensen Huang, if the company hits specific financial targets by January 31, 2027. This is a huge amount for the average person, but, according to Reuters, the leather-clad executive’s compensation package for 2025 totaled to $49.9 million, with 77% of its value, around $39.8 million, made up of stock awards. This means that the tech executive’s financial incentive to hit targets is less than 10% of his gross annual salary.

Mr. Huang’s bonus will be paid out in cash, allowing him to spend it as he pleases (like buying a Mercedes Benz for his parents) without affecting his ownership or the future value of his shares. But it’s actually the stock awards that are driving his wealth, putting Jensen among the 10 richest people on the planet, with his value estimated to be around $150 billion. In fact, he sold 6 million Nvidia shares in June of last year, which was announced about three months earlier, and is estimated to be worth around $925 million. This makes the $4-million bonus a drop in the bucket of what he could potentially make in a year by selling some of his holdings.

We should note, though, that the Nvidia CEO won’t take home the entire $4 million. Because it will be paid out in cash, he will have to pay both Federal and State income taxes on it, as well as other taxes. In the end, it’s estimated he will receive $2 to $2.5 million from the bonus. It’s for this reason that some executives prefer their bonuses to be paid in stock — aside from potentially making their bonuses larger when share prices go higher, it also means that they don’t have to pay income taxes until they sell their holdings.

Even though Huang has been at the helm of Nvidia since its founding, he didn’t get consistent salary increases. In fact, he only received a hike in his base pay last year, after staying at the same level for a decade, and that was only increased so that his compensation would stay at a similar level as his peers. Nvidia’s filing did not mention any increases for Jensen this year, despite the company reporting record-breaking annual revenues, in the face of challenges in China. So, if the CEO can keep this momentum, he’ll get that 7-digit bonus as part of his reward. But with Jensen Huang owning about 3.5% of Nvidia, a positive market performance should be more than enough to make up for the 'paltry' $4-million bonus he’ll get for hitting the company’s fiscal targets.

As the world reels from the consequences of the AI boom, Nvidia — both a benefactor and beneficiary — is busy enjoying its fruits. Speaking at a press conference recently, CEO Jensen Huang shared his views on various topics, but the bulk of the discussion focused on bottlenecks in data center buildouts. This is where he went on a pro-scarcity line of thought that can best be described as controversial.

"I love constraints... because in a world of constraint, you have no choice but to choose the best," said Huang. He explained that a lack of options will force companies to go with the highest-end hardware instead of experimenting with cheaper alternatives. AI firms won’t fill their data centers with arbitrary hardware when “land, power, and shell are constrained."

The exec left no room for subtlety by doubling down on his argument and saying, "Because everything is so constrained, if [I] choose poorly, [my] revenues are affected, everything is affected. They can’t choose poorly." Those words reflect an almost unapologetic perspective that champions efficiency. When supply becomes tight, no one wants to take risks, so the safest bet becomes the most sensible one.

And it's not just GPUs that Nvidia has; it can lay down the entire infrastructure of a data center, which Jensen kindly reminded everyone of: "From the moment you secure the capacity, we’re gonna be able to stand up an entire factory for you. We’re the only company in the world that can come into your company and help you stand up an entire AI factory."

These comments are more specific than broad strokes about how the prevailing component shortages are actually beneficial to the trillion-dollar corporation. But the thing is, AI eating up all the production lines affects everyone else, too, like gamers, who are now left with triple-priced memory and storage. GPUs are getting more expensive as well, and the AI boom is showing no signs of slowing down.

"You know, if you set up a factory, a plant, a DRAM plant, and I come in and say, “You know what? Go ahead and set up the DRAM plant because I’m gonna use it,” that goes a long way. You might as well take that to the bank, as many of them have. I think the fact that everything is scarce is fantastic for us." That last line might be particularly irksome because it's so disconnected from what the average person is experiencing.

Gaming accounts for only 8-9% of Nvidia's total revenue, with data centers by far the largest contributor, so it's no surprise the company is happy to sell the AGI dream. Enthusiasts going bankrupt thanks to their next RAM purchase is not Nvidia's concern.

Huang ended his thoughts by saying, "I've got all the memories, I've got all the wafers, I got all the CoWoS," referring to how his company is basically the strongest negotiator in the industry right now. He added, "I've got all the packaging, I've got all the systems, I've got all the connectors, I got all the cables. Everything from copper to multilayer ceramic capacitors, everything is secured."

As for the regular earthlings, make sure you enjoy that 9 GB RTX 5050.

Jensen Huang, chief executive of Nvidia, has rebuffed claims that the U.S. intends to shift 40% of Taiwan's semiconductor capacity to the U.S., therefore removing the island's silicon shield, reports DigiTimes. He insisted that the global fab construction represents new capacity growth rather than relocation. Haung also said that TSMC must expand worldwide to meet surging AI-driven demand for chips and keep Taiwan as its stronghold.

Huang explained that demand for wafers is now outpacing what Taiwan's power grid can physically support, making overseas production a necessity rather than a political manoeuvre. He said that while TSMC will build and expand fabs in the U.S., Europe, and Japan, a substantial share of its output will remain in Taiwan, as no other region can replace the island's manufacturing ecosystem. According to Huang, spreading production across multiple regions strengthens resilience for both Taiwan and the U.S. and prevents supply bottlenecks as AI hardware volumes rise sharply.

For Nvidia, which sells everything it can produce both in Taiwan and the U.S., vast manufacturing capacities are crucial. Meanwhile, getting enough memory — HBM, DDR5, GDDR7, LPDDR5X, or even NAND — is as crucial for the company as getting enough compute silicon. To that end, production capacities for DRAM and NAND in Japan, South Korea, Taiwan, Singapore, and eventually the U.S. are just as important to Nvidia as logic production. Huang said the company is coordinating closely with all major HBM suppliers —Samsung Electronics, SK hynix, and Micron Technology — to secure the volumes required for its next-generation AI accelerators, namely Rubin.

When it comes to geopolitics, Huang said that lawmakers must balance three competing goals: national security, technological leadership, and economic leadership. Therefore, he dismissed remarks by Anthropic CEO Dario Amodei, who compared exporting advanced AI processors to China to 'selling nuclear weapons to North Korea,' and reminded that the current U.S. government has determined that selling Nvidia's H200 to Chinese entities does not undermine national security. However, he noted that it is now up to the Chinese government to let these processors into the country, as the company is awaiting regulatory clearance from Chinese authorities.

During his Taiwan visit, Huang plans to attend internal Nvidia meetings and Lunar New Year events, as well as to meet TSMC founder Morris Chang and chairman C.C. Wei.

Nvidia CEO Jensen Huang lamented during an interview at the 2026 World Economic Forum gathering purchasing “the most expensive car in the world.” According to the leather-clad CEO, he regretted cashing out some of his company stock after its 1999 IPO to buy his parents a nice car, although he also said they still have the vehicle.

“My only regret was at the IPO. After the IPO, I wanted to buy my parents something nice, and so I sold Nvidia stock at a valuation of $300 million — the company was at a valuation of $300 million — and I bought them a Mercedes S-Class,” Huang said. “It is the most expensive car in the world. They regret it.” Thankfully, when the host asked, “Do they still have it?” Jensen answered, “Oh, sure. Yeah, they still have it.”

The S-Class was Mercedes-Benz’s top-of-the-line offering back in 1999, and given that Huang just received a massive windfall after Nvidia’s IPO, we can assume that he bought the most expensive S600 trim, which came with a 6-liter V12 engine. Multiple sources indicate that this vehicle cost around $135,000 back then, depending on the options. With Nvidia’s stock price at $12 per share at the time, Jensen likely sold around 11,250 shares to afford the Mercedes.

Nvidia shares have made several splits since then:

So, if Huang decided to gift his parents Nvidia shares instead of an S600, they’d probably have 5,400,000 shares of company stock right now. Aside from the number of shares, its value has also skyrocketed, with each share sitting at around $187 at the time of writing (5.4 million shares are currently valued at $1,009,800,000). This far eclipses the price tag of the bespoke Rolls-Royce Droptail, currently the most expensive new car in the world, worth $32 million apiece, with only four units being made.

One could say that this was a bad investment for Jensen, and his parents also seem to agree. Nevertheless, that amount is just a drop in the bucket for the CEO. After all, even though he took out 6 million shares just last year, that is still a minuscule amount compared to the estimated $123 billion he holds in Nvidia stock.

Artificial intelligence is expected to reshape the labor market by eliminating white-collar positions that do not require a lot of creativity or experience, but at the same time increase demand for blue-collar employees like construction workers, electricians, or plumbers, as AI infrastructure requires a massive built-out, according to Jensen Huang, chief executive of Nvidia. That build-out spans many industries, so while some roles will vanish, others will flourish, reports Bloomberg.

"This is the largest infrastructure buildout in human history that is going to create a lot of jobs," Huang said in a conversation with Laurence D. Fink, the head of BlackRock, at the World Economic Forum 2026. "We are going to have plumbers, electricians, construction and steel workers, network technicians, and people who install and fit out the equipment. In the United States we are seeing quite a significant boom in [these areas]: salaries have gone up, nearly doubled. We are talking about six-figure salaries for people who are building uh chip factories or computer factories or AI factories. We have a great shortage in that."

However, the benefits of AI-driven growth are unevenly distributed across the labor market. Anthropic CEO Dario Amodei once warned that AI-enabled automation could trigger a 'white-collar bloodbath,' which could eliminate up to 50% of entry-level office jobs. He noted that Anthropic's Claude AI has become particularly great at coding tasks, which could displace junior software developers and even erode portions of more senior software engineering work.

Still, even Amodei believes the long-term gains from AI will outweigh the damage. Nonetheless, he warns that large-scale unemployment or underemployment remains a serious risk over the next five years.

By contrast, Huang argues that some professions that can greatly benefit from both AI and human touch will actually increase demand for certain specialists, which will lift certain industries to new heights.

"Ten years ago, one of the first professions that everybody thought was going to get wiped out was radiology," Huang noted. "The reason for that was that the first thing AI [gpy] superhuman in capability was computer vision, and one of the largest applications of computer vision is studying scans by radiologists. Well, 10 years later, it is true that AI has now completely permeated and diffused into every aspect of radiology. It is true that radiologists use AI to study scans. […] However, […] the number of radiologists have gone up. Is that because a lack of trust of or is that because the human interaction with the results of AI is a better outcome? […] The fact that they are able to study scans now infinitely fast allows them to spend more time with patients diagnosing their disease, interacting with the patients, interacting with other clinicians. […] As a result of that, the number of patients that the hospital can see has gone up, [driving revenues of hospitals]."

In short, while AI can be a disaster for certain industries and professions, its impact on the quality of life will likely be comparable to the impact of electricity, automobiles, computers, broadband Internet, and telecommunications, all of which created many more professions and employment opportunities than they eliminated. However, one should note that the impact of AI can be compared to the cumulative impact of the aforementioned technologies combined in a very short time, so making exact predictions here is hardly a good business.

Nvidia CEO Jensen Huang has said in an interview that Nvidia is TSMC’s largest customer at the moment, dethroning Apple, which has previously held the record for some time. The leather-clad CEO said this during the first episode of the “A Bit Personal with Jodi Shelton” podcast, wherein Shelton asked him where he gets his confidence. Shelton is a self-proclaimed "longtime leader in the global semiconductor industry," and is also the CEO and co-founder of the Global Semiconductor Alliance.

“I remember Morris Chang has a similar story when he first met you, that you immediately said, ‘I’m going to be your biggest customer or one of your biggest customers. And he’s like, ‘Wow, that’s a lot of gumption.’ So, where did that confidence come from at such an early age?” Shelton asked. “Well, you know, it’s rough to know everything — I’m just kidding,” Jensen said with a laugh. “By the way, Morris will be happy to know Nvidia is TSMC’s largest customer now.”

The AI GPU company was once TSMC’s top customer in the early 2000s. However, it was overtaken during the 2010s by Apple when TSMC took it on as a customer to build the iPhone and iPad processors, after Intel fumbled the potential partnership with Cupertino. This was especially true during recent years when the iPhone overtook Samsung in market share across the globe.

But even if Apple’s smartphones, tablets, and even the legendary Apple silicon on Macs and MacBooks are driving record sales for the company, the AI boom is also pushing demand for Nvidia’s AI GPUs, resulting in skyrocketing revenue for the company. More than that, enterprise customers are willing to pay billions and billions to Team Green to get as many AI processors as they can, whereas many consumers have a price ceiling after which they will go with another brand if a smartphone, tablet, or laptop is priced too high.

Aside from losing its top spot, there are also rumors — reported by WCCFTech from the Apple leaker Fixed Focus Digital — that TSMC is hiking up the prices it’s charging Apple for chips, especially as the AI demand is squeezing capacity for other semiconductors. Furthermore, Cupertino might no longer have production priority. However, this is just speculation, and even if it’s true, the companies will likely keep information like this confidential.

Nvidia’s success is directly tied to the AI hype, with many tech companies pouring money into acquiring thousands, if not hundreds of thousands, of GPUs just to get the horsepower to train the most advanced models. And with Team Green cornering the market for AI processors, it’s basically printing cash as long as companies feel that they can make more money by adding more computing power. But if the AI bubble pops and we’re left with a lot of AI data centers with no customers, then we expect Apple to retake its position as TSMC’s number one customer.

Nvidia CEO Jensen Huang went on the No Priors podcast to discuss the current advances in AI technology and to refute claims he believes are wrong about AI. The multi-billionaire made his feelings very clear about the current climate of AI, saying that doom-and-gloom influencers have negatively impacted the AI industry. He also claims that we are far away from "god AI" becoming a reality.

A third of the way into the podcast, Jensen claimed that someday we might have god AI, but clarified that someday will likely be on the level of a biblical or galactic scale. Huang said, "I don't see any researchers having any reasonable ability to create god AI. The ability [for AI] to understand human language, genome language, and molecular language and protein language and amino-acid language and physics language all supremely well. That god AI just doesn't exist."

Huang further clarified that god AI he believes is not coming "next week." But he deems that AI should be used to advance the human population as much as possible in the meantime, before this prophetic god AI shows up. He also does not desire a god-level AI to exist: "I think that the idea of a monolithic, gigantic company/country/nation-state is just.. super unhelpful, it's too extreme. If you want to take it to that level, we should just stop everything..."

Moving on, Jensen fired shots at influencers who paint AI in a negative way: "..extremely hurtful frankly, and I think we've done a lot of damage lately with very well respected people who have painted a doomer narrative, end of the world narrative, science fiction narrative. And I appreciate that most of us grew up enjoying science fiction, but it's not helpful. It's not helpful to people, it's not helpful to the industry, it's not helpful to society, it's not helpful to the governments."

Huang wants AI to succeed as a tool that people can use to make their work more efficient. One use case that Huang addressed last week is the ongoing labor shortage, noting that robots can act as "AI immigrants". However, the real-world effectiveness of AI paints a different picture. Stanford University reported last year that job listings dropped 13% in three years due to AI. Furthermore, Fortune reported that 95% of AI implementations have no impact on P&L.

But that is not stopping the tech industry from increasing AI capacity worldwide. Meta just announced a 6-gigawatt-capable nuclear power plant aimed at powering AI datacenters, following in the footsteps of The Stargate Project from OpenAI.

Jensen Huang, Nvidia CEO, will take to the stage today in Las Vegas, Nevada, for the company's CES 2026 keynote. The keynote begins at 1 p.m. PT, and we'll be covering it live, with the latest updates.

To set the stage, Nvidia has had a record 2025, building on the back of demand from its data center business, where it generated a staggering $51.25 billion in revenue in Q3 of FY2026, a rise of 66% year-on-year. For those looking for consumer products, such as its GeForce lineup of graphics cards, don't expect too much, as the company has already announced that we won't be seeing new GeForce GPUs during its later GeForce On community update, which is set to begin, at 9 p.m. PT.

It's Jensen's world, and we're just living in it

In 2025, Nvidia had one of its best years to date. It launched the RTX 50 series, and its data center profits skyrocketed. However, 2026 paints a very different picture. With the AI industry booming, and hyperscalers shovelling investment into new data centers like there's no tomorrow, the industry is waiting with bated breath to see exactly what course Huang might plot for 2026 and beyond. Needless to say, the entire industry will hear the reverberations.

— Sayem Ahmed

Nvidia preshow kicks off CES festivities

While Jensen Huang hasn't taken to the stage yet, Nvidia has a 'pre-game' show, where its showing a manner of applications that use Nvidia tech, complete with an interview panel ahead of time. While it's a neat warm-up, don't expect anything too staggering while things are still kicking off.

Huang is set to take the stage at 1 p.m. PT, so there's not too long to wait until we get to the real meat of today's keynote.

— Sayem Ahmed

The preshow is over: T-minus 3 minutes until the keynote begins

The preshow is now over, and Huang is expected to take the stage in three minutes to kick things off in earnest. Being rolled onto the stage is a high-resolution screen, with some semi-dramatic music playing, and we'll expect to hear more shortly. While this is fun, what are the odds that the music is AI-generated?

There may be some expectation that Huang will emerge carrying some kind of object. We've seen him roll out with robots and even a shield made of chips before; surely the company has the cash for more than just a new leather jacket.

— Sayem Ahmed

Nvidia is late to its own party

Despite a slick preshow, Nvidia has yet to officially commence its keynote, running around ten minutes later than anticipated. You'd think that with the vast resources available to Nvidia, they'd run on time. Perhaps an AI model running a calendar hallucinated somewhere?

Regardless, the industry is waiting with bated breath for things to kick off, and we'll be right here reporting the latest, as it happens.

— Sayem Ahmed

Jensen Huang takes to the stage

Slightly later than expected, the show has now officially begun, with Nvidia CEO Jensen Huang taking the stage to lay out what 2026 and beyond might hold for Nvidia. Expect Nvidia to press on topics like AI, data centers, and robotics. While it might not be quite as exciting as the launch of a new consumer graphics card, whatever is announced over the course of the keynote will likely set the tone for the rest of the industry to follow for the rest of the year.

— Sayem Ahmed

Inventing a new world with AI

100 trillion dollars of industry investment is shifting over to AI, or so Jensen Huang claims. The CEO states that R&D budgets are now pouring in, perhaps to cool down claims of circular funding in the AI industry. The CEO is now shifting the conversation into a history lesson for AI models, reiterating that Agentic models like Cursor are a focus for 2026 and beyond.

— Sayem Ahmed

Nvidia's focus on frontier models across industries

Huang reiterated that it's not a cloud distribution service, as DGX cloud winds down to R&D, it's now focused on developing frontier models like Earth 2, Cosmos, a world foundation model, GR00T for robotics and locomotion, and more.

Huang states that he open-sources these models, but also the datasets behind them, so developers understand what makes things tick, with the intention for every company to take part in the incoming AI developments. And just like that, the lights go out, and Jensen makes a joke.

— Jeffrey Kampman

AI tops leaderboards across the industry

Nvidia's models are topping leaderboards, with the hopes that it can make developers utilize and create AI agents in order to research, models, and more easily. With reasoning capabilities, AI models no longer have to understand everything in a single day.

Jensen mentioned Perplecity as an example of how it would create an AI reasoning chain to create a multi-model, making just about anything fit a certain task, which has empowered AI startups — all thanks to Nvidia's technology, of course.

— Jeffrey Kampman

Nvidia Brev: Creating closed agentic sandboxes

Using a new tool called Nvidia Brev, the company has demoed an environement that can hook up to a DGX spark inside a closed environment for a variety of AI applications, or connecting it to frontier models via HuggingFace. A couple of examples were given, including integrating it with robotics.

"Isn't that incredible?", Jensen remarks, before mentioning that just a few years ago, it would have been impossible. Thanks to using a variety of applications, named an Agentic framework, Brev creates the architecture of applications across a closed sandbox.

— Sayem Ahmed

Full-stack Phsyical AI: Compute becomes data

Jensen is explaining how several computers, connected through Nvidia Omniverse, can create a full-stack AI platform through training (GB300), Simulation (RTX Pro), and inference (labelled THOR). By utilizing multiple models aligned with language, compute power has become data, Jensen says.

Synthetic data, grounded by physics, can be used in a Cosmos foundation model to become physically-based, digestible data to train a new AI platform. This could curtail the requirement for real-world training data for Physical AI platforms, aligning elements like trajectory predictions into real-world, usable data for training.

— Jeff Kampman

Nvidia Alpamayo: A thinking, reasoning AI model for vehicles

Powered by the Cosmos AI model, Nvidia has created Alpamayo, an AI model used for autonomous vehicles. It can reason every action: From the actions it's about to take, how it reasoned that action, and then developing a trajectory.

Huang claims that it's based on a large amount of human training and supplemented by Cosmos' synthetic data. The keynote has now shifted to a real-world example of the model working in action, with a car (in San Francisco) taking turns and making decisions on the fly. Huang notes that it's impossible to get every single possible scenario, but breaking these tasks down can be understood by the AI model if it reasons through it.

— Jeff Kampman

More Alpamayo - coming to Mercedes Benz CLA

"Not only does your car drive as you would expect it to drive, it reasons about every scenario and tells you what it's about to do."

The first AV car powered by Alpamayo is the 2025 Mercedes-Benz CLA, shipping to the U.S. in Q1. It has been rated as the world's safest car by NCAP.

How does Nvidia keep its car safe?

Nvidia says it has spent years building an entire AV stack that's fully traceable, running both stacks at the same time as a guardrail against accidents and scenarios you can't legislate against. A real shot across Tesla's bow.

"Use some Nvidia wherever you can"

Jensen says that in the next 10 years, a high percentage of the world's cars will be autonomous. Stating we can all agree that this market has very much arrived.

IT'S ROBOT TIME

The moment you've all been waiting for, it's time for Jensen's robot hour! Not just for entertainment, Nvidia says that the principles that underpin its Alpamayo stack for autonomous vehicles will also inform other AI industries, including robotics. This is great cinema.

"Nobody's as cute as you guys"

Caterpillar and Uber Eats, as well as Boston Dynamics, join Jensen on stage to showcase the different types of robots that Nvidia's AI stack is being use to train.

Industry acceleration

Jensen says that the full Cadence stack is going to be accelerated by Cuda-X, and that future robots will have their chips designed inside tools like Cadence and Synopsys.

"We're going to integrate Cuda-x deeply into the world of Siemens." The robots are jumping up and down on the stage now.

Powering industry

Nvidia says that as global labor shortages worsens, we need AI more than ever to power industry. Siemens is integrating Cuda-x, Omniverse, and AI models into its whole portfolio, of EDA, CAE, and digital twin tools and platforms, bringing physical AI to the full industrial lifecycle - design and production, simulation, and operations.

"Let's talk about Vera Rubin"

The successor to Blackwell takes the stage...

Insane Demand for AI computing

Jensen says the demand for AI is "skyrocketing," with model size growing by 10x parameters per year, test time scaling needs increasing 5x per year, and token cost becoming 10x cheaper per year. The latter signals the race that everyone is trying to get to the next level, which means it's a computing problem.

"We have to advance the state of computation every single year."

Vera Rubin is in full production

"I can tell you that Vera Rubin is in full production." Nvidia says it arrives just in time for the next frontier of AI.

"An order of magnitude every single year"

Vera CPU in all its glory, with 88 Olympus Custom cores, 227 Billion Transistors. Bottom right, two dejected robots leave the stage, no longer the center of attention.

Jensen says Nvidia has a rule: "No new generation should have more than one or two chips change." However, "the number of transistors we get year after year after year can't possibly keep up with the models, with 5x more tokens per year generated, it can't keep up with the cost decline of the tokens." Nvidia can no longer keep up with the demands of AI unless it innovates all of the chips, the entire stack, all at the same time.

"I think this weighs a couple of hundred pounds"

Jensen cracks a joke about the weight of Vera Rubin that absolutely bombs. More pertinently, building the Rubin chassis takes just five minutes, down from two hours. And it's 80% liquid cooled.

Vera Rubin vs Blackwell

Here's how Vera Rubin stacks up against Blackwell. Jensen tells another water-based joke: "It weighs two and a half tons today, because we forgot to drain the water out of it." A much better pop than his previous attempt.

"The power of Vera Rubin is twice as high as Grace Blackwell"

Despite the huge increase in power, cooling demands of Vera Rubin are the same, with no water coolers required. "We're basically cooling this computer with hot water."

Bluefield 4

"We created Bluefield 4 so that we could have a very fast KV cache memory store right in the rack." Jensen says everyone is suffering from storage issues, crushed under the amount of JV cache traffic moving around.

A giant leap

Nvidia says that Vera Rubin is "One Giant Leap to the Next Frontier."

With four Bluefields, 150TB of memory (presumably NVME), each GPU gets an additional 16TB of context memory. "This is crazy sh*t" - Jeffrey Kampman.

So how well does Vera Rubin perform?

As you can see, quite well. According to Nvidia, Vera Rubin throughput is through the roof compared to Blackwell, using 1/4th fewer GPUs in a time to train test of 100T tokens in one month. Rubin factory throughput is around 10x that of Blackwell, and with just 1/10th token cost.

And we are done!

Jensen leaves the stage, but says Nvidia will show us some outtakes of slides left on the cutting room floor. Yes, there are more robots.

And that is all for Nvidia! You can read the full announcement about Nvidia's biggest revelation, Vera Rubin, below:

Nvidia launches Vera Rubin NVL72 AI supercomputer at CES — promises up to 5x greater inference performance and 10x lower cost per token than Blackwell, coming 2H 2026

Nvidia chief Jensen Huang said that he’s uncertain whether Beijing would allow Chinese companies to purchase Nvidia chips if the company were allowed to sell them there. Huang said this in a statement to reporters after meeting U.S. President Donald Trump, where they talked about export control issues, according to Bloomberg. There has been some talk in Washington about the possibility of letting the AI GPU giant export its last-generation H200 chip to China, especially after Congress reportedly rejected the GAIN AI Act, which would have forced Nvidia to prioritize shipments to domestic companies.

“We don’t know. We have no clue,” Huang said when asked whether the company would be able to sell the H200 in China. “We can’t degrade chips that we sell to China, they won’t accept that.” The Biden administration has previously banned the export of this AI chip to Beijing, citing security concerns, especially its use in military applications. It was eventually replaced by the H20, which, even though it had limited capabilities versus Nvidia’s then top-of-the-line chip, still offered formidable performance.

However, even this AI GPU was banned in April 2025, resulting in a $5.5 billion write-off for Nvidia, before Washington allowed it to resume shipments some three months later. Things didn’t go well for the AI tech giant for long, though, as Beijing ordered its tech companies to stop purchasing the H20 in August in response to U.S. Commerce Secretary Howard Lutnick’s “addiction” comments. This has since expanded to a ban on RTX Pro 6000D GPUs as well, with the Chinese Communist Party (CCP) claiming that homegrown AI processors can now match Nvidia’s China-only chips. Because of these moves, Huang said that Nvidia’s market share in China has dropped from 95% to essentially zero in just a few years.

This talk of finally allowing Nvidia to export fully-fledged H200 chips into China legally would be a major win for the company, especially as Huang has been lobbying for this and has been vocal against export controls. Nevertheless, even if the White House finally allows Nvidia to sell the unshackled version of its Hopper GPUs, it still wouldn’t be a full 180 turn for Washington, as administration officials say that its rival can only have AI chips once they’re outdated. And while the H200 is still a relatively powerful AI chip, it has since been supplanted by the arrival of the B200 chips.

Nvidia chief executive Jensen Huang was allegedly recorded telling his people to use more AI while assuring them that they won’t get replaced by the tool. The head of the AI chip giant is reported to have said this during an all-hands meeting after its record-breaking quarter, which was leaked to Business Insider. The statements were reportedly made during the same meeting where he complained about the drop in Nvidia’s stock price despite performing absolutely well, with Huang saying that the market did not appreciate the company’s ‘incredible’ quarter.

“My understanding is Nvidia has some managers who are telling their people to use less AI. Are you insane?” Huang reportedly said in the recording. “I want every task that is possible to be automated with artificial intelligence to be automated with artificial intelligence. I promise you; you will have work to do.”

This push to use more AI tools has been happening across the industry, especially among massive tech companies like Meta and Microsoft. These two giants have been mandating their employees to use AI, with the use of such tools becoming a part of their evaluation. Business Insider also reports that Google has instructed its engineers to use AI for coding, while Amazon employees have requested the company to adopt AI coding tool Cursor.

On the other hand, the widespread adoption of AI has made most employees wary of being replaced by machines. Even experts and industry leaders have been warning about this trend: Ford CEO Jim Farley said that it could wipe out half of white-collar jobs in the U.S., while Anthropic CEO Dario Amodei said that it could cause up to 20% unemployment in the next half-decade. A Massachusetts Institute of Technology and Oak Ridge National Laboratory study even created a labor simulation tool that estimates that up to 11.7% of workers are in danger of being replaced by AI.

Nevertheless, Jensen Huang has reportedly reassured his employees that they are not in danger of being supplanted by this technology. Despite implementing the use of AI tools, Nvidia has continuously been hiring people, bringing in over 6,000 new faces in its last fiscal year. And amid the increasing tech industry layoffs, Huang says that the company probably needs about 10,000 more staff members.

It makes sense for Huang and Nvidia to push their people into using AI. After all, it’s the reason that the once-gaming GPU maker has become the first company in the world to hit a $5-trillion market capitalization. But it’s just a tool that can enhance the productivity of employees, not something that should replace them entirely.

Nvidia CEO Jensen Huang has reportedly told Nvidia employees in a leaked all-hands meeting that “the market did not appreciate” the AI giant despite the company’s record-breaking quarter, according to Business Insider. The company’s stock price slid from around $195 to a low of $180 just one day after it released its quarterly earnings, which is a surprise given Nvidia’s performance. This meant that its market capitalization dropped from its all-time high of $5.12 trillion to around $4.4 trillion, with the company losing around $365 billion in just one day of trading.

It seems that this movement is driven by fears of an AI bubble, something that many experts and analysts, including former Intel CEO Pat Gelsinger, have been warning about. “If we delivered a bad quarter, it is evidence there’s an AI bubble. If we delivered a great quarter, we are fueling the AI bubble,” Jensen said during the meeting. He also added, “If we delivered a bad quarter, if we’re off by just a hair, if it just looked a little bit creaky, the whole world would’ve fallen apart.”

Nvidia has quickly grown from a relatively unknown company familiar only to gamers to becoming the most valuable company in the history of the world. This is largely driven by the massive demand for AI chips, as many companies, even nations, are racing for technological supremacy in this field. Because of this, it has arguably become the cornerstone of advancements in artificial intelligence. “You should’ve seen some of the memes that are on the internet,” the CEO said. “We’re basically holding the planet together — and it’s not untrue.”

Despite its market and technological leadership (or because of it), Huang has admitted that it has been harder for Nvidia to meet expectations. This is seen with the recent changes in the company’s stock price, which has been trending down since it peaked at over $200 in late October and early November. However, this movement is seemingly driven more by investor jitters rather than Nvidia’s performance, especially as it reported that all its data center GPUs were sold out during the quarter. It also expects the sales blitz to continue well into 2026, with the company forecasting its 4Q26 revenue to hit $62 billion.

In a statement of response, an Nvidia spokesperson told Tom's Hardware, "After another quarter of incredible growth and off-the-charts demand, Jensen’s message to the company was to stay focused and let the market take care of itself."

TSMC Chairman and CEO C.C. Wei was joined at the firm’s annual Sports Day event by Nvidia’s Jensen Huang this weekend. However, to our surprise, Wei’s footwear managed to upstage any Jensanity. Wei's custom-made TSMC-branded sneakers were “the focus of the audience” at the event, according to an ‘exclusive’ Mirror News report (associated video in Mandarin Chinese, embedded below).

According to the source, Wei thought these unique running shoes were a gift from the company. However, later in the report, an interview with a shoemaker from Kaohsiung, the biggest city in the south of the island, reveals that the shoes worn by Wei were part of a business pitch made back in 2017.

The Kaohsiung shoemaker was reportedly quite taken aback to see his TSMC sneakers highlighted by the media this weekend. Mirror News says the man felt "shocked" and "super surprised" (machine translation) when the sneakers caught the attention of Sports Day attendees this weekend.

Holding aloft detailed cobbling plans for the sneakers, the shoemaker alleged that he sent the sample, as worn by Wei, to then-Chairman Morris Chang, as part of a business proposal eight years ago. Like TSMC silicon, the maker of the sneakers seems proud that their footwear is still Made in Taiwan (MIT). Many rivals have moved a lot of production to China to reduce costs.

We can’t vouch for the sneaker quality, but we guess they still look like new after eight years in storage. The news video says that they feature special stitching for 10-year sole adhesion durability.

Both TSMC’s Wei and the Kaohsiung shoemaking firm hinted that a closer collaboration may be on the way. The TSMC boss told reporters that sneakers with the company branding may become official merchandise in the future. Meanwhile, the MIT shoemaker says he has plans to put together a new proposal for TSMC’s consideration.

In the footsteps of Microsoft & Adidas, Apple & Nike, Nintendo & Puma, Sony & Nike

We hope the TSMC sneakers collab goes ahead this time. Shoes are super-collectible and sought after. Tech giants and sports brands have had particularly rich partnerships, like Microsoft (Xbox) & Adidas, Apple & Nike, Nintendo & Puma, plus Sony (PlayStation) & Nike.

The footwear would join plenty of other unlikely collaborative products available in the factory shops at TSMC facilities. In recent years, we have reported on TSMC-branded merchandise like snacks, honey, dumb-phones, suitcases, and there are various bags, cups, and more that you can find being sold on online marketplaces like Shopee in Taiwan – useful for those without TSMC employee retail access.

We’d also like to see a TSMC fab toy building set to rival the ASML and Lego collaboration, or the SK hynix and Oxford (a Korean Lego-type product) sets.

The Select Committee on China of the U.S. House of Representatives has called out Nvidia CEO Jensen Huang, pointing out on X its claims that Nvidia has been sharing its Santa Clara campus with Futurewei, a subsidiary of blacklisted Huawei. The committee has previously demanded that Futurewei reveal details about its connection with Huawei and its American operations, while also pointing out its close proximity to Nvidia’s offices for years. While not directly accusing Nvidia CEO Jensen Huang or Futurewei, the committee highlighted the strategic implications of this co-location. We have reached out to Nvidia for comment.

“Our Select Committee letter earlier this year documented how Nvidia shared a campus with Futurewei, a blacklisted Huawei affiliate,” the committee said in the post. “China may be ‘nanoseconds behind’ in AI, but for years it was in Nvidia’s backyard.” This was made in response to Huang’s comment that “China is going to win the AI race,” and his following statement saying, “As I have long said, China is nanoseconds behind America in AI. It’s vital that America wins by racing ahead and winning developers worldwide.”

According to the letter (PDF) the House Committee sent, Futurewei remains closely linked to Huawei despite distancing itself from the embargoed company on paper. Although it presents itself as an independent U.S. entity, its actions on the global stage allegedly point toward giving its former parent company and Beijing an advantage in global technological standards.

There were also concerns that the company was being used for or directly conducting industrial espionage, with the letter citing a civil case alleging that its employees “register using fake U.S. company names to infiltrate into the meeting, then compiled reports that were transferred to product development, strategies teams, and executives in China” after Huawei was banned from a private telecoms summit hosted by Facebook.

The lawmakers were probably pointing out that Nvidia has been taking advantage of the massive AI demand on both sides of the race, which has helped it become the world's most valuable company by market cap. Members of the federal government want to limit China’s access to American hardware, especially as they think that Beijing uses it for its own technological advancements in both civilian and military applications. On the other hand, Huang thinks the U.S. should let the entire world use its technology — that way, the backbone of global AI infrastructure will be built on American hardware, specifically Nvidia hardware.

There might be some truth to both sides of the argument, but Jensen’s take also benefits his company. After all, if Nvidia supplies most of the data center infrastructure on both sides of the AI race, then it’s a definite win for the AI giant and its investors.

Even as the head of the world's first five trillion dollar company, this week hasn't been great for Nvidia CEO Jensen Huang. Despite all his efforts, President Trump did not discuss the sale of advanced Nvidia GPUs with Chinese Premier Xi Jinping this week, nor did he give the official go-ahead for Nvidia to develop and sell a cut-down version of its flagship Blackwell GPUs.

The ongoing trade war between the two world's largest economies has Nvidia stuck in the middle, with the U.S. looking to maintain its technological lead, while Nvidia seeks to maintain its strong software and hardware position in Southeast Asia to fight off a growing domestic chip industry in China.

For most of this year, the goals of the U.S. government and Nvidia have been mostly aligned, leading to enormous deals for the GPU manufacturer, including government contracts and stakes in government-owned businesses. But as China and America have become more entrenched in their trading positions, both have begun to move towards domestically controlled supply chains of the latest chip designs, leaving Nvidia facing a waning Chinese market share.

From diffusion to dissilution

Nvidia has been selling GPUs to China for a long time, but while it was previously mostly related to gaming and cryptocurrency mining, the growth of the AI industry has made these sales more crucial and the fallout more dramatic. Export controls put in place in 2022 curtailed its sales of its latest GPUs to China, but Nvidia has made bespoke models like the H20 and 5090D that offer reduced performance compared to the flagship models it sells in Western markets.

That continued in 2025 with the introduction of the AI Diffusion rule, which was designed to restrict Nvidia's sale of its top chips to China and other blacklisted countries around the world. This was ultimately pulled by the Trump administration mere days before it was set to become enforceable, but since then, it has swung back and forth, allowing sales, then disallowing them. Right now, Blackwell GPUs remain off the table for China, at least for now.

Even with Nvidia praising the administration for its stance on AI and global sales, the U.S. has maintained an antagonistic stance towards China on trade with various tariffs and policies, often brandishing access to Nvidia GPUs as a bargaining chip in negotiations.

China's response has been strong, cutting international companies' access to its domestic manufacturing facilities, and pushing for its own firms and government offices to utilize as many domestically produced chips as possible. Huawei has developed a rack-scale CloudMatrix 384, which is being pushed by the Chinese government, though it is not as efficient as Nvidia's latest offerings.

Both China and the U.S. are driving toward chipmaking self-sufficiency, or at least more self-controlled supply chains. For Nvidia, this has led to a waning of the company's influence in China. Access to its hardware is simply unreliable, so countries and companies are looking for alternatives, and the Chinese government is pushing companies toward homegrown chips.

The CUDA stronghold is under siege

CUDA has Nvidia's proverbial moat, shielding it from attack, and welcoming users into its castle gates. The software stack has become so ubiquitous in various industries that Nvidia GPUs are all but required for everyday use. Although competitors do exist, and AMD's hardware is by many measures, almost as capable as Nvidia's. But, without CUDA support, it's a major headache for companies to move to a new standard.

That's the business approach that Nvidia has taken globally, too. As hyperscalers deploy huge AI data centers to AI workloads, it wants their GPUs at the heart, supported by other crucial technologies like NVLink Fusion and ConnectX, just to name a few. This is to ensure Nvidia's long-term dominance in the data center segment.

With around half of the world's leading AI developers living and working in China, Nvidia wants those users working with its GPUs, harnessing the CUDA platform. But if those developers can't get Nvidia GPUs, they can't use CUDA, meaning that they'll use something else. We saw the first examples of how quickly this can happen at the end of September, when the latest DeepSeek model included support for China-native chips and the CANN platform, developed by Huawei.

CANN is also open source, which will aid in its adoption in China and elsewhere, and industry alliances of Chinese AI firms may help to consolidate their efforts in pushing away from Nvidia's near-monopoly.

Though DeepSeek still supports CUDA, its developers are encouraging users to leverage the TileLang kernel for prototyping instead. Although these models and the associated domestic hardware may not be as capable as Nvidia's platforms yet, China has a number of levers it can pull to make them more competitive.

Long-term investments from China make it clear that it wants to control its own destiny when it comes to the latest hardware. Its domestic chip suppliers are ramping up, and the investment is there to help that continue. But it will take time, and until that inflection point happens, Nvidia wants to have enough of a foot in the door that its relevance will never evaporate completely. Unfortunately for Nvidia, the U.S. government is loosening the company's control.

China is still behind

China purchased most of the million-plus Nvidia HGX H20 GPUs that were produced last year, and GPUs were also smuggled into the country. DeepSeek R2 was trained using Nvidia chips, despite a push by the authorities to use domestic chips instead. China's chips cannot compete when it comes to training workloads quite yet.

If Nvidia has one saving grace, it is that the chip industry is enormous, expensive, and takes time to change. China may want its own domestic chip supply, and it may have a decent AI development framework, and its hardware may even be pretty good for inference, even if it's not quite as efficient. But there's no denying that Nvidia and other Western companies are years ahead of even China's best, likely due to the lack of advanced EUV lithography machines, which are required to develop the latest cutting-edge nodes.

There are plenty of reasons that China views Taiwan through such hungry eyes, and access to tools which can produce the most cutting-edge process technologies is undoubtedly one of them. Even if China can convert a huge portion of its AI industry to using domestic chips and push for the development of its own domestic supply chains, those are going to take years to build up, and without ASML's advanced tools, they may be on the back foot. But, how long that will hold up for remains to be seen.

Nvidia CEO Jensen Huang says Washington has lost its edge in artificial intelligence and warns that China will win the AI race. He cited the West's cynicism, export controls, and favorable energy circumstances in China as the reason, claiming it is much easier for companies to access energy in the country.

The chief of the most valuable company in the world by market cap has long been saying that the U.S. ban on chip exports is a failure, and that the spread of its advanced semiconductors is vital for it to retain its competitive advantage globally. However, the ongoing trade war between the two powers has resulted in export bans of Blackwell chips from the White House on the one hand, and the CCP banning foreign AI chips from state-funded data centers on the other. Because of this, Nvidia’s market share in China has since dropped to basically zero, which probably led to Huang’s statement to the Financial Times.

“China is going to win the AI race,” Jensen commented. He also added that “we need more optimism,” saying that the West’s cynicism is holding it back. Huang released a statement on Nvidia’s X account a few hours after FT published his words. “As I have long said, China is nanoseconds behind America in AI. It’s vital that America wins by racing ahead and winning developers worldwide.” The Nvidia CEO previously mentioned this in late September on a podcast, leaning on his stance that he’s been preaching for over a year that export restrictions on his company’s AI chips are detrimental to the U.S.’s long-term interests.

Huang argues that if China loses access to Nvidia’s latest AI GPUs, its tech companies will be forced to purchase homegrown alternatives, which will pour money into its chip makers and further drive research, development, and innovations in the local semiconductor industry. Aside from that, it will also reduce these companies’ dependence on Nvidia’s software ecosystem, making it easier for them to migrate to a Chinese AI processor. On the other hand, other industry leaders contend that the U.S. is heavily dependent on China and that it’s only using Nvidia’s products as a stopgap until it builds a credible competitor to the AI chip powerhouse. The comments come just days after the administration hinted that China could have access to Nvidia Blackwell chips, but only once they are out of date.

Aside from export controls, Nvidia’s top executive also highlighted China’s approach to energy subsidies that make it easier for companies to put up power-hungry data centers, versus the hodgepodge of rules the different States in the U.S. are pushing on AI, potentially resulting in “50 new regulations.” Experts have been saying that electricity generation is the next bottleneck that the AI industry must solve, and it seems that Beijing is miles ahead, as it has already addressed the energy problem for its AI infrastructure. On the other hand, American tech companies are still investing in alternative power sources like small modular reactors and space-based data centers, which will take years to materialize, if at all. Recently, Microsoft revealed it has GPUs it simply can't plug in because it doesn't have the energy required.

The status of the AI race between the two global rivals isn’t clear, especially as politics and protectionism are muddying the waters. Aside from that, both sides' arguments for and against China getting access to Nvidia’s AI GPUs have merit, meaning we will probably only truly see who is right years down the line. But one thing is clear in all of this — Nvidia will get a massive advantage if it supplies the chips that both sides use in the AI race.

Korean fried chicken stocks were given a significant boost today by a new not-so-secret ingredient – a sprinkling of Jensanity. Nvidia CEO Jensen Huang was in Seoul meeting top execs at firms such as Samsung and Hyundai, reports Bloomberg. That’s big news on its own, but photos and videos of Huang enjoying the local fast food staple of spicy chicken, with a few beers, went viral, and KOSDAQ-listed Korean fried chicken brands saw their shares rise by as much as 20% or 30% this morning.

A different kind of ‘KFC’

Jensen Huang was pictured alongside Samsung’s Jay Y. Lee and Hyundai’s Chung Euisun at Kkanbu Chicken, in what has become a signature style of outing for the Green Team chief, appealing to the common man. Huang reportedly joked, “This is very good for your health, right?” with reporters outside the restaurant.

But what makes Korean fried chicken worth a taste test, or even preferable versus rival styles like the iconic American KFC?

As someone who enjoys an occasional piece of Korean fried chicken, I’d explain it to the uninitiated as a more crunchy than usual fried chicken style, with an intense spicy kick, sticky, sweet and sour tastes, and umami sauciness. The nearest Western-known sauces that may contribute to the signature flavor (but not the spice) would be Worcestershire sauce and/or OK sauce.

Jensanity - Huang’s Midas touch reaches beyond silicon

While Kkanbu Chicken isn’t publicly traded, peers like Kyochon F&B surged on the stock market by up to 20% in the day’s trading. Jensanity is infectious, and Bloomberg noted that related industry players like Cherrybro Co., a poultry processor, saw shares climb up to the daily limit of 30%. Another beneficiary of the viral fast food meeting was Neuromeka, a chicken-frying robot maker.

It is noted that Korean investors are characteristically easily influenced by risky trades, chasing short-term gains on the back of cultural, political, and meme-worthy events. Bloomberg cites U.S. President Donald Trump’s recent visit to South Korea, where he praised the host’s pen, sparking local pen maker MonAmi Co’s share to surge, as evidence of this phenomenon.

What was the Nvidia CEO even doing in S. Korea?

Huang was in South Korea to attend the APEC CEO Summit. During the important industry event, the Nvidia CEO unveiled new contracts to supply AI chips to major South Korean companies, says Bloomberg. He will have also been in the country to solidify agreements with AI and semiconductor players to counter the unpredictable China sanctions situation.

Palantir CTO Shyam Sankar said that the U.S. should end its dependence on China, and that the first thing it should do is to recognize its dependence is a problem. According to his opinion piece in the Wall Street Journal, the U.S. and China are already engaged in an economic war with each other, and other people should wake up to this reality. However, Sankar says that many business leaders still refuse to see this, and still wholeheartedly believe in the Chinese message of its "peaceful rise."

The opinion piece points out that Nvidia CEO Jensen Huang recently expressed his opinion that the label 'China hawk' is not a badge of honor Americans should wear, it is really 'a badge of shame.' Huang also said it "doesn’t have to be all us or them. It could be us and them."

Mulling over the Nvidia CEO's philosophy, the Palantir CTO wrote, "The first step to ending our dependence on China is admitting we have a problem." Sankar continued, "We can continue as useful idiots, decrying ‘China hawks’ who point out that we’re funding our own demise. Or we can wake up to the reality that we’re already in an economic war in which every purchase and investment will help determine which system survives."

While Sankar does not directly call out Huang as a “useful idiot,” the implication is certainly there, given his reference to the Nvidia CEO's comments. The Nvidia CEO has always been against export controls on the most powerful chips, saying that such a move could backfire against the U.S., as it would allow Chinese companies like Huawei to define global standards.

Instead, Huang wants his chips to be readily available in China, so that American technology can become the backbone of global AI technology. We should note, though, that China used to be Nvidia’s biggest export market, where it once had 95% market share — it has since dropped to zero because of export controls and the ongoing trade war between the two global rivals.

Sankar’s take on this is that China is just using foreign companies to support its goals until it can develop a credible home-grown challenger. These companies would then flood the global market with cheaper goods, while, at the same time, Beijing is taking steps to limit the access of the original foreign business to the Chinese market. He does not lay the blame on China alone, though.

American companies complicit

American companies have been an undeniable part of China's growth, with juggernauts like Apple, Tesla, Intel, General Motors, Procter & Gamble, and Coca-Cola, among others, investing heavily in the country. This massive inflow of cash, technology, and know-how has allowed it to rise and become the leading global manufacturer. In fact, some experts say that companies stay in China not because of cheap labor, but because it’s the only country that already has the necessary supply chain in place to build the latest technology.

Sankar argues that the U.S. should face this development head-on by rebuilding the industrial base it has let slide. While Washington does not have to completely stop trade with China, it does have to take steps to build alternative markets and supply chains to avoid so that it has alternatives and not be left with no choice but to comply with Beijing’s demands.

The Palantir CTO argues that the current situation will only get worse if the U.S. does not take action today, but there are still quite a few who refuse to see this. On this point, he quoted Upton Sinclair: “It is difficult to get a man to understand something, when his salary depends upon his not understanding it.”

This will be a long and arduous road, though, especially as many are already used to cheap goods coming from China. But it’s only with that realization that the United States can take the painful but necessary steps to ensure that it remains sovereign in the face of Beijing’s goal to overtake the US in global supremacy.

Earlier this week, Nvidia’s DGX Spark AI mini-PCs were released to the masses. Symbolic of the splintered state of the AI industry, though, Nvidia’s CEO Jensen Huang hand-delivered DGX Spark systems to Elon Musk and Sam Altman — separately. Altman and Musk once worked closely together, for a common cause, as co-founders of OpenAI, where Jensen once hand-delivered the original DGX-1 nine years ago, long before the AI boom began.

The last time we saw such a star-studded DGX photo-op was when Huang hand-delivered the original DGX-1 to Elon Musk, in his role as co-founder of non-profit OpenAI. Once partners seeking to further the development of safe AI for the benefit of humankind, Musk and Altman have become the fiercest of rivals. The rivalry isn’t very sportsmanlike, either, with the pair now regularly trading barbs and public insults, and even engaging in some acrimonious legal tussles. Since 2023, we have also had two distinct competitive AI products addressing the same market, albeit from different angles: ChatGPT and Grok.

Musk received his DGX Spark while wearing his ‘Chief Engineer at SpaceX’ hat. Huang quipped that he was “delivering the smallest supercomputer next to the biggest rocket,” at the Starbase, Texas facility.

We are reminded by the Nvidia blog that the GB10 Grace Blackwell Superchip-powered DGX Spark packs 128GB of unified memory and delivers a petaflop of AI performance. It is claimed to have enough resources and muscle to run models with 200 billion parameters locally. Moreover, the Green Team’s blog highlights that it has been nine years since Huang personally delivered the DGX-1 to Musk at OpenAI.

Sam Altman also reminisced about Huang’s previous little parcel. “Things have come a long way since the delivery of the DGX-1 9 years ago; amazing to see...” mused the OpenAI boss. Altman was commenting on the President and co-founder (another one) of OpenAI, Greg Brockman's, shared photo. The picture shows Huang nestled between Brockman and Altman.

The Jensen-powered delivery service

Huang famously started his career washing dishes, bussing, and waiting at Denny’s. Now he’s back as a server, but on the menu are slices of AI-accelerating silicon, delivered in person to a select few fellow tech industry giants.

Nvidia’s Jensen-powered delivery service isn’t standard, even though the DGX Spark has gotten a third more expensive since it was first announced. The Nvidia first-party DGX Spark MSRP is now $3,999, and it is shipping direct from Nvidia, Micro Center, and a number of partners.

The first batch of DGX Spark systems was also put into the hands of researchers at AI-processing hungry companies like Anaconda, Cadence, ComfyUI, Docker, Google, Hugging Face, JetBrains, LM Studio, Meta, Microsoft, Ollama, and Roboflow.

If you are interested in the DGX Spark, and its integrated Nvidia AI stack with full CUDA library support, the firm’s partners are also cooking up systems, featuring their own special saucy tech - but they all look fairly similar. DGX Spark systems are being made and marketed by Acer, Asus, Dell Technologies, Gigabyte, HPI, Lenovo, and MSI. You definitely won’t get Jensen-powered delivery with these, though, you’d be lucky to get a free MSI dragon plush toy.

Two weeks ago, Nvidia CEO Jensen Huang made a surprise visit to Taiwan where he met TSMC for a few hours. It was a short stay but it sparked customary rumors pertaining to why he was there. Originally, it was thought to be just a routine check-up on the upcoming Vera Rubin chips that TSMC is manufacturing for Nvidia. However, amidst the thought pool, a report had claimed that Huang was actually there to deliver a message from President Trump over revenue sharing — a claim that has now been shut down by TSMC.

Earlier in August, the Trump administration struck an informal deal with semiconductor companies such as AMD and Nvidia to share profits. In exchange for permission to sell their chips in China, these companies would give 15% of the profit to the government. TSMC, so far, does not fall under this arrangement and that's where the original rumors stem from. Jensen's visit was claimed to be moonlighting as an envoy for the U.S. government, conveying some sort of message through a mutually important liaison.

Nvidia CEO Jensen Huang is back in Taiwan for weighty negotiations with contract chipmaker TSMC. The talks are thought to be related to the new China-specific B30 chips using the Blackwell architecture. No matter the gravity of the talks, though, the Nvidia head enjoys a very cordial relationship with CC Wei, the CEO of TSMC. Their warm relationship is made clearly apparent in a video showing the two billionaires joking about who will pay the bill for dinner.

(click ‘see more’ to watch the video of the tech titan pals)

With these incredibly serious negotiations probably still some way to go, the two tech leaders enjoyed dinner in Taipei. In the video, you can see them standing closely with Huang’s arm around Wei’s shoulders.

After Huang’s introduction, and explanation that he has been in meetings with “TSMC’s world-class leaders,” earlier in the day, Wei took his turn to speak. “Let me say that we have the honor to have this four trillion NT guy to be my guest.” The sum of four trillion NT Dollars is about USD $130 billion, and is obviously a reference to Huang’s fortune.

Then, Wei started to ruminate about the precise value of his fellow CEO’s wealth, only to be told by Huang to “stop that!” And, as a quick retort to hide his embarrassment, the Nvidia CEO shot back “Still, you’re paying for dinner!”

We get a sense, next, that negotiations are not yet finalized. Wei responded to the dinner bill tease by saying that he was “not bothered [about the bill], as long as you agree with my wafer price.” The video segment ends with the Nvidia CEO laughing, “I agree with your wafer price.”

The White House plans to allow Nvidia to sell its H20 AI GPUs to China once again, signaling a significant victory for the company after it suffered a $5.5-billion write-off when they were banned for export to China in mid-April. The company confirmed to Tom’s Hardware that “The U.S. government has assured Nvidia that licenses will be granted, and Nvidia hopes to start deliveries soon.”

The company announced the China-specific H20 AI GPUs in late 2023 after Washington banned its most advanced H100 and H200 models for export to China. However, the Biden Administration’s AI diffusion rule, and then more targeted measures from the Trump administration, threatened to ban even these defanged GPUs, which were still quite popular among Chinese customers. Nvidia CEO Jensen Huang reportedly spent $1 million on a dinner with the president to have the plan suspended, but the White House banned their export a week later anyway, a measure affecting both the Nvidia H20 and AMD MI308 AI chips.

Jensen Huang has been vocal against the ban that the U.S. is placing on advanced AI chips, an area dominated by his company. The CEO has said many times that AI chip export control is a failure and that the Chinese military will avoid American tech for its development. Instead of limiting who has access to its technology, he says that it should do the opposite and allow American AI tech to spread far and wide — or else it risks losing the lead to its Chinese competitors like Huawei.

H20 export license approvals resumed a month after the U.S. and China negotiated a preliminary trade deal amid prolonged tariff tensions. Some of the developments between the nations include the resumption of rare earth metal exports to the U.S. in exchange for the lifting of the EDA export control. Nvidia says that CEO Jensen Huang has been flying between Washington, D.C., and Beijing, meeting with officials and policymakers to emphasize “the benefits that AI will bring to business and society worldwide.” It seems that his lobbying between the two parties has been successful with this approval, although we won't know for sure until the licenses are officially granted. Nvidia will be hopeful it can resume H20 sales without a hitch.

We should note, though, that this doesn't appear to be a blanket lifting of the ban — instead, it’s just a promise that Washington will start approving export licenses for the H20 GPU. It’s likely for this reason that the company announced the fully compliant Nvidia RTX Pro GPU, which “is ideal for digital twin AI for smart factories and logistics.” The company was also reportedly preparing a cut-down HGX H20 GPU in response to the original ban, which wouldn’t have any sort of restriction placed on it.

Nvidia CEO Jensen Huang has downplayed Washington’s concerns that the Chinese military will use advanced U.S. AI tech to improve its capabilities. Mr. Huang said in an interview with CNN that China’s People’s Liberation Army (PLA) will avoid American tech the same way that the U.S.’s armed forces avoid Chinese products.

This announcement comes on the heels of the United States Senate’s open letter [PDF] to the CEO, asking him to “refrain from meeting with representatives of any companies that are working with the PRC’s military or intelligence establishment…or are suspected to have engaged in activities that undermine U.S. export controls.”

Washington is concerned that the PLA might utilize this to develop advanced weapons systems, intelligence systems, and more, prompting a bipartisan effort to deny China access to the most powerful hardware over the past three administrations. However, Huang has often publicly said that the U.S. strategy of limiting China’s access to advanced technologies was a failure and that it should lead the global development and deployment of AI.

“…Depriving someone of technology is not a goal, it’s a tactic — and that tactic was not in service of the goal,” said the Nvidia CEO during the interview. “Just like we want the world to be built on the American dollar, using the American dollar as the global standard, we want the American tech stack to be the global standard.” He also added, “In order for America to have AI leadership, it needs to make sure the American tech stack is available to markets all over the world, so that amazing developers, including the ones in China, are able to build on American tech stack so that AI runs best on the American tech stack.”

When Zakaria asked him about the Chinese PLA’s use of this tech, Jensen said that it’s not going to be an issue. “The Chinese military [is] no different [from] the American military: [they] will not seek each other’s technology to be built on top [of each other]. They simply can’t rely on it — it could be, of course, limited at any time,” Jensen answered. “Not to mention, there’s plenty of computing capacity in China already. If you just think about the number of supercomputers that are in China, built by amazing Chinese engineers, that are already in operation — they don’t need Nvidia’s chips or American tech stacks in order to build their military.”

Despite what he says, China has been heavily investing in AI data centers, and companies within the country are explicitly sourcing Nvidia’s most powerful products, even the ones that the U.S. has put export controls on. And even though Huang said that there’s no evidence of AI chip diversion, it’s widely reported that you can easily get these banned chips in the Chinese black market, with one businessman even showing off his smuggled GPUs on social media.

Chinese operators of these smuggled AI chips would have a harder time getting firmware updates and likely won’t have access to Nvidia’s advanced cloud tools and enterprise platforms. However, because Nvidia still sells export-compliant GPUs to China, the platform and cloud software can still potentially work with the banned higher-power equipment.

Aside from that, it will probably be difficult for the U.S. to disable these AI GPUs remotely, if it comes to that. After all, Nvidia would have a harder time selling its chips if a way to disable them remotely exists — that’s why the U.S. has a bill in the works that could force geo-tracking tech on high-end hardware. Even if there is such a technology, China can just air gap the systems to prevent them from being remotely killed.

Nvidia CEO Jensen Huang made himself available for media interviews in the wake of the publishing of its record $44 billion revenue financials and the traditional analysts' call. Bloomberg has shared its on-air Q&A session with Huang, in which the Nvidia boss was questioned about the impact of U.S. policy on his company's recent revenue. However, when specifically addressing President Trump’s tariffs and decision to rescind the AI Diffusion Rule, Huang couldn’t have been more extravagant with his personal praise.

After Huang’s gentle criticism of U.S. policy regarding exports of technologies that could accelerate AI, the Bloomberg journalist got more specific about the U.S. administration’s policies. Specifically, he asked the Nvidia CEO about his trust of President Trump, and the direction things were going in.

“Obviously, I don’t know all of his ideas, but let me tell you about two that are incredible,” answered Huang. "The first one is utterly visionary. The idea of tariffs being a pillar of a bold vision to re-industrialize to onshore manufacturing and motivate the world to invest in the United States is just an incredible vision. I think this is going to be a transformative idea for the next century for us, explained the Nvidia CEO. "We're all in on the idea. We're setting up plants and encouraging our partners from around the world to invest in the United States, and we have a lot of stuff going on, and so I'm very excited about that."

Some more outpourings of praise followed. Huang was perhaps hoping to influence any forthcoming decision(s) which would fill the vacuum caused by the AI diffusion rule being rescinded. "The second major idea is to rescind the AI diffusion role, recognizing that this isn't about limiting American technology, but this is about accelerating American stacks around the world to make sure that, before it's too late that the world builds on American stacks during this extraordinary time, the AI era."

Yet more praise was lavished on the U.S. president to underline Huang’s admiration. He ended this segment by saying, "These two initiatives are completely visionary, and it's going to be transformative for America."

The interview with Huang also covered how Nvidia successfully made up for lost China revenue streams. The Nvidia CEO snappily replied, “We have a whole bunch of engines firing right now,” illustrating the appeal of a broad base and wide customer portfolio. He also took the opportunity to blow the Nvidia tech trumpet, adding, “people realize that Blackwell is a home run.”

Still on the topic of China, Huang lamented the loss of U.S. influence in the AI industry there. He reminded the interviewer that the Chinese market is very important for its absolute size, and that it is still home to maybe 50% of the world’s AI researchers. Naturally, developers there are pivoting to Huawei, for example. That’s an “unfortunate part of changing policy,” said Huang, but he hoped things would change so U.S. tech could again become a desirable standard.

Following Nvidia's keynote at Computex 2025, Nvidia's CEO, Jensen Huang, sat down with journalists to talk about all of Team Green's latest announcements, including talk of GB200, and international market opportunities.

In response to one question, Huang talked about export controls which were first imposed by the Biden administration saying that the limitations had caused Nvidia's China Market share to be cut from 95 to 50 percent within in the presidency and hadn't accomplished what they set out to do. He also posited that the restrictions did not prevent China from developing its own, competing technologies.

Huang also talked about the massive write-downs his company had to take because of bans on the H20, saying "export controls resulted in us writing off multiple billions of dollars. Then, write off the inventory. The write-off of H20 is as big as many semiconductor companies."

He later praised the Trump administration for ending Biden's AI diffusion rule, saying "I think it's really a great reversal of a wrong policy."

This was a roundtable talk with several other journalists from other publications, but this is not a complete transcription of the entire Q&A. However, we've transcribed all of the questions we did manage to hear, some elements lightly edited for flow and clarity. Some speakers did not have clear audio while speaking, and we have noted as such on the transcript.

Ahead of reading this Q&A, you should familiarize yourself with what Huang announced at Nvidia during his Computex 2025 keynote, we've popped it down below, just so you can get a refresher.

Jensen Huang: Good Morning, very nice to see all of you. Did you guys see all of this? Isn't this just incredible?

So, this is the motherboard of a new server [Presumably the GB200 NVL72, or RTX Pro machine], and this server has many GPUs that are connected. The GPU's are connected on the bottom, or on top. And on the bottom are switches that connect all the GPUs together, and these switches also connect this computer to all the other computers, using CX8 networking (Nvidia ConnectX-8), 800 gigabits per-second, and then the transceivers plug in right there... Plug this into that, now you have an enterprise AI supercomputer. Because this system is air cooled, it's very easy for enterprise [users] to buy. It's available from all over the world's enterprise IT OEMs. Every single company will be offering this, and you can use this for everything.

It runs x86, so all of your software that you run with your enterprise IT works today. You can run Redmap, VMWare, Nutanix, so all of the orchestration and operating system works just fine.

And, you can run computer graphics, you can run AI, you can run agents. This is incredible. This one idea that the GPU... they didn't give us a GPU [To showcase], but you know what one looks like, it's the gold one, and that makes it a new server.

So, this is the RTX Pro Enterprise AI server, and this is a huge, huge announcement, and it opens up the enterprise market. As you know today, all of the AI isn't involved, but OEMs would like to serve the enterprises, companies would like to build it for themselves.

And so anyway, that's a very big announcement. So Cloud AI over here and GB200, that's our enterprise AI system.

Right, whose got the first question? Good morning.

Elaine Huang, Commonwealth Magazine: Just like what you mentioned, that enterprise is a very important market, and everybody talks about not just AI servers, but AI PCs. So what are the potential opportunities that Taiwan has to co-work with Nvidia for upcoming features?

Jensen Huang: Last night, Microsoft announced Windows ML, Windows Machine Learning. Machine Learning is AI, so Windows AI. And, they announced it on Nvidia. So now Windows ML, which is a new API [that] runs AI inside Windows, runs on Nvidia.

And, the reason for that is Nvidia's RTX has CUDA and Tensor cores, everyone one of them, exactly the same. We have several hundred million RTX PCs in the world. RTX equals AI, and now Windows ML runs on RTX. Everyone with RTX? They know. Hundreds of millions of gamers and PC users, workstation users, everybody. Laptop, desktop... Bingo! Home run, job done [laughs], Windows ML.

If you're a developer, and you would like your own AI supercomputer so that you don't have to keep going to the cloud, open the cloud, and when you're done, you know, shut down your session, because if you don't shut it down, the bill keeps running. And so maybe you're doing development, there's a lot of idle time. And so, you would not like to do that on the cloud, you would like to do it on your desk.

So, if you have a Mac? No problem. If you have a Chromebook? No problem. If you have Linux? No problem. If you have Windows? No problem. We have a perfect little device for you.

[We want] To give you this little AI supercomputer [Presumably DGX Spark], that sits next to you. You can connect it with networking, or you can connect them with Wi-Fi. You talk to this like you like you talk to the cloud, and the software is exactly the same.

So, if you are a developer, software programmer, AI creator, this product is perfect for you. The perfect developer companion.

And if you'd like a bigger one, this is essentially a computer for the AI natives [DGX Station], anybody who's getting completely AI applications, and you would like a bigger one than this one [DGX Spark], this is an AI workstation [Referring to DGX Station].

And this goes into a desktop, a normal desktop, and you can access it, you can remote, you can use it like the cloud, but it's yours, and you can walk away and go enjoy a coffee and don't feel bad.

Question 2 (Unclear speaker and outlet): I'm curious to know, over the last five to ten years, you've had a lot of great new products. The array of products and services you have now is quite extensive. I'm really curious to know what you had in the pipeline. Did you kill anything before it entered production? Like, you had a project, it had momentum and at some point you had to get down to business... [unintelligible speech], I'm really curious about the products that never saw the light of day. Can you share anything with us about that?

Jensen Huang: I would say it's very rare that we would completely kill a project. It's very likely that we shape it, shape it and reshape it. And, the reason for that is because the direction needs to be right. Like, for example, the initial early days of Omniverse, we had to rebuild it a couple of times, and the reason for that is because in the beginning, of Omniverse, our vision was right. That we needed to create a virtual world of digital systems, and robotic systems, and AI systems.

The vision was right. But, the way we architected the software was odd. It was kind of based on the old days of enterprise and workstation applications. And so, it wasn't scalable.

[Jensen pauses to ask for a bottle of water and proceeds to choke] I do that too, you know, I say something surprising, I'm talking, and then I'm drinking and swallowing all at the same time. I say something surprising to myself, and then I choke on water.

So, in the beginning, we built Omniverse as single instance software with multiple GPUs, and that was the wrong answer. Omniverse should have been created as a disaggregated system. It should run across multiple systems, multiple operating systems and multiple computers with multiple GPUs each. Which is the reason why we built this machine. In fact, this computer RTX Pro, it's called RTX Pro for a good reason.

It's essentially an Omniverse generative AI system, and notice this is one computer, eight GPUs, and you can connect them with more computers. Omniverse will run across this whole thing. This is the perfect Omniverse computer, the perfect robotics computer, the perfect digital twin computer.

We started working on Omniverse, how many years ago now? Let's see... Six years, seven years ago, finally it's come to connecting everything together. So notice that all the pivots that were made along the way, all of the mistakes that were made, and so on and so forth, we just keep investing.

Eric, Publication Unclear: Just a quick question about DGX Spark, and what you said with simple production, delivery is going to happen in a couple of weeks. I wonder if you can give any additional color about what you feel about the opportunity and compliance. You know, no pun intended, but is the window closing for an additional player to get into ARM-based computing?

Jensen Huang: So first of all, it's just delightful to look at. You know, it's nice to have a computer that's beautiful. The reason why we need this computer is because we need a coherent, productive AI development environment, and AI has models that are fairly large. Its environment really wants to be fully accelerated with excellent Python software and AI stacks.

If I look around this room right now, I don't actually see a computer that would be perfect for AI development. Most of the computers don't have that memory, or they don't have Tensor cores, because maybe it's a Mac, or maybe it's a Chromebook, or maybe it's an older version of a PC, or an older version of a desktop.

And so we took a state-of-the-art AI system, and we put it in a remote Wi-Fi environment that connects to everybody's computer. Now there's some 30 million software developers in the world, there will probably be just as many who are now going to be AI developers.

And so everybody has the benefit of having, essentially an AI supercomputer, an AI cloud, but not being burdened with the anxiety of your cloud computing that's ticking away. And so this is something you can buy, the ROI is probably, call it six months.

And for most of all, of course, this, we have really great volume, and it's available from everybody. So they'll be available from Asus, they can sell it alongside their laptops. It's available from MSI, and not to mention all the enterprise OEMs.

Every single developer can go out and just get one, and just put it next to their desk. You can develop on here, and you want to now scale it out, or test it out on large data sets, it's just like one pull down menu, point it at a cloud. Exactly the same thing runs there. And so, this is really an ideal AI developer environment.

Victoria Jen, CNA: Given the trade tensions and also the talk of de-globalization. How is Nvidia thinking about its global supply chain strategy, and where does Taiwan fit in that picture?

Jensen Huang: First of all, Taiwan is going to continue to grow, and the reason for that is we're at the beginning of a breed of a new industry. This new industry builds AI factories. The world is going to have AI infrastructure all over. AI infrastructure will cover the planet, just as internet infrastructure has covered the planet. Eventually, AI infrastructure will be everywhere.

We are several hundred billion dollars into a tens of trillions of dollars AI infrastructure buildout that will take five decades.

I've been looking around Taiwan. There are cranes everywhere. There's buildings everywhere. Factories are being built everywhere. And the reason for that is because we're all racing to build infrastructure for AI, manufacturing for AI.

Well, simultaneously, the world needs to be needs to have more manufacturing resilience and diversification, and some of that will be distributed around the world.

In the United States, we're going to do some manufacturing. It is impossible to do all manufacturing, all on-shore, and it's also unnecessary. But, we should do as much as we can that is important for national security, while having resilience, with redundancy, all around the world.

And so this rebalancing is happening at actually, a very good time. It's happening at a very good time because the world is building AI infrastructure. We're adding new infrastructure for the very first time. So we need a lot of new plants anyway.

The most important thing is we have to provide energy for these new plants. Communities realize that we want to grow. We want to have economic prosperity. We want to have economic security. In order for that to happen, industrialization; AI factories, need energy. And so the support of governments to provide for energy of all kinds while we pursue new technologies, whether it's hydrogen or nuclear, solar or wind, whatever new technology that that is most available at the time, we're going to need it all.

And so, government officials around the world really need to support all of the companies, so that we can re-industrialize and reset our industry, so that we can grow into AI infrastructure.

Question 5 (Unclear speaker and outlet): My question is about NVLink Fusion, what's your strategy?

Jensen Huang: NVLink Fusion allows every data center to take advantage of this incredible invention we call NVLink, now in it's fifth generation. We've been working on NVLink now for... How many years? 12 years?

Also, NVLink and Spectrum X NVLink, and quantum- our networking, is highly integrated and highly optimized together. And, that's one of the reasons why the performance of the AI data center, the AI factory, is so good.

When the factory cost $10 billion and our efficiency is 90%, and someone else's efficiency is 60%...30% of $10 billion is $3 billion. So, network efficiency is very important. Performance is very important. Efficiency is very important. Energy is very important...All because the network efficiency is so good.

And so we have many customers, many people who are developing their semi-custom AI infrastructure. They came to us and asked: "Can we can we use NVLink?"

Because, of course, there's a there's a industry discussion about UALink. UALink is not doing that well, I don't think. And so, the customers have come to us and asked whether NVLink could be authenticated. And I said, of course, we're happy to.

The benefit to us, is that the Nvidia network, the Nvidia the fabric, is really the operating system of the data center. It's the nervous system of the data center. And so, we can extend Nvidia's nervous system into every data center, whether it's Nvidia's technology, or if you're selling custom technology.

So we can expand our our market opportunity. It is also so good for us, it's good for the ASIC companies, Mediatek, Alchip, Marvell, right?

It's good for them, because now they have a complete solution. They can have HBM [High Bandwidth Memory], they have [speech unclear], and now they also have NVLink and networking. So now they have a complete solution partner. For the customer, of course, the most important part is that the architecture of NVLink is integrated with the [server and data center] rack system.

The rack system is so complicated. The spine is so complicated. And since they are already using GB200, they're already using Nvidia's racks. Now, they can scale, continue to use Nvidia racks, or even semi-custom. So one architecture, one hardware architecture, one NVLink architecture, one networking architecture, sometimes it's three CPUs, sometimes it's Fujitsu CPUs, sometimes Qualcomm CPUs, it's very nice for the customer.

Are we open to working with Broadcom? Of course, we are, of course we are. Currently, they have their own plan. But if they need, if they would like, to use NVLink [we're] very open.

We love working with Broadcom. We work with Broadcom in many places, export control. So, as you know, export control has caused us to write off our H20s. Our H20 is now banned in China. Banned to ship in China, and export controls resulted in us writing off multiple billions of dollars. Then, write off the inventory. The write-off of H20 is as big as many semiconductor companies.

If you look at look at most chip companies, their quarterly revenue is only a few billion dollars. We wrote off, you know, multiple billion dollars of inventory. And so the cost to us is very high, and also the sales to us was quite high.

The fact of the matter is, the China market is very important. It's very important for several reasons. The first reason is that China is where 50% of the world's AI researchers are. And we want the AI researchers to build on Nvidia. DeepSeek was built on Nvidia. That's a gift to us. It's a gift to the world.

Now, DeepSeek runs incredibly well everywhere. [Audio unclear, Huang mentions R1 or similar.] is an excellent, excellent AI model. It's a gift to the world. It's open source. And so, the China market is important, because the AI researchers there are so good, and they're going to build amazing AI no matter what. We would like them to build on Nvidia's technology.

Second, the China market is quite large. As you know, it's the second largest computer market. There's no others like it. And so the China market, my guess is that next year, the whole dang market is probably [worth] $50 billion. $50 billion dollars! You know how large many chip companies are? Much less than $50 billion.

So, the $50 billion market opportunity to Nvidia is quite significant, and it would be a shame not to be able to enjoy that opportunity, to bring home tax revenues to the United States, create jobs...sustain the industry.

Okay, so, all of that... [Jensen gets distracted and looks at the person who asked the question] You asked me a question, you're not even paying attention.

[The duo converses in Mandarin, and Huang responds] Am I upset at the policy? [Regarding export controls to China] I'm not upset at the policy. I think the policy is wrong, and the reason for that is because, let's look at the evidence.

Four years ago, at the beginning of the Biden administration, Nvidia's market share in China was nearly 95%. Today, it is only 50%. The rest of it is China's technology, and not to mention we have to sell lower chip specifications. So, our ASP [Average selling price] is also lower. So we left a lot of revenue, and nothing changed.

AI researchers are still doing AI research in China. They have a lot of mobile technology they would use if they don't have Nvidia, if they don't have enough Nvidia, they will use their own! They'll use the second best. Then lastly, of course, the local companies are very, very talented and very determined, and the export controls gave them the spirit, the energy, and the government support, to accelerate their development. And so I think, all in all, the export control was a failure, the facts would suggest it.

Question 6 (Unclear speaker and outlet): So I have a quick question about AI factories. I mean, AI factories and depracaction. So the equipment inside is a data center or AI server, right? So if we talk about the factories, we have to talk about depreciation, and equipment upgrades. So, what do you expect to see? And then you have this one-year-rhythm theory, which means the systems will be upgraded every year.

So, what's your expectation on the lifetime of equipment in data center AI factories. How frequently will their systems need to be upgraded?

Jensen Huang: There are two pieces of information that are very important. The first is the reason why we upgrade every year. It's because in a factory, performance equals cost, and performance equals revenues.

If your factory is limited by power, and our performance per watt is four times better, then the revenues of this data center increase by four times. So, if we introduce new generation, the customer's revenues can grow, and their costs can come down.

We upgrade every year. So we tell our customers, don't buy everything every year. Buy something every year. This way, they don't over-build and over-invest with old technology. But the benefit that we have, is that Nvidia architecture is compatible in all of the factories. And so, we can upgrade the software for a very long time.

The second fact, Hopper in the [beginning] of it's life, Llama-70B, in the beginning, was 1/4 the performance on the same Hopper [system] four years later. So, we keep improving the performance using CUDA software, which is the benefit of CUDA. And if we optimize the software, and improve the performance of the model, it helps the whole factory. Every single every single factory. Every single computer.

Nvidia's CUDA is very valuable here, Nvidia's once-a-year rhythm is very valuable, and so you have to use both of them together. With that, your overall data center fleet revenues will go up, your overall data center costs will come down.

And then one last idea. As you know, Nvidia CUDA runs everything. Every model, every new innovation, because the Nvidia CUDA install base is so high. If you are a software developer, of course you would do Nvidia CUDA first.

You have the best performance, the best technology, you also have the largest install base, and software developers want the largest install base, so that they can touch and reach everyone. Isn't that right? And so these three ideas, once a year, performance up, costs down. Once a year, all the time, a software upgrade with CUDA. And then lastly, our install base is so high everything runs, so the life of your data center will be quite long.

Max Cherney, Reuters: Since you were just talking about China, it brings me to something that I think is been an interesting question. Over the past 10 days, you've gone on a world tour. Made pit stops in the Middle East and elsewhere. And what I'm wondering is you've also made a flurry of announcements. Very technical stuff here at Computex, you know.

What I'm wondering is if you could put some of the technical announcements you've made, such as NVLink Fusion, the laptop platform, and some of the other more detailed, nerdy things in the context of how you're planning to continue to sustain Nvidia's growth over the next few years. I think that's especially relevant, with some of the fears investors have at the moment about a pullback in AI spending, especially after DeepSeek.

Jensen Huang: That last little part is really important. Remember what DeepSeek did. DeepSeek was incredible for AI infrastructure.

The old AI is called one shot [A stateless model like GPT-2 and GPT-3] . You hit enter, and the AI gives you an answer. One shot. The only way to give you a one shot answer is not to think. No thinking. You, [the AI model] already know it. You've kind of memorized it from pre-training. But DeepSeek is a reasoning model. It has to think.

It has to think, and you want to think fast, because if you don't think fast, the answer will take too long to come. And so DeepSeek opened the reasoning model, the world's first open source, excellent reasoning model.

Developers all over the world are using it, because it's so good. Now, the reasoning model is not one shot [stateless model], but it's hundreds of shots. It even goes to the internet to read websites, and read PDFs. So, it has to read, think, reason, plan, read some more.

So, that's the reason why deep research... You see that the latest versions of queries are taking much longer. The reason why it takes much longer is using a lot more compute [power]. And so, in fact, DeepSeek increased the amount of computing needed by maybe 100 to 1000 times.

That's the reason why all over the world, the AI companies are saying the GPUs are melting down, right? Sam [Altman], says our GPUs are melting because they're working too hard. They need more GPUs, more GPUs.

And last night, Microsoft announced that they were the first to online GB200, that OpenAI is already using GB200, and that they're planning to build out this year, hundreds of thousands of GB200 [systems]. More build out this year than all of Microsoft's data centers combined, only three years ago.

That's how much [OpenAI plans to build out], in just one year. And so the build out, the ramp of AI infrastructure, to me, is actually just beginning. This is now the beginning of the reasoning AI era, and reasoning AI is so useful, and it's so useful in so many different applications.

Second, AI infrastructure is being built out. That's one of the reasons why I'm traveling around the world. Every region realizes they need to build their own AI infrastructure. AI infrastructure is going to be part of society, part of the industry. Just like electricity, just like the internet, AI is going to be an essential part of infrastructure, social infrastructure, as well as industrial infrastructure.

When I was in the Middle East, President Trump announced that this is the reversal of what was the previous AI diffusion rule, the new diffusion rule, for this administration, they realized the goal. The goal of the AI diffusion rule has specified in the past, was to limit AI diffusion.

President Trump realizes it's exactly the wrong goal. The United States, and America, is not the only provider of AI technology. If the United States wants to stay in the lead, and if the United States would like the rest of the world to build on American technology, we need to maximize AI diffusion, maximize the speed. And that's where we are today.

I think it's really a great reversal of a wrong policy, frankly. And this [the new AI diffusion rules] is a great reversal of that, and it's just in time.

Question 8 (Unclear speaker and outlet): We started with CPUs, and then to right now with GPUs. So still, both are important for our industry. So, what is the future?

[This question is quite unclear, but the general gist of it is that the speaker asks Jensen about the future of the hardware and software industries in the wake of AI factories and data centers.]

Jensen Huang: Good question. Fluid Dynamics is not going to go away. Particle Physics is not going to go away. Finite elements not going to go away. Computer graphics is not going to go away. These algorithms are so good, and they've been refined over so many years.

Not to mention trillions of dollars of software already written, no reason to rewrite it. And so flexible software, flexible hardware is always valuable. That's the reason why CPU has been so successful for 60 years.

Now, Nvidia has created something and you have been following CUDA for two decades now, and you understand very deeply, that CUDA is so successful because there's so many domains of applications.

Everything from deep learning, to machine learning, classical machine learning, to unstructured data quantities, structured data processing, to particles, and fluids, and quantum, and chemistry, and so on so forth. The list goes on.

And so the benefit is flexibility. If it's slow, then it's too expensive. But Nvidia's technology is very fast, it's also flexible. Then the data center can be used for many things. If the data center can be used for many things, the utilization will be high. If the utilization is high, the cost is down.

So, general purpose equals low cost. In fact, you might remember, on the day that Steve Jobs announced the iPhone, he showed iPhone, and then he showed the music player and camera, and also a PC. So all of these different devices can now be in a general purpose device, camera, music, player, all in one general purpose device. This general purpose device is, of course, more expensive, but the cost is actually lower than having all of those things.

So, general purpose equals low cost, but it hasn't got very high performance. And that's the benefit of CUDA. You have just exactly pointed to the reason why CUDA is so successful.

Question 9 (Unclear speaker and outlet): Two or three years ago, you said that Nvidia is a software company, and beyond hardware. So, what elements will take Nvidia to the future? Is it still CUDA [unclear audio], or a bunch of AI [unclear audio].

Jensen Huang: Thank you. Appreciate that. Actually, what I said is that Nvidia starts with software. We always start with the algorithm. For example, it could be a quantum classical algorithm, quantum classical computing.

Maybe it's an algorithm for computational lithography, making chips. Maybe it's an algorithm for 5G and 6G radio. We always start with the algorithm, and then, we try to design up, down, bottom. It's called "co-design", across the entire stack.

But, we have to start with the algorithm. Otherwise, if you don't understand the algorithm, you cannot accelerate it. CPUs don't have to understand algorithms. CPUs, because the algorithm sits on top of a compiler, and you only see a compiler. But, accelerated computing is not like that. [It's a] Very, very different type of computing format.

So, Nvidia starts with that [with software and algorithms]. In the future, though, you will see that Nvidia started with software, acceleration of algorithms, to full-stack, then we became a systems company, then we became a data company. Now, we're becoming an AI infrastructure company.

And the infrastructure is important, because the software that runs across the infrastructure is very different than the software that runs on a PC. And, the system organization, architecture and optimization is very different than inside a PC.

So, as we think about the future of computing and these factories, you have to think about the infrastructure completely. Everything from power, to cooling, to networking, to scale up networking, into the fabric, security, storage...everything. Everything has to be considered in one time.

Otherwise, the software is not optimized, the throughput is not optimized. And if the throughput is not optimized, the revenue is affected. This is the first time, the very first time, that a computer directly affects the revenues of a company.

Today, when you see a chip fab, that ASML equipment directly affects TSMC's revenues. Makes sense, right? It directly affects the revenues. But a computer in a big IT data center... How do you know?

If I bought you a faster laptop, does it directly translate to your revenues? Does it directly translate to your income? It does not. Same thing. [For example] IT, if I bought them more computers, does it directly translate to Nvidia's revenues? It does not.

But in the AI factory, it does.

So, this is a very new way of thinking about computers. It's a factory, and we have to optimize it to the extreme, because these factories are very, very expensive.

Dr. Ian Cutress, More than Moore: Love the NVLink Fusion announcement you did yesterday. I'm trying to understand the width, depth and breadth, to the availability to the outside world. I kind of want to envision a system where you have the NVLink spine, you have a partner with that custom CPU, with NVLink, their custom GPU, TPU, whatever you want to call it, with their NVLink, being a custom partner with a switch on top. All that's involved with Nvidia, is the ingredient with the switch. Is that a vision you can expect for that technology in the future, you said you wanted to at least buy something right?

Jensen Huang: That is one vision. But the more likely vision, is that they will buy an NVLink chiplet, and they'll buy the NVLink switch, and the NVLink spine, and the Spectrum-X switch, and all of the necessary software to go along with it. That's more likely.

Let's use one particular example. Remember, Fujitsu has been a computer company for literally, exactly as long as I can remember. They have a large install base of Fujitsu systems all over the world, and it's based on Fujitsu's CPU. They would like to add AI to that.

How do you do that? Because today, Fujitsu has a CPU, and they would like and all of their software stack runs on the Fujitsu CPU, and the Nvidia AI, runs on Nvidia AI.

And so how do you combine the two? How do you use these two together? Well, the way you fuse these two ecosystems together is with NVLink beauty. It's a fusion of ecosystems. Does it make sense? That's why I call it NVLink Fusion, the fusion of two ecosystems.

All of a sudden, by building a Fujitsu CPU with NVLink, and you connect it to...the port is actually going to look exactly like this, except this will be a producer CPU, or [unclear audio], or [unclear audio], or Rubin. We would then sell this to Fujitsu. Make sense? They plug it into the NVLink system, and look what happened. Fujitsu's entire ecosystem just become AI supercharged.

Dr. Ian Cutress, More than Moore: But could they use their own accelerator?

Jensen Huang: They could, but they really want our ecosystem. That's the reason why they did this. If they don't want our ecosystem, there's nothing to fuse. People want our ecosystem, and all the software that we bring along.

So we would do the same with Qualcomm, and if other CPU vendors would want, we're more than happy to. Because we put the chip to chip, and they NVLink into Synopsys and Cadence, so every CPU company could do it. And all of a sudden, Nvidia's entire ecosystem becomes integrated with theirs, fused with theirs. Pretty clever, huh?

Lisa, Wall Street Journal: I just want to follow up with something you said earlier. You talked about AI diffusion rule , and basically it's been a reversal for the past week. I'm interested in your views on going forward? Do you think this reversal will continue, just at least the Middle East is just one example of a country's negotiation over GPUs. I'm just wondering, did you expect Trump and his administration to continue that line and his attitude?

Jensen Huang: I don't know the details of the diffusion rules. The policy hasn't come out. No one knows what future policies are going to happen. Nobody knows in any country and in any government. Policies are always evolving.

But here's what I do know, the fundamental assumptions that led to the AI diffusion rule in the beginning, has been proven to be fundamentally flawed.

That's the big thing. Believe that smart people are doing smart things in governments, and they want to do what's good for the country. I believe people genuinely do that.

If the facts are flawed, if the assumptions are flawed, then the outcome would have to be flawed, the policy would have to change, and so the fundamentals have been completely proven wrong.

And so that's the reason why President Trump made it possible for us to expand our reach outside the United States. And he said very publicly, that he would like Nvidia to sell as many GPUs as possible, all around the world.

The reason for that is because he sees it very clearly, that the race is on, and the United States wants to stay ahead. We need to maximize, accelerate our diffusion, not limit it, because somebody else is more than happy to provide it.

And this AI diffusion is important, because AI is not just AI for all of the things that we said, remember, AI is also going to be the foundation of 6G. So, future communications infrastructure will also be affected. So, we need to get the American AI technology out to as many places as possible. Work with developers and AI researchers all around the world, and help them build an ecosystem, [to] participate in this incredible AI revolution, and do that as fast as possible.

The fundamental assumption was that United States the only provider of AI. And, obviously that's not true.

Dianne, New York Times: So you talked about how important the China market is for Nvidia, and I was wondering, what does it look like for Nvidia to compete in China on an ongoing basis? Is it accurate that the company is investing in a research center in Shanghai, and does the future of Nvidia in China look like, potentially working more closer with the US government, to avoid a future situation like H20?

Jensen Huang: We are trying to lease a new building for our employees in Shanghai. We've been in China for 30 years. Our employees are in a really cramped environment.

Because now more and more people- We still have a flexible work from home policy. So, you know, I decided that the way that people work should reflect the capabilities of the technology, the nature of our work and the sensibility of culture.

And the one additional idea is, because of video conferencing, because we can remote work, I wanted to use the opportunity to enable young people, young parents, to be able to build a life, build a family, and build a career at the same time. Because many young many young women can't build a career, because they have to be at home taking care of their children.

I would want to make it possible for young women to do both: Have a great career and be a great homemaker. And so the ability to have remote work enables that to happen. It's been a fantastic response from all of our employees and all of the others.

They think it's fantastic. Of course, it is incredible maintaining both jobs or doing both things at one time. It's not easy, but at least it's possible. And so that's the reason why we have remote work.

But more and more people are starting to move to the offices, and so the offices are just too cramped. We finally found a place that we could lease the building, and that's basically it. I'm surprised that that's such an enormous story. I feel like I just bought a new chair and that that became front page news. [Laughs]

Our competition in China is really intense. Let's face it, China has a vibrant technology ecosystem, and it's very important, the fact that China has 50% of the world's AI researchers, and China is incredibly good at software. I would put China's software capabilities up against any country, any region in the world. That's how good they are.

Not to mention, they're fast. So our competition is intense. If we're not there, quite frankly, the local companies are more than joyful. They would love for us to never to go back to China.

And so it is precisely those policies benefit, whatever the reasons are. I hope that that what is actually happening, is going to help shape the policy-makers, so that it's possible for us to go back and compete, and that's my goal.

H20, as it currently stands, Hopper. We don't know how to degrade Hopper to make it useful to the marketplace, but we're committed to the market.

You know, the number one in export controls. Export control puts limits on products. If the government would like to completely have sanctions, and whatever they want to ban completely, they're allowed to do that, of course, and we'll comply with the law.

But in the meantime, our job is to comply with the export controls, and the government is very clear about that, provide the export controls, but do your best. Provide the export controls, but continue to do your best, serve the market.

What we're trying to do right now is to think through, how can we best serve the market? And we have very limited choices. We degraded the product so severely, It's going to be quite complicated. But anyhow, we're going to do our best. I don't have any good ideas at the moment, but I'm going to keep thinking.

Penny, Publication Unknown: I'm just going to ask you a question about China. So there are lots of startups in China, GPU companies, and they're developing their ownerships. I'm just wondering how you see this, and how is Nvidia going to respond to it?

Jensen Huang: There are startup companies, and [Audio unclear] one of the the largest and most affordable technologies, period, in the world. And, they are innovating fast. The advantage that AI provides is that the data center is very large. It's not like a cell phone. It doesn't have to fit in one line. If it doesn't work, you know, use two chips. And if that doesn't work, use four chips. It uses more energy. But power is quite cost effective in China, and there's plenty of land. So the the the ban on H20 is not effective for that reason. They'll just buy more more chips from the startups, from Huawei, and others. And so, I really do hope that that the US government recognizes that the ban is not effective and gives us a chance to go back to market as soon as possible.

Question 14 (Speaker and publication unclear): Nvidia is building AI systems for large scale, solutions like GB300 NVL72, do you envision any [audio unclear] specific platforms. Will Nvidia extend any particular specialized AI hardware, and how will you prioritize areas like robotics and industrial AI?

Jensen Huang: These are the two computers. These called DGX. DGX-1 was the first computer in the world, created for one service, for AI. It only does one thing. AI. Oh, and CUDA.

So DGX-1, was the world's first AI native computer, and when I first announced it, there were no customers except for one, and they didn't have any money, so I gave it to them. A company called OpenAI, this was 2016.

So, I decided that now that there are developers all over the world, and they would all love to have their own DGX-1, but DGX-1 is very big. and so I decided to make small ones. These are personal DGX-1's. This one is called DGX Spark, and this one's called DGX station, the world's first AI personal computer.

[Audio unclear] With respect to robotics, robotics is going to be the next industrial revolution. Let me prove it to you. In order for a technology to succeed, it needs to have excellent capability. It needs to have usefulness, so customers buy it, and there needs to be enough customers buying it [at] high volume, such that the R&D fly-wheel can be high.

It has to be useful, it has to be good technology. The technology needs to converge at just the right time, [it needs] lots of customers and use cases. [Audio unclear]

If this technology fly-wheel is high, then the refinement rate will be exponential. The performance will go like this. Cost will go like this, just like smartphones. The moment that the smartphone, all the pieces of technology, from touch, to 3G, which became 4G, mobile processors, internet, the whole web. The moment all of those things came together, boom, it took off. A huge industry.

The same thing is going to happen with robotics, and the reason for that, is the humanoid robot is the only robot that we can imagine using in many places, because we are in many places. We fit the world to ourselves.

There are only two of them [robotics products] with that property, those characteristics. Self driving cars, because we create the world's [Audio unclear], for cars and human robots. Because, we created the world for ourselves.

If we can make these two technologies useful, functional and useful, it's going to take off. And that's what Nvidia's Isaac GR00T is.

Our entire platform, just like we have RTX for games, just like we have Nvidia AI that you're seeing here, Isaac GR00T is our human and robotics platform, and we are very successful with them. That's going to be the next multi-trillion dollar industry. I expect it to be very, very large.

This was not the end of the Q&A session that journalists had with Nvidia's Jensen Huang at Computex 2025. However, we hope you enjoyed reading.

Nvidia will send 18,000 AI GPUs to Saudi Arabia's new state-sponsored AI company, Humain, CEO Jensen Huang announced Tuesday. The move comes after the US canceled pending AI diffusion export rules that would have complicated these types of transactions.

As reported by Bloomberg, Huang made the remarks at the Saudi-US Investment Forum in Riyadh as President Donald Trump makes his visit to the country. According to the report, Nvidia's semiconductors will be used to build a 500-megawatt data center.

During his remarks, Juang reportedly stated that Saudi Arabia would help Nvidia unlock new capabilities in the field of AI thanks to its rich energy stores. "I am so delighted to be here to help celebrate the grand opening, the beginning of Humain,” Huang said in comments reported by CNBC. “It is an incredible vision, indeed, that Saudi Arabia should build the AI infrastructure of your nation so that you could participate and help shape the future of this incredibly transformative technology.”

The news comes just days after it was revealed the Trump administration plans to jettison its restrictive AI Diffusion Rule, an export control policy proposed in January to prevent the proliferation of AI tech to rival nations. The three-tier system reserved its strictest controls for the likes of Belarus, China, and Russia, but Saudi Arabia was among nations listed in tier 2 set to face restrictions that would have precluded even a tenth of the amount proposed from changing hands prior to the rules being scrapped.

Saudi Arabia's Humain venture explained

If you wish to try out the "breakfast of geniuses," the Nvidia Breakfast Bytes first seen at GTC 2025 are now available at Denny's restaurants. This is the first product of 2025 with the Nvidia name on it that is readily available, is purchasable at the expected price, and is affordable. However, this sub-$5 breakfast of 520 calories made up mostly of flour, processed meat, and sugars, is probably as bad for your health as an RTX 50 graphics card is for your bank balance.

Denny's says the Nvidia Breakfast Bytes are a limited edition menu item, available until May 13. It consists of four pork sausage links, four fluffy buttermilk silver dollar pancakes, and a ladle of maple syrup.

In case you don't know what to do with this plateful of fast foodstuffs, Denny's shares bullet point instructions on "how to make the perfect byte" alongside a visual guide to folding the pancake around the sausage like a hot dog. (Wasn't this supposed to be the breakfast of geniuses?)

Actually, those instructions seem to stray a little from Jensen's favorite way to eat, as according to his own lore he would wrap a sausage with a pancake and then dip it into syrup as he chomped from one end to another – which sounds much more finger friendly.

Jensen's full-stack moment

"Denny's will always be a special place for me. It’s where I learned that no task was too small to do well," explained Jensen Huang about the special place the special place the restaurant has in his life and career.. "This dish powered me through my long shifts and eventually inspired the birth of Nvidia at a Denny’s booth right here in San Jose. Seeing it on the Denny’s menu today is a true full-stack moment!"

We don't know why Denny's is removing the Nvidia Breakfast Bytes from the menu in mid-May. But, until that fateful date, Denny's customers will be able to order this menu item online for carry-out or delivery, all day, every day, including late night via Dennys.com and the iOS and Android apps. Denny's customers in San Jose will enjoy a more convenient Nvidia Breakfast Bytes experience, as participating restaurants in this area of California - Nvidia's home turf - will serve the dish for dine-in customers.

After May 13 we guess you'll have to go back to 'menu hacking' to order up Jensen Huang's signature savory and sweet delicacy. Also, by that time, potential Nvidia graphics card customers will hopefully be having better luck securing their hardware at reasonable prices.

An Asus exec at GTC 2025 has shown off what might be both the ultimate PC collector's item and the most valuable consumer graphics card on Earth. Asus Director of Marketing, Ernest Cheng, shared a picture of one of the extravagant ROG Astral GeForce RTX 5090 Dhahab OC Edition graphics cards. Lifting this to a higher level of geek Nirvana, this particular sample bears Nvidia CEO Jensen Huang's autograph. We think this lavish gold graphics card sample is probably worth over $16,000 after looking at previous auctions.

As Cheng points out above, this 'Golden ROG RTX 5090 Astral' is now one of its kind, bearing Jensen's autograph and his "RTX ON!" inscription. However, it was already one of the rarest graphics cards among the rare-as-hen's-teeth RTX 5090 hardware that has reached retail.

As a reminder of the calibre of product we have in the photo, you can check back through our extensive RTX 5090 review, and recap the ROG Astral GeForce RTX 5090 Dhahab OC Edition story we ran in February (linked top).

The ROG Astral line is a new quad-fan flagship family from Asus, and an RTX 5090 OC model carries an official MSRP of $3,099, which is over 50% more expensive than a reference design. Now, add the golden shroud and design featuring detailed engravings of skyscrapers, camels, and Arabic calligraphy – and you have true opulence. This Middle Eastern exclusive will obviously carry a further price premium to the $3,099. Add in Jensen's autograph, and the sample graphics card in our picture will surely be worth a king's ransom.

One thing collectors will be aware of, though, is an overabundance of signatures can devalue the addition of any autograph. Jensen seems to be pretty open to signing things from fans willy-nilly, which is nice but could limit future collector valuations. Already this year we have seen the official Nvidia GeForce social media channels offer up several historical GPUs accompanied by the CEO's scrawl.

We also reported on Der8auer buying a Jensen-autographed Asus ROG Matrix GeForce RTX 4090 (with proceeds to charity) last year. That raised $16,000, which might help draw a baseline expectation on the sum the headlining 'Golden ROG RTX 5090 Astral' from the GTC 2025 event could achieve.

Nvidia’s annual GPU Technology Conference (GTC) is happening today, and Jensen Huang is set to give the keynote address this morning. The multi-day event focuses on artificial intelligence, computer graphics, and other technologies that rely on GPUs' specialized computational power. The keynote address will happen live at the SAP Center in San Jose, California at 10 am Pacific Time, but it will also be live-streamed to a global audience via YouTube.

A pre-broadcast livestream, Live at Nvidia GTC with Acquired, will start on YouTube at 8 am Pacific Time. The company says this event will feature speakers who will dive into Nvidia’s over 30-year history to see how it became the AI giant it is today.

But what’s more exciting for everyone is that Huang is expected to unveil the Blackwell Ultra GPU, which has since been renamed the B300 series, that is expected to deliver more performance and have upgraded memory configurations. Huang said he will also show off next-generation Rubin AI GPUs and more at GTC.

The B300 series AI GPUs are expected to be available in the latter half of this year, while the next-generation Rubin is scheduled for 2026. Many people are anticipating the arrival of these more powerful chips, especially as tech giants and startups alike are battling for supremacy in the AI space.

Nvidia’s competitors, like AMD and Intel, also have their own AI GPU offerings. However, they are miniscule compared to Team Green, which currently owns around 92% of the entire data center GPU market. Its near-monopoly on AI GPUs, plus the hype around AI models, allowed it to become the most valuable company in the world practically overnight.

It has since dropped to third place after some market corrections, with the company losing more than half a trillion dollars in market cap after the release of DeepSeek AI. But as long as there’s demand for powerful AI GPUs, it’s unlikely that Nvidia will go away anytime soon.

It’s just a shame that many gaming enthusiasts, which was Nvidia’s primary market before AI exploded into the scene, feel that they’re being left behind by the company. While it’s understood that the company will prioritize its AI cash cow, the pricing and availability (or lack thereof) of its recently launched RTX 50-series GPUs has disappointed millions of its core fan base.

Jensen Huang, CEO and co-founder of Nvidia, met on Friday with U.S. President Donald Trump at the White House to discuss American AI policy, export controls on advanced AI GPUs for China, and U.S. technology and AI leadership, Reuters reports.

"I cannot say what is going to happen," Trump reportedly said. "We had a meeting. It was a good meeting."

According to the report, Trump's recent meeting with Nvidia's boss touched upon several topics related to artificial intelligence and semiconductors. The AI section of the discussion reportedly included American AI policies, China's DeepSeek, and the implications of its technologies on the AI services and hardware market in general, as well as U.S. export controls on advanced AI GPUs.

The Reuters report does not detail the semiconductor-related part of the conversation, though given Trump’s focus on the onshore production of chips, we can make some guesses.

"We appreciated the opportunity to meet with President Trump and discuss semiconductors and AI policy," an Nvidia spokesperson said in a statement by NHK. "Jensen and the President discussed the importance of strengthening U.S. technology and AI leadership."

Nvidia is the industry-leading supplier of AI GPUs for training and inference, so when the U.S. government updates its export policies, this seriously affects the company. Earlier this year, the previous U.S. government announced new export policies under which Nvidia and other companies could sell advanced AI hardware without any restrictions only to entities based in the U.S. and 18 allied countries. There would be restrictions on shipping sophisticated AI GPUs and hardware to the rest of the world, including U.S. allies in Europe and the Middle East. In contrast, companies in adversary countries like China and Russia would be essentially blocked from getting high-end AI GPUs. Nvidia has criticized the move as its current and upcoming products fall under the new rules, which might affect the company materially.

The Trump administration could reverse the proposed regulation, just like it reversed Biden’s AI development policies earlier this month. However, it has yet to make its move. There are reports that the Biden administration is considering blocking sales of Nvidia’s cut-down H20 HGX to China, which could cost Nvidia some $10 billion in revenue.

Another topic that might have been discussed is Nvidia’s reliance on Taiwan-based TSMC for chip production. Trump wants leading chipmakers to build their fabs in the U.S., but building cutting-edge fabs would take years. The only company with leading-edge manufacturing capacity in the U.S. is Intel. However, it is unclear whether the company has enough 18A (1.8nm-class) production capacity for itself and external customers is unclear.

According to the Financial Times, Nvidia CEO Jensen Huang will meet with U.S. President Donald Trump at the White House. The source, familiar with the matter, reportedly indicated that the meeting was planned some time ago but did not reveal the topics to be discussed. Given Nvidia’s current focus, it is likely that Huang and Trump will discuss U.S. AI policies.

U.S. AI policy is multifaceted, from domestic development of AI models and hardware to exporting AI hardware to other nations. As a result, Jensen Huang, who did not attend Trump's inauguration, and newly elected U.S. President Donald Trump could discuss many topics.

The meeting comes after the Chinese startup DeepSeek made a major AI breakthrough, triggering a massive sell-off of AI-related stocks and wiping out a trillion dollars in market value. However, the Financial Times's source stressed that the meeting was planned before DeepSeek introduced its R1 AI model.

DeepSeek has drawn attention to developing an advanced AI model while using significantly fewer computing resources than companies like Meta or OpenAI. The startup claims it spent $5.6 million training its V3 model using 2,048 Nvidia H100 AI GPUs. However, analysts estimate DeepSeek and its affiliate, hedge fund High-Flyer, have access to approximately 60,000 Nvidia H100 GPUs and have invested over $500 million in restricted hardware that was not supposed to be shipped to China.

Nvidia has long opposed expanding export restrictions, arguing that limiting sales of high-end chips to China would affect the sales of American companies and could backfire by encouraging Chinese firms to develop their semiconductor industry. To meet strict performance limitations for AI GPUs shipped to Chinese entities, Nvidia developed its H20 HGX —a cut-down version of the H100—that complies with current U.S. export regulations and does not require an export license from the Department of Commerce. However, rumors suggest that the Trump administration plans to restrict Nvidia's H20 HGX GPU shipments to Chinese entities, which could cost Nvidia over $10 billion in annual sales.

Nvidia has not commented on Huang’s upcoming meeting with Trump.