When the Nvidia CEO isn't busy basking in the adoration of fans at Computex Taiwan, it seems he might spend his time considering how to shift social norms. In what direction, you ask? Why, using AI more, of course.

That's what he told the Associated Press when the interviewer asked whether AI itself concerns people or "the absence of social structures to adapt to something happening so fast."

Jensen responded that "it's a combination of all that" but also emphasised that new social norms are needed: "You have to deal with regulation, technology, you have to deal with social norms."

He gives the example of automobiles and initial concerns over the harm they could do to people, especially children. But we changed social norms so that now kids are warned not to play in the street, there are laws surrounding speed, and so on.

However, when asked what social norm should be changed for AI, the answer isn't particularly satisfying: "The first thing is that I would advocate that everybody use AI. Just go engage it."

I'm not entirely sure that this response would traverse the analogy bridge over to automobiles very well. I can't imagine 'just use a car' would have been very convincing, back in the day. And I'm not sure how keen Huang would be on actually analogous shifts in norms and regulations, such as one akin to speed limits but for AI.

Huang says that, unlike pretty much any other technology, AI is free and easy to use, which is true enough on the surface. However, those 'free' tiers of AI aren't actually free. AI uses and inflates the price of technology that already exists. It's also subsidised by higher paid tiers, funny money inflating a ballooned market, and of course (and apologies for getting a little technical here) a metric s***ton of energy.

In other words, 'free' my arse.

I also can't help but wonder whether there's an element of worry in Huang imploring people to actually use AI. After all, if people don't actually use the technology, eventually that lack of end-user demand will catch up with AI companies, and in turn with the company that gives them their AI hardware: Nvidia.

As it stands, Nvidia is extremely profitable, but the companies that buy from Nvidia aren't. We'll just have to see how long it can last—markets are funny things.

One concept was continually repeated by Nvidia at Computex 2026, and it's this idea of "reinventing the PC." The phrase has been used in reference to the company's RTX Spark SoC—powering "the world’s first Windows PCs purpose-built for personal agents"—and from a hardware perspective, it's an interesting bit of kit.

However, Nvidia CEO Jensen Huang went further into the "reinvention" of the PC at a Q&A session later in the show. "Your personal computer is really the world's largest edge device, and it's 40 years old," said the Nvidia chief. "And [it] has to be reinvented for agentic systems…. just like we have to reinvent the car."

Huang then used an example of modern autonomous cars as edge devices, while satellites "put intelligence in the sky." Later, the Nvidia chief had this to say about the future of the PC platform as a whole:

"Our computer sits at our desk waiting for us to use it. In the future, when we leave it… we're talking with it all the time," said Huang.

"I'll be chatting in WhatsApp with my agent, and it's doing stuff... and my agents are going to have names, and they're on my WhatsApp, and we're just chatting all the time. I'll be talking to it, and it's going to be talking back. It'll call me."

"That is the personal computer future. Tell me that's not R2-D2. Tell me that's not robotics. Tell me that's not cool," Huang continued. "I believe that many, many people will have this at home, just like they have a car at home. Soon, the agent is going to be so valuable to you, you want it to be sitting in a nice box, sitting in a nice computer, secure, performant, something you could carry with you, something you would use for a long period of time."

That's a nice sci-fi-style piece of imagery. Who among us hasn't imagined the idea of the ever-present "computer" (summoned with a cut-glass British accent, of course), working away in the background to not just respond to our commands, but to intelligently work with us to satisfy our needs, even at great distances?

The problem, however, is when that thinking runs into the cold, hard wall of reality—and all the extra consequences that entails. As things stand, our PCs are enablers of our own intelligence in a relatively direct way. We input commands, the computer responds. We control the machine, to a considerable degree. We are the agent.

But transforming our PCs into something with more agency, more AI-handled tasks, strikes me as risky business. It's putting the user further away from the machine, and letting AI do much of the heavy lifting instead. And in a world where concerns around the wider scope of the tech are well-publicised, this sort of AI-first thinking seems like a misread of the public perception surrounding it.

It reminds me of a joke/meme I read a long time ago, which I'll reprint here:

"Tech enthusiasts: Everything in my house is wired to the Internet of Things! I control it all from my smartphone! My smart house is Bluetooth-enabled, and I can give it voice commands via Alexa! I love the future!

Programmers/Engineers: The most recent piece of technology I own is a printer from 2004, and I keep a loaded gun ready to shoot it if it ever makes an unexpected noise."

AI is far from perfect. And while it continually improves, the level of public trust around it seems shaky at best. We continually read stories of AI deleting work, breaking existing systems, and hallucinating. It can also be manipulated, sometimes with surprising ease. In this upcoming agentic AI PC world, can we really trust it to integrate itself so smoothly into our digital lives? And more crucially, do we want it to?

Looking at the wider picture of public perspective around AI, the temperature seems to be rising. Students are actively booing speakers who tell them about the wonderful AI future they're walking into.

Microsoft's head of AI, meanwhile, has expressed puzzlement around negative reactions towards the tech, while the company itself is in the process of scaling back AI integration into Windows 11 features, after complaints that the operating system wasn't focusing on the fundamentals. Which are, of course, the traditional functions of your PC.

Personally, I like the fact that my PC is a box that I control directly, not an AI agent platform I work with from afar. It makes me feel empowered. And while there are already lots of unseen processes running under the hood to make that happen for me, I'm not sure a swarm of AI agents will improve the experience.

"We're now reinventing the computer. It's an agentic computer. It's an agent now, it's an assistant, not a tool. And that's the big idea," says Huang. That's a shame. I like tools. They enable me, a human being, to directly express myself. Agentic AI assistants handling many tasks for me, reducing my primary role to some sort of bizarre conductor, though? Is this really what we, the end users, want?

Nevertheless, the artificial intelligence beast continues to spread its tentacles into our daily lives, and we're often told that if we don't get on board with the tech, we're going to be left behind. Don't worry, though. It's a good thing. Agentic AI will make our lives better, and soon we'll all… I don't know. Have more time to go to the beach, or something.

I guess I'll believe it when I see it. But it's difficult not to feel that, as end consumers, we don't really have much of a choice as to how our technological future develops. Our brave new AI-dominated world looks to be coming for us whether we like it or not, and we'd better hope it's everything that was promised. Will I be writing about how awesome my new agentic AI PC is in future? Will I even, thanks to AI, be writing about anything at all?

I've no idea, but it doesn't feel great. How about you?

We live in some odd times when the CEO of a tech company can be seen working crowds, signing autographs, and generally giving off film star vibes, but that seems to be norm when it comes to Nvidia's Jensen Huang whenever he's in Taiwan. But it was during one such moment at Computex that he said something that would resonate with any PC gamer: declaring that the GTX 1080 Ti was a bit special.

The brief interaction was shared by MilGrauNews on X, where somebody (apparently the OP's girlfriend) handed Jensen an original GeForce GTX 1080 Ti for signing. "Oh, one of my favourites," he enthusiastically responded. "Oh, my god. This is one of the best. This changed everything."

For once, Nvidia's CEO has said something that I wholeheartedly agree with, as the GTX 1080 Ti was outstanding for its time—and for many more years to come. To understand why, we need to go back to May 2016, when Nvidia launched its Pascal GPU architecture. The initial line-up of graphics cards sporting these chips topped out with the GeForce GTX 1080, but then three months later, the Titan X Pascal made an appearance.

That graphics card used a slightly cut-down GP102 GPU, with 3,584 shaders and 12 GB of GDDR5X. It was mighty powerful, but also outrageously expensive at $1,199, though certainly not the most costly that Team Green had released at that point (the $2,299 Titan Z from 2014 takes that award).

But in March 2017, Nvidia did something very special; something that it's never done since and will probably never do again. It launched the GeForce GTX 1080 Ti, a GP102-powered graphics card that also had 3,584 shaders and just one GB of GDDR5X less than the Titan X Pascal.

What made the launch special was the price, just $699. Since it used faster VRAM chips than those on the Titan card, it actually had more memory bandwidth, so you were effectively getting an equally, or slightly more, capable graphics card for 42% less money.

Nvidia would eventually go on to release the Titan Xp, in April 2017, that used a full-spec GP102 GPU, with 3,840 shaders for the same price as the first Pascal Titan. But, with the 1080 Ti being so good and so much better value, relatively few people were interested in it. I must admit that I was one such person and bought an Xp, but that was the last time I ever forked out for a range-topping Nvidia graphics card.

In many ways, Pascal marked the end of an era for Nvidia, because the GPU's successor (Turing) was the first to sport Tensor cores and ray tracing units, kick-starting the whole RTX shebang. Something else that the RTX 20-series cards pushed off the line was a noticeable hike in prices. The RTX 2080 Ti and RTX Titan, both released in 2018, were $999 and $2,499, respectively, and these days, all Nvidia models that use the biggest GPU in a given series are silly money.

I'm not suggesting that the GeForce GTX 1080 Ti was cheap, because that's still a big slab of money to hand over for a GPU even now. But what you got for all thatcash was, and still is to some extent, extremely good.

Huang is absolutely right in saying that "it changed everything" because it marked a turning point when Nvidia realised that if PC gamers were happy to spend $699 on a graphics card, they would probably be just as happy to spend a bit more. And then more… and more. Until we're at the point where $699 will only get you a GeForce RTX 5070, although the RAMpocalyse is the biggest factor behind that.

The GeForce GTX 1080 Ti was indeed one of the best graphics cards Nvidia has ever made, but I suspect we will never see its like again.

Nvidia's second GTC of the year took place in Taipei, Taiwan this week, with CEO Jensen Huang repeatedly assuring that "useful AI" (read: AI that makes a return on investment) has arrived. As for AI's wider-ranging effects on the economy, Huang expressed some scepticism on stage.

"People talk about AI reducing jobs—complete nonsense," Huang said during his on-stage presentation. "It's causing more software engineers to be hired, and the reason for that is very simple. If you can hire a software engineer and you could generate $9 trillion worth of productive work, why wouldn't you want to hire more software engineers?"

Huang had earlier argued during his presentation, "30 million software developers, representing about $3 trillion worth of GDP, producing three—that's what they're paid—$3 trillion worth of salaries per year, which is generating economic growth for the rest of the industries. Say $100 trillion of the world's industries is impacted...is generated by $3 billion worth of salary [for software engineers]."

It's a little unclear where Huang is getting these numbers from, but earlier remarks suggest he based at least that 30 million figure on increased GitHub activity. Huang then later went on to add, "If that line was flat, then obviously people will hire fewer software engineers, but because the output is so incredible, people want to hire more software engineers. This is going to show up in our economy somehow soon, and so the first thing [to take away from this year's GTC] is useful AI has arrived."

Huang has historically been blasé about the prospect of job losses due to AI, memorably saying that programmers won't be able to 'raw dog' their work in future; he told the All-In podcast last summer, "We also know that…although everybody's job will be different as a result of AI, some jobs will be obsolete, but many jobs will be created.

"The one thing that we know for certain is that, if you're not using AI, you're going to lose your job to somebody who uses AI. That, I think, we know for certain. There's not a software programmer in the future who's gonna be able to hold their own typing by themselves."

But to state the obvious, software engineering is not really the most representative job sector when it comes to the impacts of AI. For one thing, someone in a call centre who loses their job to AI won't necessarily neatly transfer their skills into a tech career. Huang's on-stage comments only discuss job losses in the tech industry, but it's hard not to feel that he's kind of ignoring the wider issues.

Well, don't worry tradespeople, Huang didn't forget about you in comments he made to Channel 4 last year, saying, "If you're an electrician, if you're a plumber, if you're a carpenter, we're going to need hundreds of thousands of them. To build all of these factories."

I am being more than a little sassy. The fact that Huang's visions of the future revolve entirely around AI infrastructure is hardly surprising given that the data centre segment of Nvidia's business raked in a total of $75.2 billion last quarter. Still, it's a no less narrow and bleak vision of the future; I'm not sure about you but I'm not looking forward to a horizon dominated by data centres.

If you are aware of AI, you are likely also aware of the word 'agentic'. Effectively, as AI gets more powerful, it is supposed to run your tasks autonomously with less oversight, and Nvidia CEO Jensen Huang thinks that is the future of personal computing.

In a Q&A at Computex 2026 attended by PC Gamer, Huang was asked why Nvidia decided to get involved in the laptop market now. With the official unveiling of its SoC chip, RTX Spark, Nvidia is ready to enter the gaming laptop space, but with the memory crisis ongoing (and Nvidia already doing phenomenally well with AI), one would assume the profit margins aren't as high in this area.

He said, "The real question is, can we make a contribution? If we can't make a contribution, and it's a marginal contribution, we won't do it. Can we help reinvent the PC?"

He continued, "If you get a chance to reinvent the single most important instrument, the single most important tool of humanity, what you and I grew up with [that] defined just about everything about our lives, and we have an opportunity after 40 years to go reinvent it for the age of AI."

Yeah, it's probably no big shock that the company that owes its sudden explosion into being the most valuable company in the world to AI also thinks that AI is the future. Huang told us that Nvidia still builds graphics cards, "and we do it insanely well, and we still do it insanely well today."

He mentioned Nvidia's history in the personal computing market and noted the RTX Spark took three years and collaboration with Microsoft and MediaTek, plus hundreds of people, to get where it is today.

Huang said that personal computers in the future will not be ones that only react when you actually use them. He said, "In the future, when we leave it, you know what, we're talking with it all the time. I'll be chatting, you know, in WhatsApp with my agent, and it's doing stuff. And my agents are going to have names, and they're on my WhatsApp, and we're just chatting all the time. I'll be talking to it, and it's going to be talking back; it'll call me."

Huang excitedly told the press, "That is the personal computer future. Tell me that's not R2D2. Tell me that's not robotics. Tell me that's not cool."

Eh, I think that's not cool, and I certainly don't want my PC running autonomously. Ignoring the environmental costs of AI, the effect on the personal PC market, and even the Microsoft co-authored paper that suggested regular generative AI use leaves users with a "diminished skill for independent problem-solving", I simply don't like the privacy implications of leaving all your data in the hands of the black box that is generative AI.

Huang does think that it will be widely adopted, anyway. "We're going to redefine how people think about computers." He continued, "I believe that people, many, many people, will have this at home, just like they have a car at home. Soon, the agent is going to be so valuable to you, you want it to be sitting in a nice box, sitting in a nice computer, secure, performant, something you could carry with you, something you would use for a long period of time."

Nvidia's first full SoC for the PC, RTX Spark, is finally here. But could it form the basis of a killer gaming handheld? Superficially, that seems like a bit of a no-brainer, what with Nvidia's dominance in gaming graphics. But comments from Nvidia CEO Jensen Huang yesterday make that appear unlikely.

Speaking after his Computex keynote, Huang responded to a question about the possible use of RTX Spark in a handheld.

"If somebody wants to do it, you know, we'll work with them on it. But right now we're really focused on doing something that is just such a big deal, reinventing the PC after 40 years," Huang said.

He went on to explain what a "gigantic project" it is for Nvidia just to launch a PC chip. "Remember all of these applications in the Windows world, the x86 world, we have to prove that they work fantastically, and all the games they have to have anti cheat turned on. And so all of that stuff is really, really hard," Huang explained.

"It took us three years working with Microsoft and two and a half years working with MediaTek to get here, hundreds of people, that's how hard it is, and that's why everybody's so excited about it," Huang says of RTX Spark.

It's all part of his plan, it seems, to reinvent the PC in the age of AI. "Can we help reinvent the PC? And, boy, if you get a chance to reinvent the single most important instrument, the single most important tool of humanity, what you and I grew up with defined just about everything about our lives, and we have an opportunity after 40 years to go reinvent it for the age of AI. Wow, we're not going to sit around, not let it get done," Huang said.

In that context, you can see how making a gaming handheld out of RTX Spark is a bit, well, tangential. Is it yet another indication that gaming is now a very low priority at Nvidia? Possibly.

Of course, the full RTX Spark Chip is probably not a goer for handhelds. It's got 20 Arm cores and a GPU with pretty much identical specs to a desktop RTX 5070 GPU. That's surely too big and too powerful for a handheld, even if Nvidia is claiming its battery life will be "much better than anything you've seen before on RTX laptops."

As I understand it, however, there is a smaller version of RTX Spark coming with fewer CPU cores and a GPU less than half the size, codenamed N1 as opposed to N1x for the full-size RTX Spark chip. And that could be a much better candidate for a gaming handheld.

The thing is, if Nvidia was actively working with partners on an RTX Spark-based gaming handheld, you'd think Huang would have answered that question quite differently. As it is, he's clear that's not where Nvidia's "focus" is right now. Which probably shouldn't be a surprise, as gaming really doesn't seem to be a high priority at Nvidia of late.

Nvidia CEO Jensen Huang called Taiwan the "epicentre of the AI revolution" this week, after commenting about plans to invest $150 billion in the country each year. The company also plans to build new headquarters in Taiwan, a project that is planned to cost $1.3 billion itself and create 4,000 jobs.

At a launch event in Taipei for the planned Nvidia HQ, Jensen Huang said, "Four years ago, five years ago, Nvidia was spending about 10, 15 billion dollars a year in Taiwan. Now we're spending 100, going to 150 billion dollars in Taiwan each year."

The comments come after AMD's own announcement last week that it would be investing at least $10 billion into Taiwan tech to 'accelerate next-gen AI infrastructure'. Jensen Huang did not say for how many years Nvidia intends to invest such an eye-watering amount into the country. Otherwise, ground will be broken for Nvidia's new headquarters later this year, and the build is estimated to be complete by 2030 (via Reuters).

"Taiwan is the epicentre of the AI revolution," Huang went on to say, "This is where the chips come, ​packaging comes, this is where the systems are made, this is where AI supercomputers were created. The number of partners we work with here in ‌Taiwan, incredible."

Taiwan is already the base of operations for the largest semiconductor manufacturer in the world, TSMC (not to mention all the other hardware companies that call it home). Huang has previously said "Without TSMC, there is no Nvidia today" and described the semiconductor company as 'the pride of Taiwan.'

It's interesting to compare and contrast these developments to Nvidia's relationship to China. For a start, Huang has repeatedly bemoaned the company's dwindling market share, saying earlier this month that as far as China's AI hardware market is concerned, Nvidia has "now dropped to zero." This is largely due to tense trade relations between China and the US, with the export of AI chips to China being a particular flashpoint.

Earlier this month Huang, alongside representatives from Micron, and Qualcomm, boarded Air Force One with US President Donald Trump in a bid to repair trade relations with China. The US approved the sale of Nvidia's second best AI chip to 10 Chinese firms—though at time of writing China has not yet approved the deal.

Nvidia's latest earnings call said almost nothing about the gaming business you and I know it for—though it's not hard to see that this part of the business is largely overshadowed by the cash AI is continuing to throw around.

Nvidia announced record revenue during the first quarter of 2026, seeing an 85% year-on-year increase overall. Bringing in a total of $81.6 billion, money made from AI infrastructure makes up a huge chunk of that. For instance, the data centre segment of the business itself saw a 92% revenue increase from last year, raking in a total of $75.2 billion.

“The buildout of AI factories—the largest infrastructure expansion in human history—is accelerating at extraordinary speed,” says Nvidia CEO Jensen Huang.

He made similar remarks during a recent call with investors, saying, "Demand for AI infrastructure continues to expand at an unprecedented pace. The buildout of AI factories is accelerating. The value of NVIDIA AI infrastructure is rising."

According to Huang, frontier model companies are eager to snap up Nvidia's AI 'superchip', Vera Rubin in particular.

Per today's press release, Huang goes on to say, "Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries. NVIDIA is uniquely positioned at the center of this transformation as the only platform that runs in every cloud, powers every frontier and open source model, and scales everywhere AI is produced—from hyperscale data centers to the edge.”

With all of that in mind, it's not hard to understand Nvidia's continuing popularity—or the fact that its market capitalisation breached $5 trillion last year (it's currently hovering around $5.30 trillion at the time of writing). This past quarter's $81.6 billion in revenue represents only a 20% over the quarter before it, though that's still a sharp uptick—and I'm willing to bet that such astronomical growth cannot continue forever. When that line will flatten is anyone's guess, but I have some theories about what might cause it.

In a tale as old as Blackwell, Nvidia has managed to make it through yet another quarterly report with nary a mention of gaming. Well, okay, there was one mention of gaming, but that was basically just to say it's now being considered subsumed under—you guessed it—an AI segment of the business. Along with the other segment which is, er... also AI.

"We have 2 market platforms," says CFO Colette Kress. "Datacentre and edge computing... Edge computing highlights devices for agentic and physical AI. Including PCs, gaming consoles, workstations, AI RAN base stations, robotics, and automotive."

Heck, graphics cards for gaming don't even get a specific mention—they'll come under "PCs", I assume. And the "gaming consoles" the company mentions is presumably refers to the Nintendo Switch 2, which does feature an Nvidia GPU.

If we look to Nvidia's earnings report, we can see that edge computing revenue totaled $6.4 billion (up 29% year-on-year), compared to a record $75.2 billion in datacentre revenue. With GPUs for PC gamers presumably making up just a small part of that $6.4 billion figure, I suppose it's easy to see why Nvidia would drop all mention of them. Especially considering this is an earnings report talking to investors and the city primarily, and they only care about one thing, AI monies.

Still, it doesn't hurt any less, does it? We are your origin, Jensen, damn it!

It also doesn't seem like the company is expecting things to change anytime soon, given Nvidia EVP and CFO Colette Kress says "demand for AI infrastructure continues to expand at an unprecedented pace." All steam ahead on the AI train seems to be the guiding line.

It makes sense from a business perspective, and just by being a small part of the company's revenue doesn't mean it will abandon PC gaming or anything like that. It's just a question of whether the PC gaming division will get the attention it deserves or whether it will be left in the wake of AI acceleration. Not to be too much of a doomer about all this, but if DLSS 5 is anything to go by, I'm not holding my breath.

If you aren't caught up on the situation, US President Donald Trump, alongside representatives from Micron, Qualcomm, and Nvidia, all boarded Air Force One a few days ago to take a trip out to China and nurse the rocky trade relationship between the two countries. From that trip, America was hoping to trade some AI chips with China, but not quite enough for it to take the lead in the AI space race. Either way, it might not have gotten past China's officials yet.

The US approved the sale of Nvidia's second-best AI chip, the H200 to 10 Chinese firms yesterday. This would total 75,000 units each. As reported by Bloomberg, Trump said on Friday that China has not yet approved this deal from its end, “because they chose not to, they want to develop their own.”

Despite this declaration, Trump does say that the conversation came up and he reckons "something could happen on that."

Trump has not yet elaborated on what this means, what could happen, or how those talks went. However, Trump has reportedly been chatting to Chinese President Xi Jinping about what guardrails could be implemented on this tech going forward. When asked what kind of guardrails these would be, Trump reportedly said, "Standard guardrails that we talk about all the time."

Notably, China reportedly approved the import of H200 GPUs just a few months ago, but the US government put caps on how many could be sent to the region. It's been a rather tumultuous time for the two entities, with both banning, unbanning, taxing, and untaxing the AI chips.

Nvidia's CEO Jensen Huang has historically been very pro-trade when it comes to AI tech and China. When Nvidia effectively left the Chinese market due to import bans imposed late last year, Huang argued, "it's important to be mindful that what harms China could oftentimes also harm America".

Just last month, Huang bemoaned this market drop and argued the US should export AI "like crazy" to China. It's naturally within the interest of Nvidia to sell its AI tech to whoever will take it, as it owes the growth of AI for it becoming the world's first $5 trillion company, after all. Though, the company says its share in China is "zero" today.

And, in turn, exporting some AI chips would be beneficial to the US too, as it can claim taxes on that tech. But all parties seem to be aware that China cannot over-rely on American AI technology. Huang said last year that "we don't have to worry" about the Chinese military using AI chips because "they simply can't rely on it".

And so, the US and China (and by extension, Nvidia) seem to be at a stalemate. Whether or not Trump's big trip will see any returns on American investment is anyone's guess, but he seems pretty positive about it anyway.

In the midst of a pretty strained trade relationship with China, US President Donald Trump recently took a jet full of tech leaders to the country to negotiate deals. The first of which appears to be the approval of sales of Nvidia's second most powerful AI GPU, the H200, to the region. The caveat is that it's just 10 firms getting them for now.

After initial reports suggested Trump forgot to invite the Nvidia head, Trump confirmed yesterday that Jensen Huang was, in fact, sat on Air Force One, alongside the likes of Elon Musk and representatives from Qualcomm and Micron. His goal was to "open up China so that these brilliant people can work their magic."

As reported by Reuters, Alibaba, Tencent, Bytedance, JDcom, Lenovo, and Foxconn are said to be among the companies allowed to purchase the chips. Lenovo is the only company to have confirmed as such to Reuters directly. Sources close to the matter say that approved companies can purchase up to 75,000 chips, though Chinese firms are reportedly still waiting on guidance from the Chinese government to see if the firms can actually take delivery of them.

Back in March, the Chinese government reportedly approved the import of H200 GPUs, with the US to set the cap, so this is a continuation of that same discussion. At the time, the proposed 75,000 cap would also include AI chips purchased from Nvidia's competitor, AMD, and it's not yet clear if this restriction has stuck.

Nvidia has wanted to sell its AI GPUs to the Chinese market for some time, but both the US and Chinese governments have been major barriers. Both countries have banned the product at different times, with the US wanting America to be dominant in the AI race and China wanting its AI to be less reliant on foreign goods.

By October last year, Huang noted that Nvidia is "100% out of China" and also argued, "it's important to be mindful that what harms China could oftentimes also harm America."

Just last month, Huang reiterated this, noting that Nvidia holds 0% market share and urged the US to export AI "like crazy".

As pointed out by Reuters, the Chinese market once generated 13% of Nvidia's total revenue, so that revenue hit would be noticeable to the company. The AI boom has led to it becoming the first-ever $5 trillion company, but it won't want to stop there. It's in Nvidia's best interest to sell as many of its chips as possible, and the US government will also see the benefits of those sales. The balancing act for the US now is giving enough chips to see a tangible revenue increase without giving so many that China can win the AI space race.

Chris McGuire, the Senior Fellow for China and Emerging Technologies, tells Reuters this deal is not in the best interest of the US. McGuire argues that more chips to China means fewer chips to US firms, and therefore fewer resources pumped into American AI. They say, "It is remarkable that President Trump keeps getting convinced to put Nvidia’s interest ahead of America’s."

Us PC gamers simply have to watch as both entities mop up as much cash as possible, as we wait for the price of memory to eventually come back down. Thanks, AI.

President Donald Trump has had a hot and cold relationship with China over both of his presidencies. But perhaps the strangest era of this relationship came with the explosion of AI. As China aims to become more independent regarding its hardware, Trump is hoping to open it up to American trade.

After reports suggested Nvidia CEO Jensen Huang's invitation to China was lost in the mail, Trump took to Truth Social to set the record straight. Calling him the "Great Jensen Huang", Trump says, "In actuality, Jensen is currently on Air Force One and, unless I ask him to leave, which is highly unlikely, CNBC’s reporting is incorrect or, as they say in politics, FAKE NEWS!"

As well as Huang, Trump has also invited Larry Fink, Elon Musk, representatives from Micron, Qualcomm, and, of course, "Tim Apple" (Tim Cook, the soon-to-be ex CEO of Apple). This is the first presidential visit to China since Trump's first visit in 2017. Trump says in his Truth Social post that he will "be asking President Xi, a Leader of extraordinary distinction, to 'open up' China so that these brilliant people can work their magic."

Huang is an interesting figure to bring along, as he has long been in favour of supplying technology to China. Just last week, he bemoaned Nvidia's market share in the region and argued the US should export AI 'like crazy'.

In May last year, he said "China is right behind us" to encourage American AI growth, and said he was in favour of sending Nvidia chips because the country could simply make its own if not. Both Nvidia and the US government benefit financially from selling Nvidia chips to China.

Two months later, Huang said "we don't have to worry" about the Chinese military using US chips, because "they simply can't rely on them." By October, Huang noted "we went from 95% market share to 0%" due to a series of bans and taxes, both from the US and China. However, earlier this year, China reportedly approved imports of Nvidia's H200 AI GPUs, even if the US government could cap the amount going to individual Chinese companies.

Nvidia itself has risen to over $5 trillion in net worth, the first company to ever do so, because of its developments and role in the growth of AI. If it wants to continue growing its worth, Nvidia will want its fingers in many different pies, supplying its goods to whoever can take them. Having Huang in tow could be a good sign for future AI cooperation between the two countries.

We'll have to wait and see to find out if anything good comes out of this exchange for either country or the companies involved in talks, but there's clearly a lot of effort put into this exchange. Trump and his crew are currently in China and are due back in the US by May 15, though we may not see the outcome of these exchanges for some time.

Jensen Huang, the CEO of Nvidia, was recently awarded an honorary doctorate in science and technology from Carnegie Mellon University in Pittsburgh, Pennsylvania, and Intel's CEO, Lip-Bu Tan, was the one to give Huang his doctoral hood. At the same time, Tan took the opportunity to affirm that Intel and Nvidia are working on new products.

In the post congratulating Jensen Huang, Tan says, "Intel and Nvidia are collaborating to develop exciting new products!"

We have known about collaboration between the two companies for some time. Late last year, Intel and Nvidia announced combined CPU and GPU products for use in both consumer PCs and AI servers. To add to this, Nvidia took a $5 billion stake in Intel.

And just last month, there was a rumour that some future Nvidia AI GPUs will use Intel Foundry technology for some of their components. So this new statement only adds to the sudden companionship between the two now financially-linked companies.

It's even currently suggested that Intel's Serpent Lake will be its first collaboration chip with Nvidia. This chip is supposed to be going super heavy on the GPU for AI workloads and will reportedly have Nvidia's next-gen Rubin GPU technology and will support LPDDR6 memory. Memory crisis be damned.

Nvidia can no longer rely on Chinese trade, due in part to global tensions, and diversifying production away from TSMC doesn't seem like an awful move with that in mind. The US Government has also made it clear that it prefers chips made on US soil.

All of this is a far cry from how bad things looked for Intel just a few years ago. But things have been looking a bit more hopeful for the company as of late. Panther Lake testing shows that its latest mobile chips are surprisingly performant and power efficient. Late last year, the US Government gave financial support to the company, with it taking even more if Intel lost control of its chip manufacturing business, so it's in both Intel's and the US Government's interest for both to thrive.

Working with Nvidia, being a company worth $5 trillion, seems like a pretty good way of making that happen. Though whether this relationship amounts to much is yet to be seen.

"We have now dropped to zero." So, says Nvidia CEO Jensen Huang of the company's market share in China's AI hardware market. Needless to say, Huang thinks this is a big mistake and Nvidia should be allowed to sell as many AI chips to China as the country wants to buy.

Speaking to the Special Competitive Studies Project podcast, Huang is clear that he thinks the upside to selling AI chips to China clearly outweighs any concerns over allowing China access to America's most advanced technology.

“Conceding an entire market the size of China probably doesn’t make a lot of strategic sense,” Huang says. “And so I think that that has already largely backfired.”

“Maybe it made sense at the time, but I think the policy really needs to be dynamic, and it needs to stay with the times,” he concludes.

His broader pitch involves the idea that the current AI revolution is akin to the industrial revolution and the US needs to be at the forefront of it all. "We were the front runners in applying technology in the last industrial revolution, we need to be careful not to be the last in this industrial revolution," he explains.

To get the full benefits of that, the US needs to "export like crazy" Huang says, resulting in an "incredible trade imbalance" in the US's favour. If this all makes immediate sense, Huang doesn't explain how the US will stay ahead with this strategy.

As Huang himself explains, the AI industry is like a layer cake with five levels: energy production, AI chips, infrastructure like data centers, AI models and finally AI applications.

By Huang's estimations, the US is behind in at least some of those categories, most obviously energy production. And he doesn't explain how supplying China with the best available chips in the short term means China won't catch up or surpass the US in all areas in the medium term.

In short, his argument seems to boil down to something ironically unsophisticated given the complexity of all this AI tech. Make hay while the sun shines, seems to be his main point. Which would be great for Nvidia, no doubt. But it's less obvious that it's a sustainable long term strategy for the US as a whole.

To paraphrase some lyrics from my mispent youth pining for a Hot Topic, 'this ain't a scene, it's a goddamn AI arms race'. The preview of DeepSeek V4 is now live, and given that the AI giant was reportedly not so keen to grant Nvidia and AMD early access to the new model, the American AI industry has been equally keen to outpace China-based businesses any way it can. Case in point, Nvidia is really pushing OpenAI's GPT-5.5.

DeepSeek wouldn't give Nvidia the sneak peek, so 10,000 of its employees got an early look at OpenAI’s latest frontier model instead. The company went with a widespread rollout of Codex, specifically, which is OpenAI’s agentic coding application powered by GPT-5.5. This has apparently resulted in big efficiency wins. "Debugging cycles that once stretched across days are closing in hours," says Nvidia.

The Nvidia blog continues in a similarly effusive tone: "Experimentation that previously required weeks is turning into overnight progress in complex, multi-file codebases. Teams are shipping end-to-end features from natural-language prompts, with stronger reliability and fewer wasted cycles than earlier models."

As with anything agentic, security was top of mind for the rollout. So, to "ensure maximum security and auditability" (and presumably to stop Codex from getting into anything it shouldn't), all participating Nvidia employees were given a cloud-based virtual machine to run the AI agent from. From there, Codex can read company data but can't directly edit it (or indeed, delete). To oversimplify, they locked the bot in a virtual plexiglass box.

The blog post also surfaces similarly gushing praise from employees, with choice quotes calling Codex's results “mind-blowing” and “life-changing". Codex was rolled out across plenty of company departments besides engineering and development, with folks working in "product, legal, marketing, finance, sales, HR, and operations" also getting to grips with the application (personally, I would love to hear the honest Codex thoughts of a grumpy office admin).

Such enthusiasm from Nvidia is no surprise, though. For one thing, the two companies have an ongoing relationship to the tune of billions (though Nvidia has scaled down what was originally a $100 billion investment in OpenAI, to a slightly less eye-watering $30 billion more recently).

Second, GPT-5.5 runs on Nvidia GB200 NVL72 rack-scale systems. This set-up is apparently "capable of delivering 35x lower cost per million tokens and 50x higher token output per second per megawatt compared with prior-generation systems," making it an economically appealing enterprise model. Company head Jensen Huang quipped to OpenAI CEO Sam Altman over email, "Fire up those Blackwells. We need more tokens!"

The world of AI boffins really is baffling, sometimes. I'm finally used to the idea that I can chat to a non-sentient, very knowledgeable and occasionally hallucinatory machine, and already we're talking about AI models interacting with AI models. It's only in such a world that Nvidia CEO Jensen Huang could think to utter the seemingly contradictory statement: "Proprietary versus open is not a thing. It’s proprietary and open.”

He said this in a recent GTC panel discussion with various AI company CEOs, and the entire discussion is framed around this mix of open and closed models. The others seem to agree with the Nvidia CEO that open plus proprietary is the way.

It's important to note that they aren't saying that you can have proprietary open-source code, as that would indeed be a contradiction. You can have a company make its code open to public viewing but requiring permission to actually use, but this wouldn't make it open-source, as open-source code must have a license from the Open Source Initiative (OSI), which requires the code to be allowed to be "freely used, modified, and shared."

Instead, they mean that there exist broader open foundation models alongside more specialised proprietary ones, and this is becoming increasingly relevant as AI "orchestration systems" are starting to crop up, which interact with other tools. These tools can and presumably will—assuming the AI industry continues on an upward trajectory—use AI themselves. So, we're essentially talking about AI interacting with AI, orchestrated by AI.

Cursor CEO Michael Truell explains this system:

"I think we're going to see the rise of these compound agents that can be smarter than any one model on their own and mix them all together... All you have to do is delegate your task. You don't have to worry about which model is good at what; it's for the orchestration system to figure it out. These sub-agents are like musicians, and the models are just instruments, and the work that AI gets done for you is the symphony or the music that they play."

Jensen agrees:

"Even in a closed-model company, I really believe that open models will be used as part of the agentic system, where the closed model is your crown jewels."

So, if you've only just started getting used to chatting to a single AI model, the bad news is the AI industry has already ploughed ahead into more complicated pastures.

Anyone who's been paying attention to the hype surrounding OpenClaw will probably already know this, though. This is an open-source AI that essentially acts as a middleman between your various accounts, applications, and, importantly for this discussion, your other AI subscriptions.

I suppose it is a little like a conductor of an orchestra. A very mechanical, lifeless, orchestra. And when our software and even our operating systems are becoming more *gulp* agential, it's not difficult to envision a world where open-source AI models interact with proprietary agential ones, and we oversee the former.

But just to fan the flames against techno-determinism for a moment, why couldn't all these models be open-source?

Reflection AI CEO Misha Laskin seems to agree:

"I think the other big misconception is on open models, that somehow open models are fundamentally going to be behind the frontier... I think that's just an artifact of the time where we are today. There's nothing fundamentally different between an open and a closed model."

In which case, why not have it all open?

I suppose the argument would be that there will always be a need for proprietary models for different use cases. And there might always be room for specialism when it comes to data sets, training, and implementation.

On that note, I'll let Huang take us over the finish line with a similar sentiment:

"We love a world where there's proprietary products, but we also need a world where a whole bunch of companies and different industries in different domains need models as a technology that we could then transform into products."

At least, I think that's a similar sentiment. I can't quite tell.

President Trump has appointed members to a newly reestablished science and technology advisory council, the President's Council of Advisors on Science and Technology (PCAST). And there are a fair few new faces in there—new kinds of faces, in fact, because the new board seems pretty business-heavy.

In general, the members so far—which total just 13—seem weighted towards science-y and certainly smart but nevertheless business-oriented people, unlike many members in previous councils, which were more academic and researcher-heavy.

Such advisory councils have existed since President Roosevelt's Science Advisory Board. The previous one, reestablished by president Biden in 2021, also appointed AMD CEO Dr. Lisa Su as a member, but there are plenty of new appointments, including Meta CEO Mark Zuckerberg and Nvidia CEO Jensen Huang.

Here's the list:

• Marc Andreessen - venture capitalist, co-founder of Andreessen Horowitz and Netscape
• Sergey Brin - Google co-founder and current AI researcher
• Safra Catz - Oracle executive vice chair and ex-CEO
• Michael Dell - Dell founder, chairman, and CEO
• Jacob DeWitte - Oklo co-founder and CEO
• Fred Ehrsam - Coinbase co-founder, Nudge co-founder and CEO
• Larry Ellison - Oracle CEO
• David Friedberg - The Production Board and Ohalo Genetics CEO, All-In podcast host
• Jensen Huang - Nvidia CEO
• John Martinis - Professor of physics, University of California
• Bob Mumgaard - Commonwealth Fusion Systems CEO
• Lisa Su - AMD CEO
• Mark Zuckerberg - Meta CEO

In the president's executive order, he explains the need for this council:

"Today, a new frontier of scientific discovery lies before us, defined by transformative technologies such as artificial intelligence, quantum computing, and advanced biotechnology."

"As our global competitors race to exploit these technologies, it is a national security imperative for the United States to achieve and maintain unquestioned and unchallenged global technological dominance. To secure our future, we must harness the full power of American innovation by empowering entrepreneurs, unleashing private-sector creativity, and reinvigorating our research institutions."

"This order establishes the President’s Council of Advisors on Science and Technology to unite the brightest minds from academia, industry, and government to guide our Nation through this critical moment by charting a path forward for American leadership in science and technology."

The council can have a maximum of 24 members, and this will include the already-existing Assistant to the President for Science and Technology (APST) Michael Kratsios, and the Special Advisor for AI & Crypto David Sacks.

"The remaining members", the executive order says, "shall be distinguished individuals and representatives from sectors outside of the Federal Government appointed by the President."

While nominally and primarily created to advise on on science, technology, education, and innovation policy, it seems the PCAST will also advise on other areas: "The Council shall also provide the President with scientific and technical information that is needed to inform public policy relating to the American economy, the American worker, national and homeland security, and other topics."

Members of the PCAST will also be able to ask heads of other agencies and departments for "information concerning scientific and technological matters" when required.

Looking at discussions online, there's obvious concern over the lack of academics, scientists, researchers, and professors. The CEO-heavy list is defended by others on the grounds that CEOs of science and technology-related businesses should be better placed than the researchers they employ to cut through to what's most important for policy decisions.

I'll leave all that discussion to the bigwigs. From my perspective, all I can say is it's not that surprising to see such a member list. The inclusion of Jensen Huang almost went without saying, given he's probably the world's biggest hotshot in this new AI era.

And who knows? Maybe the Nvidia CEO remembers his roots and whispers something for us PC gamers in the president's ear. Wishful thinking, I know.

I get the sense that Nvidia CEO Jensen Huang and I are quite different people. He's the head of the world's most valuable company, and a massively influential tech figure. I'm a long-haired hardware writer that had beans on toast for lunch. That sort of thing.

However, when it comes to our opinions on games, I think we might have more in common than first thought. Appearing on the Lex Fridman podcast, Huang was asked what he thought was the greatest or most influential game ever made, and he responded without hesitation:

"Doom. I would say Doom, from the intersection of the cultural implication, as well as the industry turning a PC into a gaming device. That was a very important moment."

"Now of course, flight simulation companies were before it, but they didn't have the popularity that Doom did to have made the industry turn the PC from an office automation tool into a personal computer for families and gamers and things like that," Huang continues.

"And so Doom was really impactful there. From an actual game technology perspective, I would say Virtua Fighter. And so we were great friends with both of [the developers], you know".

While many would argue that other games paved the way first, Doom's place in gaming culture is so cemented at this point, even your grandparents have heard of it. Actually, given the endless march of time, many of your grandparents probably played it, too.

So it's nice to see Huang's instantaneous recognition of Doom as an incredibly influential game, the tendrils of which run deep within not just gaming, but our shared culture overall.

I fondly remember an ex-boss of mine scoffing at the idea that I played "those video games" in my spare time, and the moment I discovered a copy of Doom installed on his ageing laptop.

"I thought you didn't like games," I remember saying to him. "Oh, Doom?" He responded. "Yeah, that one's really good."

Yes it was. Is. Shall always be. We've all got something in common, at the very least. Who knew?

Given Nvidia's status as the world's most valuable company, and the firm sitting at the forefront of the AI boom, I doubt CEO Jensen Huang has many regrets. Still, in a recent appearance on the Lex Fridman podcast, Huang confirmed that his future could have looked very different if he'd accepted a position as the chief executive of chipmaking juggernaut TSMC.

The company's founder, Morris Chang, wrote in his autobiography that Huang was offered the top position at the firm in 2013, but declined. When asked to confirm the story, Huang said:

"The story is true. I didn't dismiss it, but I was deeply honoured. And of course, I knew then, as I know now [that] TSMC is one of the most consequential companies in history.

"Morris is one of the highest regarded executives and business and personal friends that I've had in my life, and for him to ask is... I was humbled and really honoured", Huang continued.

"But the work that I'm doing here is really important, and I've seen, you know, in my mind's eye, what Nvidia was going to be and the impact that we could have. And it was really important work, and it's my responsibility, you know, my sole responsibility to make this happen."

"And so I declined it", Huang concludes. "Not because it wasn't an incredible offer. It's an unbelievable offer, but I simply couldn't take it."

Despite having declined the position (and publicly giving TSMC the hurry up in recent months), Huang's admiration for the chipmaking titan is clear to see.

"The deepest misunderstanding about TSMC is that their technology is all they have, that somehow they have a really great transistor, and if somebody shows up [with] another transistor, game over", said Huang.

"Their technology makes the company special, but their ability to orchestrate the dynamic demands of hundreds of companies in the world as they're moving up, shifting out... increasing, decreasing, pushing out, pulling in, changing from customer to customer. Wafer starting, wafer stopping, emergency wafer starts.

"So their system, their manufacturing system, is completely miraculous, I would say", Huang continued. "Then the second thing is their culture. This culture is a simultaneously technology focused, on one hand, advancing technology [while being] simultaneously customer service oriented on the other hand.

"A lot of companies are very customer service oriented, but they're not very technology excellent. They're not at the bleeding edge of technology.

"Somehow they've balanced these two, and they're world-class at both. And then probably the third thing is the technology that I most value in them, that they created. This intangible called trust. I trust them to put my company on top of them. That's a very big deal."

So, while Huang opted to stay and captain the good ship Nvidia towards extremely lucrative shores, it seems his admiration for TSMC is undiminished. And while both companies are raking in the profits as the AI boom continues to explode, it seems the relationship between the two has never been stronger.

"I don't know how many tens, hundreds of billions of dollars of business we've done through them, and we don't have a contract", Huang concludes. Quite the handshake deal, isn't it?

After all the furore surrounding Nvidia's DLSS 5 announcement, which was met with a mixture of curiosity around its AI capabilities and outright objection to the aesthetic changes it appears to make to existing games, CEO Jensen Huang has pushed back against the critique.

Despite stating that the DLSS 5 backlash was "completely wrong" late last week, the Nvidia chief has since taken a more thoughtful tone in an appearance on the Lex Fridman podcast. When asked to explain the drama around DLSS 5, Huang said:

"I think their [gamers] perspective makes sense, and I can see where they're coming from, because I don't love AI slop myself. All of the AI generated content increasingly looks similar, and they're all beautiful... so I'm empathetic towards what they're thinking.

"That's just not what DLSS 5 is trying to do," Huang continued. "I showed several examples of it, but DLSS 5 is 3D conditioned, 3D guided, it's ground truth structure data guided, so the artists determine the geometry. We are completely truthful to the geometry... in every single frame.

"It's conditioned by the textures, the artistry of the artists, and so every single frame it enhances, but it doesn't change anything."

Hmm. One of the problems with DLSS 5's announcement has been the mixed messaging around exactly how it operates, and I'm not sure Huang's words make things clearer. Certainly, a splitting of hairs between the terms "enhance" and "change" is debatable—and from the demos shown to date, it seems the latter is perhaps more appropriate to describe the infamous "yassified Grace."

"Because the system is open, you could train your own models to determine and you could even, in the future, prompt it," Huang continues. "So you can give it even an example, and it would generate in the style of that, all consistent with the artistry... and so all of that is done for the artist so that they can create something that is more beautiful, but still in the style that they want.

"I think that they [gamers] got the impression that the games are going to come out, the way games are shipped, and then we're going to post process it. That's not what DLSS is intended to do. DLSS is integrated with the artists. It's about giving the artist the tool of AI, the tool of generative AI. They could decide not to use it, you know?"

I think one of the interesting things to pull out of Huang's words is the use of future tense. You could train your own models. You could, in the future, prompt it. But, as was revealed in a recent Q&A session with GeForce Evangelist Jacob Freeman, what DLSS 5 appears to be doing in the demos shown to date is essentially applying an adjustable AI filter to already-rendered 2D frames, with some motion vector data thrown into the soup.

This is all really, really messy. What strikes me at this point is that the version of DLSS 5 shown to the public, and the messaging around how it operates, is still a muddle of AI terminology and odd process descriptions that, at points, seem to directly contradict each other.

And while Huang seems more empathetic towards the gamers' concerns, it does seem like what we've been shown to date is a very early version of something that, on a conceptual level, doesn't seem to have clearly defined parameters.

I guess all there is to do now is to wait for more demonstrations, technical deep dives, and really anything that gives us a clearer bead on what our AI-enhanced gaming future will actually look like. May you live in interesting times, as the old proverb goes.

Nvidia CEO Jensen Huang has responded to the widespread criticism of DLSS 5. Nvidia's new generation of upscaling technology majors on AI-enhanced lighting but also introduces generative AI at the geometry and asset level and can result in dramatic changes to the look of character models in particular. And that has many observers up in arms, or at least making fun of DLSS 5.

Tom's Hardware attended a Q&A at Nvidia's ongoing GTC event and queried Huang about the negative response to DLSS 5. According to Huang, the critics have it wrong.

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

Importantly, he said, developers can "fine-tune the generative AI" and that it "doesn't change the artistic control." Whether that's making a "toon shader" or making the game look like it's "made of glass," DLSS 5 apparently opens up all manner of possibilities, all of which are in the control of the developer.

Of course, the granularity of that control is likely critical here and remains somewhat of an unknown. It's not entirely clear if using DLSS 5 from a developer perspective will be like choosing from a relatively limited menu of "looks" or "styles" or if it's much more open ended.

If the former, well, that's when the fears expressed over the past day or so kick in. The idea that all games with be slathered with the same generative AI gloss is, essentially, what many object to.

But the reality could be both. In other words, there could be some pre-baked settings that developers can choose from for expediency while also having the option of diving in and getting fully involved in how DLSS 5 interprets everything from lighting to materials and assets.

Huang's comments certainly seem to suggest extensive developer control. "All of that is in the control — direct control — of the game developer," Huang said, "this is very different than generative AI, it’s content-control generative AI. That’s why we call it neural rendering."

The other problem with DLSS 5, at this stage at least, is computational intensity. For the demos Nvidia has been showing at GTC, DLSS 5 has been running on a second RTX 5090 graphics card in parallel to a primary 5090 running the game engine itself. That's obviously far from practical or cost effective.

Nvidia says it has DLSS 5 running on a single GPU "in the labs". But if so, why not show the demos running on that single GPU solution? Whatever, DLSS 5 in its current form is clearly a very demanding model and the question remains over whether Nvidia will be able to scale it down into something that can not only run on a single GPU, but can run on the kinds of more affordable GPUs that the vast majority of gamers use. It needs to run on RTX 5060s, not 5090s.

If there is an uncontroversial appeal to DLSS 5, it's the prospect of enabling the lighting realism of ray tracing and path tracing but without the debilitating computational load of calculating all that light bouncing around a scene. To deliver on that proposition, DLSS 5 will need to be far, far more efficient than the dual-5090 hardware setup required for the demo implies. And that improvement needs to come quickly. DLSS 5 will supposedly be released later this year.

During the Nvidia GTC keynote, company CEO Jensen Huang reiterated the company's commitment to gaming, stating that "This is the house that GeForce made." However, the company is still full steam ahead on AI, leveraging the tech to "revolutionise how graphics are made" in the form of DLSS 5.

We got our first look at the tech last night, and the response has been mixed to say the least. Resident Evil Requiem was one game used to showcase the upscaling tech, and while I personally don't mind seeing Leon S. Kennedy with even more scruff, the tech makes Grace Ashcroft look like a totally different person, with distinctly higher cheekbones and fuller lips. Nvidia has said devs will retain 'artistic control' with this tech but, in the case of Grace, it's hard not to feel like DLSS 5 has daubed her with AI beauty standards.

It's such a dramatic shift that plenty of PC gamers have been poking fun at DLSS 5, dismissing it as akin to a 'yassification filter'. Case in terrifying point, I stumbled across this Bluesky post that yassifies Requiem's stalker enemy, The Girl. Now that I've seen it, you can't unsee it either—you're welcome.

Elsewhere online, the memes have been similarly on point. In a similar vein to that downright haunting take on The Girl, developer Neal Agarwal reimagined The Password Game with a distinctly fleshy twist.

After that, I think you've earned a palette cleanser. Among Us developer Innersloth was quick to playfully imagine what DLSS 5 could do with its game. Similarly, the official Cult of the Lamb X account also had fun reimagining the game's similarly cartoon-y art style.

Meanwhile over on Reddit, r/PCMasterRace is perhaps predictably having a whale of a time dunking on DLSS 5. Besides a look-in from Handsome Squidward, an unfavourable comparison to Sonic the Hedgehog's original movie design, and even a throwback to Ecce Mono, the community turned their gaze to r/Nvidia. Alleging mods were deleting comments en masse, Redditors seized on yet another obvious DLSS 5 punchline.

Thanks Nvidia from r/pcmasterrace

Now, the case could be made that the tech's genuine improvement to environmental lighting is getting lost among all the memes. Furthermore, leveraging AI to get more out of older hardware, especially in the midst of a memory supply crisis that has made PC components even more expensive, is no small thing either.

To be fair to the tech, DLSS 5 arguably had a better showing in EA Sports FC—where the character models are even more closely based on real people in the form of recognisable sports persona. Unfortunately, the tech's implementation of photorealism in Starfield did not play well with that game's stiff conversation animations, creating a downright uncanny effect in my humble opinion.

DLSS 4's multi-frame generation felt like a genuine game-changer. DLSS 5 is attempting to change the game again, but so far that's looking far more literal than many would like. Here's hoping the implementation will be refined over the coming months, and I'll recognise Grace Ashcroft next time she stumbles over her own feet.

Launching in 2001, Nvidia's GeForce 3 series marked an important step for Nvidia, according to CEO Jensen Huang. In a YouTube video, Huang celebrates the 25-year anniversary by waxing lyrical about the card and what it means for the company.

"GeForce 3 was such a transition for us," Huang says.

"We introduced really the first successful mainstream graphics accelerator, Riva 128 and subsequently Riva TNT, Riva TNT2, and what we did well was recognising the graphics pipeline is really deep. Where we intercepted it was at exactly the right place.

"That entire pipeline stage, including the intense memory traffic, the texture processing, all of that was done in hardware."

He argues that computer graphics, at the time, "was looking exactly the same".

Nvidia's goal was reportedly to serve as a tool to get games looking different and expressive. The GeForce 3, with its pixel shaders and more flexible architecture, allowed a level of creative freedom to game developers. Huang argues that artists in games "can't be pre-coded."

Huang spends time reflecting on not only what the GeForce 3 did, but what has changed since. He notes the relatively small number of transistors in the GeForce 3—30 million—versus the several hundred billion that chips are working with now.

One other big change is power draw. Huang says, "This is what? 35 watts? We're now pushing on 3,500 watts."

Even looking at the 130 W-575 W needed to run the RTX 50-series cards, games have come along an incredible amount in the 25 years since the launch of the card. Gamers picking up the GeForce 3 in 2001 would be treated to classics like Max Payne, Civilization III, Microsoft Flight Simulator 2002, and Baldur's Gate II: Throne of Bhaal.

Gamers playing games now can play graphically impressive titles like Microsoft Flight Simulator 2024, Baldur's Gate 3, and other games that aren't just sequels to older games.

There were three central GeForce 3 cards: the GeForce 3, GeForce 3 Ti200 and GeForce 3 Ti500. The $500 GeForce 3 was considered the high-end card (which is a far cry from the $2,000 MSRP of the Nvidia RTX 5090), where the GeForce 3 Ti500 came in at around $350 and the GeForce 3 Ti200 fetched $150.

All three had a 128-bit bus, 64 MB of memory, four pixel shaders, one vertex shader, and they were all based on the 150 nm process size.

Still, as games of its era proved, great experiences aren't just about what you've got under the hood. And PC gamers were eating good in 2001, with all hundred or so MB of memory, and a CRT in tow.

To recap for those who've been recently resting under a cool, mossy rock, Phil Spencer has now retired from his role as CEO of Microsoft Gaming. His replacement is Asha Sharma, who joined Microsoft in 2024—as president of its CoreAI product. This has resulted in a wave of doomsaying for Xbox that leadership has since been keen to dispel.

But besides Sharma herself recently assuring that the gaming division won't "chase short-term efficiency or flood our ecosystem with soulless AI slop," Microsoft CEO Satya Nadella said the company will "always" invest in gaming during a recent internal Q&A.

Sharma hosted the session in which, according to a transcript verified by Windows Central, the pair discussed their long-term vision for gaming at Microsoft.

Nadella said that Xbox "at its best lifts the entire company." He also said, "The trickle from that excellence to the rest of the company becomes straightforward. I joke with [Nvidia CEO] Jensen Huang, if it wasn't for gaming, [Nvidia] wouldn't exist. Think about it, without DirectX, I don't think the entire GPU revolution, or the acceleration, would've happened."

"That's why I'm long on it. Phil, he's always talked to me about how gaming is the largest entertainment category—what is gaming in its most expansive form going forward?" Nadella goes on to elaborate, "This doesn't mean we walk away from what people are doing today—when we think about a AAA game on a console. The question is about where else can we go to extend that?"

He adds, "For me, we're long on gaming. We'll continue to invest, and we'll always do so."

As for Sharma, she reflected on her time among Xbox's various teams, saying that games can't always be "manufactured" like software, but instead need to be "crafted" by humans. She also said, "I'm spending a lot of time thinking about how I can empower these worlds, these stories, and these characters."

Sharma also shared that, as far as Xbox's current strategy is concerned, "everything is being relitigated."

Nadella then jumped in to add, "We have to make sure that the friends we have today, are the friends that you have tomorrow. You want to wake up feeling like your friendship has even grown stronger. We have to really make sure, whether it's console, whether it's PC, whether it's the lover of Forza, Halo—we really want to make sure they love us for what they expect us to do."

In other words, Xbox isn't going anywhere—but it's not looking to reinvent the green spokes of its wheel either. Reassurance that there is a long-term strategy for Microsoft Gaming is one thing, but concrete details of that strategy would very well have been another. Though, given the fact leadership is still in a transitional phase with all things Xbox still being 'relitigated,' perhaps some vagueness is to be expected.

But speaking of 'the more things change, the more they stay the same', Microsoft remains committed to releasing fresh hardware at some point in the future—despite a less-than-strong showing from the console side of things in recent years. Project Helix, the next-generation console, was just announced. However, beyond the codename, logo, and that it will "play your Xbox and PC games," information is thin on the ground.

OpenAI and Nvidia have had a tense relationship as of late. OpenAI is reportedly not very happy with Nvidia's GPUs, and Nvidia's plan to invest $100 billion in the company has stalled. Recently, in an interview with Nvidia CEO Jensen Huang at the Morgan Stanley Technology, Media & Telecom conference, he announced that OpenAI would instead be getting $30 billion.

He said: "So recently, there was a question about 'are we going to invest $100 billion in OpenAI?' Just for everybody's update, we finalized our agreement. We're going to invest $30 billion in OpenAI. I think the opportunity to invest $100 billion in OpenAI is probably not in the cards."

The reasoning he gives here is that OpenAI is going public and he believes "the revenues will more than follow" if OpenAI continues to get computer power from Nvidia. He says, "This might be the last time we'll have the opportunity to invest in a consequential company like this."

That investment is one that would give Nvidia some ownership, but the partnership with Nvidia to buy its stock will also benefit the gaming company long-term. Effectively, Nvidia doesn't need to invest more as it doesn't have to.

On that same note, Nvidia said: "Our $10 billion investment in Anthropic probably will be the last as well." Huang goes on to talk about Nvidia's role in the AI boom, adding, "We expanded OpenAI's reach of capacity to AWS. We're ramping AWS like mad. We're ramping them as hard as we can so that OpenAI has accessed even more capacity."

$30 billion is still a lot of money, though less than a third of the investment round OpenAI announced just over a week ago. Nvidia is the most valuable company in the world thanks to its efforts in the rapid growth of AI, and that growth is what's stopping you from buying memory at a reasonable price.

This is to say, even if Nvidia isn't investing as much as one thought it would just a little while ago, the AI industry shows no sign of slowing down. Nvidia has also taken a pretty wide swing, when it comes to which companies it is throwing its support behind; it wouldn't invest so much cash if it didn't think it would get it back.

Nvidia CEO Jensen Huang sat down for a discussion at the Morgan Stanley Technology, Media and Telecom Conference yesterday and spoke on a variety of topics, including his company's place within the gaming industry.

However, the discussion then ranged into AI and data center topics, which is no surprise given Nvidia's recent stratospheric revenue announcements for the data center side of its business.

The company's AI hardware is raking in huge amounts of money at the moment, which is believed to be the primary factor behind current electronics supply chain issues, particularly when it comes to the ongoing memory crisis and wafer production capacity. Nvidia's AI factory revolution is well underway, and it looks to be straining current supply lines to their very limits.

When asked about various constraints upon the AI token economy, including a lack of supply of memory, power, and other factors involved with spinning up huge amounts of AI hardware at an unprecedent rate, Huang responded:

"I love constraints. And the reason for that is because in a world of constraint, you have no choice but to choose the best. You can't squander your choice. If the data centers—if the land power and shell is constrained, you're not going to randomly put something in there just to try it out.

"You're going to put something that you know for certain is going to deliver the tokens per watt, that you know for certain is going to allow you, from the moment you secure the capacity, we're going to 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."

"The second thing is Nvidia is, as you mentioned, working at such a large scale", Huang continued. "One of the things that we do with our capital is to secure supply chain, so that when [Microsoft CEO] Satya [Nadella] asked me to help them stand up a few gigawatts, the answer is no problem.

"And the reason for that is, I've got all the memories, I've got all the wafers, I got all the CoWoS. 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. That's one of the reasons why Nvidia's balance sheet being strong is so strategic."

That's certainly good for Nvidia. Given the company's vast economic capabilities at the moment (Nvidia is valued at $4.48 trillion at the time of writing), it can use its considerable funds to secure supplies for its hardware in ways that other providers could merely dream of.

However, it does leave the rest of the market with relatively little to work with, something that is very advantageous for the green team, and considerably less so for various other companies.

Speaking specifically about memory, Huang said: "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 going to use it. That goes a long way. You might as well take that to the bank, as many of them have. And so I think the fact that everything is scarce is fantastic for us."

And why would the Nvidia head honcho think otherwise? With its AI hardware continuing to experience phenomenal demand, and enough money (and reputation) in stock to allow for favourable contracts and a first-in-line position for manufacturing capability, the future sure looks rosy for both Nvidia and Huang right now. And, indeed, the companies that work with it.

That being said, while fears of an AI bubble continue to rumble on in the background (despite Huang, and others, protestations to the contrary), and the financial market's occasional wobble in response to the potential knock-on effects of our brave new, AI-focussed world, it's something of a guessing game as to how long this vast AI expansion can continue.

And indeed, whether suppliers can ever hope to keep up, even with mass expansion plans for chipmaker TSMC and memory manufacturers well underway.

In an a small part of Nvidia's earning call opening remarks, chief financial officer Colette Kress did make mention of supply constraints being "the headwind to gaming in Q1" and beyond, so perhaps the effects of all this data-focussed expansion may be a small issue for Nvidia there.

For the rest of its hardware stack, though, Kress seemed very confident, echoing Huang's statements by saying the company had "strategically secured inventory and capacity to meet demand beyond the next several quarters."

It's alright for some, I guess. Anyone got any spare memory modules going cheap? I know a few million gamers that might be interested.

Nvidia CEO Jensen Huang spoke at the Morgan Stanley Media and Telecom Conference yesterday, and, yes, AI and a celebration of Nvidia's recent successes were very much on the table.

After a somewhat subdued opening ("Wow, no music, no walk on music, no roaring applause?" said Huang, jokingly), the Nvidia head honcho got down to the business of explaining how his company developed into the titan it is today, and its importance to the videogame industry.

"Well, the answer is, as it turns out, we started the company with the idea of creating a new computing platform, a new way of doing computing" said Huang.

"And the type of things that we were extremely good at are algorithms, because the inner loop of the software tends to be about 5% of the code, but 99% of the compute time. And back then, the algorithms in the world of computers was quite rare. And one of the most important algorithms was computer graphics, the simulation of light and how light travels through space."

"And so while computer graphics was used for things like animation movies... it was during that time where computer graphics was becoming more capable, and we could simulate virtual reality with it, and we applied it to creating a new industry, which did not exist at the time called videogames."

"And so 3D graphics was modernized in my time, consumerized in my time", Huang continued. "And the whole videogame industry was created in my time."

Which is... quite the bold claim, I guess. Allowing for hyperbole, it's difficult to underestimate the impact of Nvidia's graphics technology on the games industry as a whole, although I think many will (correctly) argue that videogames have been a thing since... oooh, the 70s at least. Perhaps even the late 40s, depending on who you ask.

And while I suppose you could debate the term "videogame industry", I think it's difficult to argue with the fact that the concept started long before Huang was born, and developed while he was still wearing short trousers.

However, Huang seemed keen to qualify his comments. "And when I say in my time, meaning it was Nvidia that pulled it all together", he opined.

"The reason why we're so beloved in the videogame industry and we're so deep in it still is, in a lot of ways, we created the modern videogame industry.

"From the algorithms associated with it, the libraries. In the computer graphics industry, without RTX, there would be nothing today. Without our contribution of all the algorithms that goes into all of the game engines, you wouldn't be able to enjoy the type of videogames you enjoy today. So Nvidia has been deep in the world of algorithms since day one, 33 years ago."

"Today, if you look at Epic's Unreal Engine, Nvidia's technology is all over it," Huang said. "And you go into every game developer, Nvidia's technology is all over. That's the reason why all the games run best on Nvidia for good reason. That's the reason why Nvidia is the world's largest game platform."

Where to start, where to start. Certainly, Nvidia's graphics technology is deeply rooted inside modern hardware and game development, engines, and the impact of CUDA and various other GPU developments is extremely important to the history of the medium.

Beloved, however, is an interesting term. From a developer standpoint, I would say that choosing not to work with Nvidia at this point would be a massive, critical mistake, as Nvidia graphics cards continue to dominate the Steam Hardware Survey to an astonishing degree. In terms of being beloved by PC gamers overall, though, I think that might be something of a stretch.

From graphics card pricing that continues to bite (although supply chains being what they are, it's a complicated issue), to Multi Frame Generation doubts, and the odd VRAM debate, the relationship between Nvidia and its GPU-purchasing customers hasn't always been a smooth one.

On the flipside, ray tracing and upscaling efforts have changed the way we game considerably, and it was Nvidia that flew the flag for both early on. As for gamer's opinions on the tech, though? They tend to vary.

And while I don't subscribe to the whole team green, team red tribalism between fans of Nvidia graphics cards and AMD equivalents (give me the fastest I can buy for a reasonable price and I'm happy), Huang's words seem like they may stoke the flames of some old grudges and debates.

Nevertheless, Huang seems more than happy to take a victory lap at this point. And sitting as he does at the head of the world's most valuable company, raking in huge amounts of revenue from the AI boom, I suppose that's the privilege that you get. Nvidia's contributions to both gaming and AI proliferation are genuinely world changing, that much is true.

But these days, it's difficult not to feel that, as gamers, we're very much down the priority list. Even if, as Huang points out, the tech inside modern games owes a whole lot to the big green behemoth. And quite a few others, of course. Just wanted to get that in there.

YouTuber mryeester, he of zany tech-tweaking antics fame, is at it again, this time creating an infinite ice-cooled PC setup. It may sound silly, it's probably hideously inefficient. But, by Jove, it actually seems to work.

The basic idea here is to use plain old water ice to cool a CPU. You can test the basic viability of that, as indeed mryeester inevitably has, by simply sticking a metal cup on top of a CPU and chucking in some ice.

In the short run, that is actually a pretty effective way to keep a CPU cool. The problem is that the ice melts pretty fast. And then you're in trouble. So, what you really want is some kind of infinite ice cooling apparatus for your PC.

That starts with a pump to pull the water away as the ice melts. Then you have the problem of topping up the ice. You could do that manually. But where's the fun—and practicality—in that?

No, some kind of ice machine is surely in order. And that's exactly what mryeester has rigged up. Essentially, a somewhat hacked up ice machine feeds a tall plastic collection tube that holds about a foot of ice, which sits atop a metal cup that in turn is placed on an aluminium block that sits on the CPU. Got that?

A water pump connected to a motherboard fan header pulls water from the cup as the ice is melted by the CPU, and pumps it into the ice machine, thereby creating an infinite loop. The machine creates new ice cubes from the water pulled from the cup.

As mryeester says, this isn't exactly the most efficient setup in terms of power consumption. Running the ice machine will significantly up overall system draw. And then there's the noise from the pump and the general precariousness of having all that makeshift kit pumping water and kicking out ice cubes right above the motherboard.

But as he says, "the fact that this works at all is blowing my mind." It appears to be actively cooling the CPU to around 40 degrees Celsius under load, which is none too shabby. Exactly how long this homebrew lashup could reasonably be expected to operate reliably is an open, and maybe redundant, question.

Instead, it's a bit of harmless fun and does actually look like something that wouldn't be all that hard—or expensive—to replicate. Not that we're actually recommending that. Not with all that water and electricity, not to mention to cost of hardware right now. Emulate these shenanigans very much at your own risk.

Nvidia has announced its financial results for the fourth quarter and fiscal year, and they make for some pretty astounding figures. Total revenue for the quarter was reported as $68 billion, up 73% year-over-year, but the real headline news is the annual data center revenue: $193.7 billion.

That's a 68% increase year-over-year, and the sort of money that's very difficult to get your head around. Not that we were expecting much less, given the runaway success of Nvidia's Hopper and Blackwell generation AI hardware and its skyrocketing market cap over the past year, but it's still a pretty astounding result.

And if you were wondering about gaming? It brought in $3.7 billion in Q4, and $16 billion over the full fiscal year—a 41% increase. That's a pretty good result for RTX 50-series sales and the like, but it's not difficult to see why Nvidia is all in on AI right now, and us gamers are perhaps feeling like the second string to team green's AI-crunching efforts.

"We have now scaled our data center business by nearly 13x since the emergence of ChatGPT in [the] fiscal [year] 2023", said Nvidia's executive vice president and chief financial officer, Colette Kress.

"We expect sequential revenue growth throughout calendar 2026, exceeding what was included in the $500 billion Blackwell and Rubin revenue opportunity we shared last year. We believe we have inventory and supply commitments in place to address future demand, including shipments extending into calendar 2027."

Well, it's good to hear someone has sufficient inventory supply commitments right now, as the DRAM supply crisis bites the rest of the hardware market and TSMC looks to be pushed near its limits. Nvidia seems to be challenging the supply chain with its massive demand, and while it hoovers up all the resources it can to fulfil a seemingly insatiable demand for more AI-crunching hardware, it's difficult not to feel like the rest of us are merely caught in its wake.

"Fueled by an annual R&D budget approaching $20,000,000,000 and our ability to extreme codesign across compute and networking across chips, systems, algorithms, and software, we intend to deliver x-factor leaps in performance per watt every generation and extend our leadership position over the long term", Kress continued in the opening remarks.

However, despite these huge figures and an earnings report that seemingly any company would be proud to show off, the effect on Nvidia's share price was surprisingly mild. While shares bounced by four percent in after hours trading following the results, the price soon settled back to a more usual rate.

While Nvidia is still all-in on AI, reports indicate that investors may be becoming wary of the spending of many AI firms, amid further warnings that the supply chain may not be able to facilitate continual AI growth. So, while it might be a red letter day as far as team green is concerned, there are signs that the market is perhaps becoming a little more cautious regarding the financial future of AI as a whole.

The last remnants of Nvidia's once-bold plan to take control of CPU specialist Arm have been defenestrated. According to regulatory filings, Nvidia has dumped its remaining stake in Arm amounting to 1.1 million shares with a value of approximately $140 million.

Nvidia hasn't commented on the move, which took place at the end of last year as per filings with regulators that Nvidia is obliged to make regarding such transactions. So, what are we to make of this?

First, it has no impact on Nvidia's ability to produce and sell CPUs based on Arm IP. That's a function of licensing deals with Arm, not equity stakes or ownership of the company.

Indeed, Nvidia announced a brand new Arm-based CPU recently, known as Vera and using an in-house CPU core customed-designed by Nvidia called Olympus. Nvidia's previous Arm-based CPUs have used bought-in CPU designs.

Of course, Vera is aimed at AI servers, not PCs. However, Nvidia also has a CPU designed for PCs in the works, codenamed N1X. Nvidia CEO Jensen Huang has indicated that N1X is the same or at least closely related to the GB10 "superchip" in the Nvidia DGX Spark AI box.

GB10 uses off-the-shelf Cortex A725 and X925 designed by Arm, reflecting licences Nvidia holds for those designs. But as the Vera chip shows, Nvidia also has a license to design its own CPU cores that leverage Arm's ISA or instruction set. In other words, Nvidia has both types of Arm licenses and its divestment of Arm shares does nothing to change that.

All that said, arguably what's interesting in all this is what it says about Nvidia's view of the future value of Arm the company. Given that Nvidia is now the world's most valuable company and is generating revenues the likes of which have never been seen before, including over $130 billion in 2025, it seems unlikely that it was desperate for the piffling $140 million or thereabouts raised from unloading its Arm shares.

So, maybe Nvidia thinks Arm shares aren't a great investment. But if so, in an admittedly indirect way, that doesn't imply anything hugely positive about Nvidia's plans for its own chips based on Arm IP, does it?

Of course, Nvidia is easily wealthy enough that it could dump Arm shares as a sort of flex. I'm referring to the backstory here where it emerged in 2020 that Nvidia had designs on taking full control of Arm. Typically, a deal of that size takes place in tranches, with Nvidia gradually building up its stake in Arm. Hence the stake in Arm that Nvidia has just sold.

Whatever, that deal was terminated in 2022 following pushback from regulators. So, maybe this recent Arm stock selloff is Nvidia's final indignant flounce. Or maybe it's just some kind of dispassionate bean counting. All we know for sure is that the Arm deal is now completely dead.

Nvidia's regular GTC conference will soon kick off, taking place in San Jose, between March 16 and 19. From its very beginnings in 2008, the event has been all about what GPUs can be used for, other than gaming. And as he is wont to do, CEO Jensen Huang has been talking up what to expect.

In an interview with the Korea Economic Daily, Huang teased, "A chip that will surprise the world will be unveiled at GTC next month." Naturally, he did not specify much more about the chip beyond this, though one has to wonder what it would really take to 'surprise' tech fiends these days. For instance, 'a fresh GPU well within my budget' may sound ridiculous, but a girl can dream.

As for the 'surprising chip' itself, one could speculate that Huang is gesturing at the long-awaited N1X Arm chip for consumer PCs. For one thing, recent reports suggest the N1X could drop as soon as the end of March—so a deep dive right before, at GTC, would make sense.

Alternatively, the wider interview's focus on AI could also be a clue as to the identity of the chip. Huang discusses Nvidia's collaboration with SK hynix, and the latter company's plans for HBM4. It's hoped this latest iteration of super-fast memory can maximize the performance of Nvidia's Vera Rubin chip (Nvidia has also reportedly already placed an order for Samsung's next-gen High Bandwidth Memory, too).

But besides that, Huang also told Korean media, "There is no AI bubble. We are just at the beginning of the largest infrastructure project in human history, worth tens of trillions of dollars."

That alone suggests a continuing strong commitment to the industry—even if Nvidia's $100 billion investment plan in OpenAI has reportedly 'stalled'. In fact, when Korean media specifically asked about future investments in AI companies like the ChatGPT creator or Anthropic, Huang was reportedly evasive; he answered, "AI is not just a model; it’s an entire industry encompassing energy, semiconductors, data centers, the cloud, and the applications built on top of it."

So, while Nvidia is not pulling away from AI, it does sound like the company may be looking to diversify its portfolio. And lest you fret that Nvidia is becoming an AI-only company, there is reportedly an RTX 5090-beating GPU in the works too. Sources say this is much further off than the N1X Arm chip, suggesting a September release.

But then surely it wouldn't be completely ridiculous to expect the unveiling of a fresh GPU at the GPU Technology Conference, right? …Right?

Things might be tough for PC gamers this year, as prices continue to rise on everything from memory modules to graphics cards. One person who doesn't appear to be feeling the pinch just yet, though, is Nvidia CEO Jensen Huang, who hosted a so-called "trillion-dollar dinner" in Taiwan this weekend, supposedly named after the market capitalization of the firms attending.

Huang took the opportunity to speak to the press in the rain outside of a Taipei restaurant on Saturday, where he jokingly appeared to give Taiwanese chip juggernaut TSMC something of a hurry up, according to Reuters.

"TSMC needs to work very hard this year because I need a lot of wafers," said Huang, laughing with the assembled press. "TSMC is doing an incredible job and they're working very, very hard. We have a lot of demand this year."

One of the attendees was TSMC CEO C.C. Wei, who did not answer questions from reporters. While the AI boom continues to run its course, TSMC's position as the key manufacturer at the base of the chip production chain has led to some reports that the limits of its current packaging capacity may be a bottleneck, as demand for AI hardware continues to be strong.

Still, TSMC executives have recently signalled that spending on its expansion will rise even further, beyond its current $165 billion investment in US chip manufacturing facilities, and there are reports of plans for four new advanced integrated circuit packaging plants in Taiwan.

"Over the next 10 years, TSMC will likely increase their capacity by much more than 100%, and so this is a very substantial scale-up in the next decade," said Jensen.

As for the ongoing RAMpocalypse, in which AI servers (many of which are powered by Nvidia's high-end AI GPUs) have been swallowing up DRAM modules, resulting in a shortage for the rest of us, Huang had this to say:

"We need a lot of memory this year… I think that the entire supply chain is challenging this year because demand is so much more."

So, no signs of a let up there, then. Certainly, Huang has a lot to be happy about in 2026, as the demand for his company's hardware shows no sign of slowing. Reports also indicate that several Chinese AI companies have received conditional approval to buy Nvidia's H200 AI GPUs for training purposes, including China's top AI startup, DeepSeek—which, if true, may signal the end of a continual thorn in Nvidia's side over the past few years.

As for those of us looking to buy a graphics card or upgrade our RAM for a reasonable sum in the near future, 2026 isn't looking quite so rosy.

While TSMC's expansion may eventually lead to more capacity for key components in our beloved gaming hardware, it's clear that Nvidia's bread is being buttered by AI demand these days, and I doubt regular consumer hardware is going to be much of a priority while the going's so good. On the plus side… well, the key tech industry players seem to have had a lovely night out. How the other half live, ey?

According to Reuters, two people "familiar with the matter" have said that the Chinese government has given approval for its top AI startup, DeepSeek, to buy Nvidia's H200 AI GPUs, with regulatory conditions that are still being finalised.

If these reports are true, it would mark a significant shift in China's previous reluctance to allow Nvidia's high-end hardware to be purchased by its top tech firms, and potentially mark the beginning of the end of a long-running saga between Nvidia and the US and Chinese authorities.

However, a Bloomberg report published yesterday quotes Nvidia CEO Jensen Huang as saying, "I’m hoping that the Chinese government would allow Nvidia to sell the H200... it's up to the Chinese government now but they are still deciding, and we are waiting patiently."

Huang's comments were given to reporters in Taipei on Thursday, prior to the Reuters report, so it's possible that the decision has been made internally since then. Or, as Reuters ' sources claim the regulatory conditions are "still being finalised", it's possible the Nvidia CEO is reluctant to confirm the arrangement as of yet.

DeepSeek made headlines last year after its newly-released open-source AI models looked to be comparable in performance and accuracy to OpenAI's efforts, leading some to call it "AI's Sputnik moment".

Given that these models were likely developed and trained on Chinese AI hardware, which is believed to be far less powerful than even Nvidia's last-generation AI GPUs, granting DeepSeek the right to buy H200 chips would likely give the AI startup a significant boost.

It's also been reported that ByteDance, Alibaba, and Tencent have been given permission to purchase more than 400,000 H200 chips in total, with other firms joining a queue for approval.

While the previous US administration implemented comprehensive restrictions on the export of Nvidia's high-end hardware to prevent China from gaining ground in the AI race (and among concerns they would be used for military technology), Nvidia's CEO has been openly critical of the policy:

"Depriving someone of technology is not a goal, it's a tactic. And that tactic was not in service of the goal", said Huang in an interview last year.

"Our mission, properly expressed... in order for America to have AI leadership", Huang continued, "is 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 [the] American tech stack."

The current Trump administration has since approved the export of Nvidia's H200 chips to China. And while the Chinese government has since blocked shipments of H200 GPUs from entering the country, after a previous ban on its new state-funded data centres from using US AI hardware, it looks like those restrictions may soon be loosening for key companies, including DeepSeek.

In which case, if these reports are correct, both the Chinese and US governments now seem to be reaching something of an accord over Nvidia's prized hardware. For DeepSeek, this would potentially mean a bounty of new AI chips to train its new models with—the effects of which on the US-led AI market remains to be seen.

Jensen Huang has well and truly escaped gaming obscurity these days. The Nvidia CEO just took the stage at the World Economic Forum to talk about AI demand, bubbles, and the impact that artificial intelligence has on the job market now and into the future. Of course, being the man in charge of shipping billions of dollars of AI chips, he has a particularly positive take on the lot.

Chatting to Larry Fink, CEO of Blackrock, who called Nvidia 'nuh-vidia' throughout the conversation, Huang had a few things to say about his booming business.

"One good test on the AI bubble is to recognize that Nvidia now has now millions of Nvidia GPUs in the cloud. We're in every cloud. You know. We're used everywhere.

"And if you try to rent an Nvidia GPU these days, it's so incredibly hard, and the spot price of GPU rentals is going up, not just the latest generation, but two generation old GPUs. The spot price of rentals are going up, and the reason for that is because the number of AI companies that are being created, the number of companies shifting their R&D budget."

Nvidia's datacentre business, the topic of conversation here, has soared to many times its gaming revenue in recent years. It hit a record $51.2 billion through August to September last year. Gaming revenue during the same period was $4.3 billion. Though the demand for datacentre GPUs, such as upcoming Rubin chips, B100/200, and older chips like the H100/H200, do have a knock-on effect in gaming GPUs.

Just look to the price of the RTX 5090—a more than capable card for smaller-scale AI deployment—which launched at $1,999 and is now selling for around $4,000+.

Capacity for production is one factor in all of this, as when AI comes knocking for chips, be those GPUs or memory, there's only so much readily available at any one time. That's why we're seeing RAM prices skyrocket: AI demand outstrips supply and datacenter buildout is more valuable than availability for consumers.

In Huang's words, the fervour to buy more AI chips is "the largest infrastructure build out in human history."

"That's going to create a lot of jobs," he says, citing skilled labor requirements for building out massive datacenters and increasing energy output to meet their demands.

The impact of AI on the job market was one of the main topics of discussion through the talk. Huang, in no uncertain terms, suggested that AI will create a labour shortage, rather than take jobs from humans. He suggests one way to understand his way of thinking is to look beyond the tasks required to do a job and instead determining the purpose of a job.

"Now, the easiest way to think about whether what is the impact of AI on a particular job is to understand what is the purpose of the job and what is the task of the job," Huang says.

"If you just put a camera on the two of us and just watched us, you would probably think the two of us are typists, because I spend all of my time typing and and so if AI could automate so much word prediction and help us type, then we would be out of jobs. But obviously that's not our purpose. And so the question is, what is the purpose of your job? In the case of radiologists and nurses, it's to care for people, and that purpose is enhanced and made more productive because the task has been automated."

I do think there are instances where this is not the case. When AI is entirely replacing the purpose of someone's job—or intrinsically changing it or shifting it further away—such as generative AI and artists or musicians, or closer to home, when AI tools are used to summarise news stories. When the AI is not owned or run by those professions affected by its use, it's not as often beneficial. Jobs may be created in some sectors, but similarly, jobs may move from other sectors entirely as it permeates into the wider market.

Though Huang aims to keep things positive about AI, as you would expect from a CEO in his position signing off with a request for people to "get involved". And if anything is clear from this talk, according to these two, it wouldn't appear there's signs of slowing for the rapid buildout of AI. If anything, they suggest the large-scale investment in AI is only just beginning.

Did you watch every CES presentation this year? If you didn't, don't worry, you didn't miss much. We tend to keep a close eye on Nvidia and AMD for any news about upcoming products, but this year, it was all about AI. I've run the numbers, with a little help from AI-powered transcription, and the mentions of AI are rather staggering.

If you thought Nvidia was emperor of AI, think again. The company's presentation was primarily focused on AI and robotics, but it logged a mere 120 mentions of AI during its 91 minute runtime. That's only 1.3 mentions of AI per minute (AI/min).

AMD's CES keynote, led by Dr. Lisa Su, hit a staggering 210 mentions of AI. That was over a longer runtime of 117 minutes, though it works out to a much higher 1.8 AI/min. Su really wanted to drive that point home, huh?

Now, bear in mind that some Ryzen products have AI in the name. Ryzen AI Max, for example, though only 13 mentions of AI in AMD's show were preceded by the word 'Ryzen'.

If you're wondering what percentage of the words spoken were 'AI', and of course you were, here you are:

• 1.2% of all words spoken during AMD's show were 'AI'
• 0.95% of all words spoken during Nvidia's show were 'AI'

Though neither company could match Lenovo. Our Andy sat in on Lenovo's event in the Las Vegas Sphere and had some opinions on that experience, and justifiably so looking at these numbers. Lenovo managed 219 mentions of AI in a 114 minute runtime. That's 1.9 AI/min.

As for gaming, AMD and Lenovo mentioned that specific term just three times throughout their respective shows. So we see where the money is coming from these days.

That said, AMD still earns nearly as much from client and gaming sales as it does from data centre revenue, at a little over $4 billion a piece. Nvidia is much more focused on data centre sales—only $4.3 billion of its $57 billion revenue near the end of last year was from gaming. That might explain why Nvidia had zero mentions of the word 'gaming' in its CES presentation—though it posted a separate pre-recorded presentation specifically on gaming announcements.

None of this is surprising. AMD, Nvidia, and most of the tech world are at a fever pitch for artificial intelligence right now. While I, nor Dell, see the same sort of fervour for AI products in terms of consumer spending, I did just use AI to transcribe all of these very long presentations in 20 minutes. So, any complaints with the methodology or results, send those to the big AI firms. Cheers.

Perhaps to the surprise of no one, Nvidia's time at CES 2026 was all about one thing: AI. That said, PC gaming wasn't entirely ignored, as DLSS 4.5 was ninja-launched with the promise of '4K 240 Hz path traced gaming'. However, DLSS is still AI-based and in a Q&A session with members of the press, CEO Jensen Huang made it clear that artificial intelligence isn't just for improving performance, it's how graphics needs to be done in the future.

This much we already know, as Nvidia banged its neural rendering drum starting at last year's CES and then throughout 2025, and it wasn't the only graphics company to do so. Microsoft announced the addition of cooperative vectors to Direct3D, which is pretty much required to implement neural rendering in games, and AMD's FSR Redstone is as AI-based as anything from Intel and Nvidia.

So, when PC World's Adam Patrick Murray asked Huang, "Is the RTX 5090 the fastest GPU that gamers will ever see in traditional rasterization? And what does an AI gaming GPU look like in the future?", it wasn't surprising that Nvidia's co-founder avoided the first question entirely and skipped straight to the topic of AI.

"I think that the answer is hard to predict. Maybe another way of saying it is that the future is neural rendering. It is basically DLSS. That’s the way graphics ought to be."

He then expanded with some examples of what he meant by this: "I would expect that the ability for us to generate imagery of almost any style from photo realism, extreme photo realism, basically a photograph interacting with you at 500 frames a second, all the way to cartoon shading, if you like."

The keyword here is generate. If one wishes to be pedantic, all graphics are generated, either through rasterization or neural networks. It's all just a massive heap of mathematics, broken down into logic operations on GPUs, crunching through endless streams of binary values. But there is one important difference with neural rendering, and it's that it requires far less input data to generate the same graphical output as rasterization.

Fire up the original Crysis from 2007, and all those beautiful visuals are generated from lists of vertices, piles of texture maps, and a veritable mountain of resources that are created during the process of rendering (e.g. depth buffers, G-buffers, render targets, and so on). That's still the case almost 20 years on, and the size and quantity of those resources are now truly massive.

As DLSS Super Resolution proves, though, they don't need to be in the era of AI graphics. Nvidia's upscaling system works by reducing the frame resolution for rendering, scaling it back up once finished, and then applying a neural network to the frame to clean up artefacts. One idea behind neural rendering is take that a step further and to use lower resolution assets in the first place, and generate higher quality stuff as and when required.

Does it ultimately matter how a game's graphics are produced as long as they look absolutely fine and run smoothly? I dare say most people will say 'no', but we don't have any games right now that use neural rendering for any part of the graphics pipeline, other than upscaling and/or frame generation. Everything else is still rasterization (even if ray tracing is used, raster is still there behind the scenes).

That means GeForce GPUs of the future, both near and far, will still need to progress in rasterization to ensure games of tomorrow look and run as intended. But with Nvidia being dead set on neural rendering (I don't think Huang said "That’s the way graphics ought to be" lightly), have RTX graphics cards reached a plateau in that respect?

Does the company now expect that all generational performance increments will come from better DLSS? Will GPUs of the future be nothing more than ASICs for AI? How would such chips process older graphics routines? Is PC gaming heading backwards in time to the era when you needed a new GPU for every major new game, because previous chips didn't support the tech inside?

Answers that generate more questions than they resolve certainly aren't a bad thing, but in this case, I wish Nvidia would give us a much clearer picture as to its roadmap for gaming GPUs and how it plans to support games of the past, present, and future.

It's been over 32 years since Jensen Huang, Chris Malachowsky, and Curtis Priem started a new company together. It even took them a while to come up with a name, but they eventually settled on Nvidia. Yes, that little, independent, underdog company. The one worth $5 trillion back in October. That level of fortune gives one plenty of opportunities to spend hours reminiscing about the past, present, and future, which is precisely what Jensen Huang and Joe Rogan recently did.

Specifically, for almost two and a half hours, Huang chatted on the Joe Rogan Experience about all things AI, GPU, CUDA, consciousness, and what have you. There's an awful lot to delve into, but I was particularly drawn to the section where Rogan remarks on Nvidia's massive AI growth and capabilities: "How funny would it be that it [AI] is birthed out of the desire for computer graphics for video games? It's kind of crazy when you think about it that way."

This prompted Jensen to start going over Nvidia's beginning, when it was a tiny group of engineers in 1993: "We were trying to create this new computing approach. The question is, what's the killer app? We wanted to create a new type of computing architecture, a new type of computer that can solve problems that normal computers can't solve."

A noble goal, one might say. However, Huang hits the issue with this idea right on the head. "Well, the applications that existed in the industry in 1993 are applications that normal computers can solve, because if the normal computers can't solve them, why would the application exist?

"And so we had a mission statement for a company that has no chance of success, but I didn't know that in 1993; it just sounded like a good idea, right?"

If you're not familiar with Nvidia's early history, the application it eventually settled upon was 3D graphics rendering. More importantly, the kind of rendering that Sega was doing with its arcade units, e.g. Virtua Fighter. I thoroughly recommend that you grab a copy of The Nvidia Way: Jensen Huang and the making of a tech giant, by Tae Kim, as it's richly detailed and goes into great depth about how Nvidia did more than just gain inspiration from Sega.

Here's a key snippet: "Amid the business of the trade show, the Nvidia team managed to secure an introduction to representatives from the Japanese video-game and console maker Sega. Impressed with the NV1 demonstration, Sega agreed to begin working with Nvidia as it planned its next console. On December 11, 1994, Jensen and Curtis Priem flew to Tokyo to suggest a chip-development deal to Sega management."

Huang explains further in the podcast: "$5 million was a mountain of money to Sega at the time, and so I told him [Sega's CEO] that if you invested that $5 million in us, it is most likely to be lost, but if you didn't invest that money, we'd be out of business, and we would have no chance.

"So what he decided was, Jensen was a young man he liked, that's it."

The NV1 was Nvidia's first-ever 3D acceleration processor, and in the Joe Rogan podcast, Huang explains that it was very nearly the only processor that Nvidia would design: "We lucked into the Sega partnership. We started taking off, started building our game console, and about a couple [of] years into it, we discovered our first technology didn't work.

"The architecture concepts were sound, but the way we were doing computer graphics was exactly backwards. The inverse texture mapping. We were doing forward texture mapping instead of triangles. We did curve[d] surfaces. So other people did it flat.

"Other technology, the technology that ultimately won, the technology we use today has Z buffers. It automatically sorted. We had an architecture with no Z buffers, the application had to sort it. So we chose a bunch of technology approaches, three major technology choices. All three choices were wrong."

Sega's console, the Dreamcast, never used the NV1. Instead, the company went with UK-based VideoLogic (now called Imagination Technologies) and its PowerVR graphics architecture. It looked like Nvidia was done for, especially as Sega told it that it wouldn't be using the proposed NV2 for its next console.

Tae Kim explains how Nvidia cleverly got its way out of the situation: "Jensen had deftly worked into the initial contract a clause for a $1 million payment from Sega if Nvidia was able to produce a working prototype of a chip that could be installed onto a self-contained motherboard that was about the same size as the older Sega Genesis/Mega Drive motherboard.

"After about a year spent on the project, [Nvidia] was able to get an NV2 prototype working within Sega’s specifications. The milestone triggered the $1 million payout, money that was a key lifeline during a time of crisis."

And key it was, because the payout (and a massive reduction in staff) generated enough funds to research and develop the NV3, also known as the Riva 128. That graphics chip was fast, capable, and although initial drivers were a bit iffy (what drivers weren't in 1997?), sales of the processor were good enough to secure Nvidia's future.

"We bet the farm on video games," said Huang to Rogan. "We narrowly focused our problem statement so I could reject all of the other complexities, and we shrunk it down into this one little focus, and then we supercharged it for gamers." Given that Nvidia now controls 92% of the discrete GPU market, that's a bet that paid off by any measure you can think of.

Of course, Nvidia is all about AI these days, which is what the bulk of the JRE podcast is really about. But I like going back to the 1990s in my thoughts, remembering those first graphics cards I bought: Rage Pro, Riva TNT, Voodoo. Ah, good times.

There's a good chance you know AI as that thing your grandpa uses to get information wrong, and also that thing that has caused the value of Nvidia to skyrocket. As OpenAI, Meta, and even the US government continue their investment in the technology, fears have sprung up that the bubble will burst and all that infrastructure will come down alongside it. But Arvind Krishna, the CEO of the huge technology company IBM, thinks Nvidia's Jensen Huang has the ability to shift the company if and when the time comes.

Talking to The Verge, and responding to the claim that Nvidia could be disincentivised to actually put out new products due to its leading role in supplying AI hardware, Krishna says:

"I think that when you have an incredibly valuable company that’s making its profit stream from a few products, there’s always an inherent or organic disincentive to try to modify that. That said, I would never bet against Jensen [Huang]‘s ability to disrupt himself and go towards the next plateau, if there is one."

Huang founded Nvidia in 1993, and it's been responsible for some of the best graphics cards for decades now, but the last few years represent unprecedented growth for the company. Nvidia, at the end of October this year, became the first ever $5 trillion company and the price per share has risen from $3-4 in 2019 to just shy of $180 as of the time of writing.

This is mostly because of the rapid growth of AI and the fact that Jensen Huang has been banging on about it since before it was cool, or at least, worthy of massive investment.

Nvidia is deeply embedded in AI infrastructure now, with its hardware being supplied to the largest data centres and AI companies. Its AI chip, the H100, is already incredibly popular and in demand, so there's a lot of cash in the current hardware, which new hardware could disrupt.

Though Nvidia recently reported revenues of $57 billion, with 'off the charts' AI GPU sales, it's not the only company with a lot of money in AI. OpenAI, in October, signed a mega deal with Broadcom for custom AI chips, and a market analyst recently suggested the AI bubble is 17x bigger than the dotcom bubble. Michael Burry, the man known for betting against the housing market in 2008, has also recently placed a billion-dollar bet against Nvidia and AI specialist Palantir.

Krishna, when asked if he believes we're in an AI bubble, says, "No. Do I believe that there will be some displacement and some of the capital being spent, especially the debt capital, will not get its payback? Yes."

Krishna instead likens it to the rise of fibre optics in the year 2000. He argues that the world is moving towards AI, and for every 10 companies competing in that gold rush, "maybe two or three of them will be the eventual winners." As far as large language models are concerned, Meta, OpenAI, Anthropic, Google, Amazon, and even IBM all have their own models.

One thing is made clear here: all those companies may be fighting for a share of the LLM pie, but Nvidia could be positioned to hand out the plates.

TSMC is a huge player in the tech industry. Being the world's largest producer of semiconductors, it has clients from Apple to Qualcomm, all the way to Nvidia and AMD. Nvidia CEO Jensen Huang, fresh off the company being valued at $5 trillion, recently went out to Hsinchu County in northwestern Taiwan to acknowledge TSMC's role in Nvidia's success.

"Without TSMC, there is no Nvidia today", the Nvidia chief said at TSMC's Sports Day last week (via Focus Taiwan). This is certainly true. You see TSMC chips in everything from the latest Blackwell GPUs (like the RTX 5090 and RTX 5080) to the AI chips that have helped prop up Nvidia's worth.

Huang told the crowd, "You are really the pride of Taiwan, you are also the pride of the world, and you know that you are also my pride". Huang was born in Taiwan and has Taiwanese citizenship, which might give extra reason for that last part.

TSMC is in a unique spot for Taiwan, being one of the biggest companies in the country. The looming threat of tariffs has caused some worries around supply, but it has a fab in Arizona, with more expected to come, and a $100 billion investment was made in the US earlier this year.

This is to say, TSMC is instrumental to more than just Nvidia. It has a history of getting to the smallest and most efficient process nodes earlier than anyone else. Blackwell is based on a custom 4 nm process, and the latest Apple chips use a 3 nm process.

Effectively, the smaller the process, the higher the density of transistors, and therefore, the greater the levels of efficiency (in terms of die area). TSMC fabs in America are expected to get the 3 nm process by 2027, which should be in time for the RTX 60 series, but Taiwan wants to restrict TSMC from allowing the latest node process in fabs outside of the country, so it won't be matching the tech made at home.

Huang also told the TSMC crowd, "I want to thank you for helping me build Nvidia", and this could be part of a process to strengthen bonds with the manufacturer. As we've seen from the effect of the memory shortage, companies producing valuable tech will go to trusted partners before anyone else.

Nvidia, being a company worth a lot of money and with its fingers in many virtual pies, will want to make sure ties to TSMC remain as strong as possible. And attending a sports day to point out the very real fact that TSMC is part of Nvidia's success seems like just an average weekend for Team Green.

A bipartisan bill might just offer a step in the right direction for workers' rights in the age of AI, calling for further investigation "regarding artificial intelligence-related job impacts" (via The Verge). The "AI-Related Job Impacts Clarity Act" will require both publicly-traded firms and government organisations to report to the Department of Labor how many staff they fired due to AI automation. The act will also require companies to keep tabs on how many people they hire or retrain due to AI integration.

Anxiety about what AI means for the workforce is widespread. For instance, last month, the American Federation of Labor and Congress of Industrial Organizations, which represents 15 million workers and 63 unions, produced a report calling for a “worker-centered technological future."

The most recent bill was introduced by Democratic Senator Mark Warner and Republican Senator Josh Hawley. Senator Warner said, "Good policy starts with good data. This bipartisan legislation will finally give us a clear picture of AI’s impact on the workforce — what jobs are being eliminated, which workers are being retrained, and where new opportunities are emerging."

OpenAI CEO Sam Altman has previously said that he expects jobs in a number of areas, such as customer support, to one day be "totally, totally gone" because of AI. Meanwhile, Nvidia CEO Jensen Huang insists that "The skilled craft segment of every economy is going to boom." He also told Channel 4 News, "If you're an electrician, if you're a plumber, if you're a carpenter, we're going to need hundreds of thousands of them. To build all of these factories."

As unintentionally bleak as some of this sounds, we shouldn't have to rely on hearsay from tech CEOs; the data collected via this latest US government act should present a more definitive picture in an upcoming report. But that said, it does feel increasingly impossible to escape the long shadow of AI, no matter who you are.

For instance, while Amazon Web Services CEO Matt Garman said back in August that replacing entry-level jobs with AI 'the dumbest thing [he'd] ever heard,' more recent organisational changes have seen the wider company lay off 14,000 corporate roles. This feels especially stark, as many major AI players have become increasingly reliant on the server power of AWS—just this week, OpenAI and Amazon struck a $38 billion deal.

With such eye-watering amounts of money being thrown around in the name of compute power, it's hard not to feel like human workers are being left out in the cold. But who knows—maybe this latest act demonstrates a recommitment to workers' rights at some level within the US government, and maybe, just maybe, they can be brought in from the cold.

Hey, remember that time a onesie wearing robot gave Nvidia CEO Jensen Huang a leather jacket? No? I'll remind you—the robot in question was the Neo Gamma, a humanoid bot built by 1X Technologies for helping out around the home. Now, you can pre-order the Gamma's successor, simply called 'Neo'…for $20,000.

CEO and founder of 1X Tech Bernt Bornich announced the launch of pre-orders via X on Tuesday, but the price is far from the only thing giving me pause. Slated for a 2026 release, the Neo is pitched as a humanoid robot that will be able to take care of household chores autonomously. However, it looks like the Gamma could only just about put a glass into a dishwasher, so what strides has the Neo made since?

Well, it turns out this robot has much to learn; Engadget reports that the Neo will lean heavily on tele-operation at least to begin with. In other words, you're not just welcoming Neo into your home, but potentially the 1X Tech employee piloting it remotely too.

The hope is that the real world experience that comes from tele-operation in early adopters' homes can be leveraged as AI training data (so yes, you'd also be welcoming a camera into your home too). When The Wall Street Journal spent the day with 1X's humanoid robot, Bernt Bornich clarified, "I think it's quite important for me to just say that, in 2026, if you buy this product, it is because you're okay with that social contract. If we don't have your data, we can't make the product better."

Early adopters will be able to schedule tele-operating sessions via an app, as well as set robo-no-go zones throughout their home that the Neo will be blocked from entering at a software level. Furthermore, the company can blur out residents' so the remote Neo operator cannot see them, and teleoperators can't take control of Neo without the owner's approval.

Bornich makes the company's case to The Wall Street journal, elaborating "I'm a big fan of what I call, like, big brother, big sister principle, right? Big sister helps you. Big brother is just there to kinda monitor you. And we are very much the big sister. Depending on how much you want to trade, we can be more useful. And you decide where on the scale you want to be."

Personally, I think there's more than just a simple branding issue at play here. Besides the obvious privacy concerns, I'm also left wondering, if someone can afford to drop $20,000 on a product that is not necessarily feature complete, why wouldn't they then just…pay another human a living wage to clean their house?

Perhaps that's naive of me—but, having seen the tele-operated Neo visibly struggle to close a dishwasher, surely hiring another actually skilled human is better value for money? Simply put, I don't think Neo is the future of household labour—either in how it gets done or how we value it.

Bornich ultimately attempts to reassure interested customers, "When you get your Neo in 2026, it will do most of the things in your home autonomously. The quality of that work will vary, and will improve drastically quite fast as we get data."

Again, there's that big tech insistence that if we just feed the AI enough data, we'll end up in that robo-maid, flying car future. I'm doubtful to say the least, especially when the cost of admittance is 'please welcome our cameras into your home'. Sure, 1X Tech will blur the faces but I'd argue my household mess remains pretty identifying.

As I type these very words, Nvidia's market capitalisation is ticking along at $5.12 trillion. Yup, Nvidia has become the world's first $5 trillion company. Truly, these numbers are getting silly.

Of course, it really, really (really!) wasn't all that long ago we reported on Nvidia becoming the world's most valuable company at $3.3 trillion. It was only a few months ago that Nvidia breached $4 trillion.

But now here we are at $5 trillion. Where does it all end? Increasingly, market observers think the whole AI thing is a bubble set to catastrophically burst. Or maybe AI is the real deal, and an apocalypse of a very different kind will be upon us soon enough.

But one thing is for sure. Whatever the outcome, there's no doubting Nvidia will have been absolutely pivotal. It dominates the AI industry when it comes to both hardware and the software development platforms on which it is all built.

But as I watched CEO Jensen Huang's keynote address at the GTC event yesterday, his narrative around Nvidia was just a little too neat, a bit too cute. If you take Huang at his implied word, Nvidia saw it all coming. Personally, I think a fair bit of luck was involved.

At GTC, Huang pointed out that Dennard scaling broke down about 10 years ago. Dennard scaling is something of a sibling observation to Moore's Law. While the latter makes predictions or at least observations about transistor densities and costs in computer chips, Dennard scaling is concerned with power consumption and operating frequency.

Nvidia's trend data rightly shows chip frequencies have largely stalled, while power efficiency is only improving gradually, too. At the same time, transistor densities have mostly continued to scale. So, a computing paradigm that takes advantage of Moore's Law but can mitigate the end of Dennard scaling is required. Huang says Nvidia saw all this coming and worked out that parallelised or "accelerated" computing was the solution.

"We made this observation a long time ago, and for 30 years we've been advancing this form of computing, we call it accelerated computing. We invented the GPU, we invented a programming model called CUDA, and we observed that if we could add a processor that takes advantage of more and more and more transistors, applied parallel computing, add that to a sequential processing CPU that we could extend the capabilities of computing well beyond, and that moment has really come," he says.

He's clearly right that the moment for parallelised or "accelerated" computing has come. I'm just not so sure Nvidia and Huang were quite so prescient as he makes out.

Who am I to question to technical and financial acumen of the CEO of the world's most valuable company? Nobody, obviously, but I have been following Nvidia in a professional capacity for over 20 years, and I can certainly take a clear view on the messages Nvidia has been putting out over that period.

My impression, for what it is worth, is that Nvidia was all about graphics in the early days. It wasn't building graphics chips with a view to parallelising everything. Instead, after building graphics chips, the company's ambitions to make more money drove it to think about what alternative applications might just be convinced to run on what it cleverly marketed as "GPUs", leveraging awareness around the existing term "CPU" as applied to Computer processors.

I can remember years of Nvidia throwing just about anything against the wall, hoping it would stick. 2D video processing, physics simulations, protein folding, mineral prospecting—they tried the lot in those early years.

Notably, it wasn't until around 2012 when Nvidia began to even namecheck "AI" as an application for its GPUs, and even then it was merely one of a long list of candidate applications for Nvidia GPUs that fell into the broader category of "GPGPU" or general purpose GPU computing.

I'd argue any claim, implied or otherwise, that Nvidia and Huang saw the AI revolution as it is today coming—transformer models running on GPUs—doesn't hold up to scrutiny. Nor does it bear cross-referencing with what Nvidia was saying or doing until much more recently.

That isn't to say that Nvidia doesn't deserve its success. No other company bet as big on GPUs as Nvidia did. No other company put nearly as much effort into creating the supporting software frame, in CUDA, as Nvidia did.

But AI in general blowing up in the way it has over the last few years and transformer models, in particular, both turning out to be so effective for creating AI models and being so well suited to run on GPUs, isn't something that Nvidia predicted. At least, if it did, Nvidia kept that entirely secret while spending large amounts of money trying to get companies to use its GPUs for lots of tasks and workloads other than AI.

So, props certainly go to Nvidia for its incredible success. But I don't think it follows that the company necessarily has any great insight into the future. And if that realisation is true, it surely has implications for everything from the stock market to the future of AI.

Nvidia streamed the keynote speech of its latest GPU Technology Conference yesterday—though unfortunately thousands of folks seem to have fallen for a deepfake Jensen Huang extolling the virtues of cryptocurrency instead. Just when you thought the dodgy reuploaders and react channels were bad enough, it turns out you've now got to worry about fully counterfeit event streams too.

For those that missed it, the official Nvidia GTC, originally streamed live from Washington, D.C. on October 28, can be viewed here. Though it's sitting pretty at nearly 200,000 views now, that wasn't the case during the stream; while about 20,000 tuned in for the official event as it went live, nearly 100,000 viewers were said to be watching the deepfake feed broadcast (hosted by a channel calling itself Nvidia Live) at the same time (via Tomshardware).

The counterfeit stream has since been removed, but CRN editor Dylan Martin posted to X about the debacle as it happened, observing that at its peak, the official upload had only about a fifth of the viewership of the deepfake feed. The deepfaked Huang claimed to postpone the main event in favour of promoting "a crypto mass adoption event that ties directly into Nvidia's mission to accelerate human progress."

The AI-generated Huang also encouraged viewers to scan an on-screen QR code, and send in supported cryptocurrencies. It's not yet clear how many (if any) viewers may have scanned this QR code or lost money while believing this fake stream to be legitimate.

This turn of events is in many ways unsurprising. Just earlier this month, OpenAI CEO Sam Altman volunteered his own likeness into the maw of AI video generator Sora 2, with perhaps predictable results. As for Huang, this is the fourth GTC keynote he's hosted this year alone, likely adding to the wealth of easily accessible video footage for bad actors to use as AI training data. Please excuse me while I go to pick out a cute, brown paper bag to wear on my head for forever more.

As Nvidia already secured a $4 trillion valuation earlier this year, (and is now fast approaching the $5 trillion mark), in no small part thanks to the many moves it's made around AI, there's an irony that isn't lost on me. It's also worth noting that, even as the money going into AI-based investments threatens to outstrip the money coming out, Huang recently downplayed concerns about a bubble.

Nvidia NIM is already being leveraged in deepfake image detection models like Hive's, but I wouldn't be surprised if Nvidia itself made a move similar to Meta, and released more deepfake detection tools in the near future. Failing that, it seems we all need to keep our eyes peeled, as our online reality threatens to come apart at the seams.

Reports earlier this week suggested that the Trump administration was planning to deploy a wave of federal agents on the streets of San Francisco as part of a large-scale immigration-enforcement plan. The news was met with widespread condemnation and plans to protest from the local community.

Trump has since posted on his social media platform, Truth Social, confirming that a planned 'surge' this weekend would no longer go ahead after conversations with San Francisco's mayor, and others—including Nvidia CEO, Jensen Huang (via The San Francisco Standard).

"The Federal Government was preparing to 'surge' San Francisco, California, on Saturday, but friends of mine who live in the area called last night to ask me not to go forward with the surge in that the Mayor, Daniel Lurie, was making substantial progress," says Trump.

"Great people like Jensen Huang, Marc Benioff, and others have called saying that the future of San Francisco is great," he continued. "They want to give it a 'shot.' Therefore, we will not surge San Francisco on Saturday. Stay tuned!"

Huang owns a substantial piece of property in the San Francisco area, while Nvidia also looks to be in the process of acquiring more office space in the city over the next few months.

The Nvidia chief also appears to have a genuine fondness for the city, describing it as "thriving" earlier this year in regards to the apparent resurgence of its tech scene.

The Jen-Hsun and Lori Huang Foundation, a philanthropic organisation co-founded and run by Huang and his wife, has also made significant donations in the area—and now it appears that Huang has used his relationship with the president to step in on San Francisco's behalf.

Huang's relationship with Trump seems to be a strong one, with the US president calling him a "great guy" earlier this year at the AI summit in Washington DC. And, it must be said, Huang appears to be using that relationship to great effect.

While Nvidia's efforts to establish its presence in the Chinese AI GPU market have yet to bear fruit amid ongoing tensions between the Trump administration and Beijing, it seems that his influence over the president still holds a substantial amount of weight. As a result, it looks like Trump's plans to 'surge' the San Franciscan streets are on hold—for now, at the very least.

Nvidia CEO Jensen Huang spoke at the Citadel Securities Future of Global Markets 2025 conference last week, and would you believe it, most of the conversation centred around AI. However, the NV head honcho also had some comments to make on China's role within AI development, and Nvidia's efforts to sell its AI hardware within the country—along with some commentary on US trade policy between the two.

"It's important to be mindful that what harms China could oftentimes also harm America, and even worse," said Huang (via Wccftech). "And so before we leap towards policies that are hurtful to other people, take a step back and maybe reflect on what are the policies that are helpful to America."

"China has about 50% of the world's AI researchers, incredible schools, incredible focus in AI, lots of passion around AI. And I think it's a mistake to not have those researchers build AI on American technology," he continued.

"We are 100% out of China… we went from 95% market share to 0%, and so I can't imagine any policy maker thinking that's a good idea, that whatever policy we implemented caused America to lose one of the largest markets in the world."

Certainly, Nvidia looks to have found itself at the centre of trade frictions between the two countries. While pre-existing US AI chip export bans to China appeared to be loosening earlier this year, in the form of Nvidia's US government-approved licenses to sell its H20 AI GPUs in the country, progress has since appeared to stall, as the two countries engage in a protracted trade dispute.

Nvidia's CFO recently described the stalled progress as "a little geopolitical situation between the two governments", but little or not, it still appears that Nvidia remains in AI chip limbo in regards to the Chinese market.

For China's part, production was also reportedly paused on H20 GPUs as a result of security concerns from the Chinese authorities halting their sale, and potential buyers were left waiting to purchase chips that have yet to make it past the restrictions. Huang has also previously expressed his disappointment at the news that China's internet regulator had banned some of the country's largest tech firms from buying the China-specific RTX Pro 6000D.

And all the while Nvidia watches as the two geopolitical giants battle it out, its Chinese competitors, like Huawei, look to be making great progress in its absence.

Last week, Trump announced a new 100% tariff on Chinese goods in relation to a rare earth metal dispute, alongside new export controls on "any and all critical software", which suggests that trade friction between the two superpowers isn't likely to calm any time soon. While AI hardware has slipped from the headlines in the recent disputes, it's never far from the frame—and Nvidia's AI chips still remain unobtainable by legitimate means on Chinese shores.

In short, the ongoing trade disputes between the US and China have been a real headache for Nvidia, and while Huang and the Trump administration appear to be on good terms, even the considerable weight of the most valuable company in the world doesn't appear to have made much of a dent on current US or Chinese government policy.

It looks like Nvidia will just have to wait to see how things play out— because as relations between the two countries currently stand, the company's Chinese market aspirations appear to be well outside of its control.

Nvidia has finally started shipping its first DGX Spark mini 'supercomputers' and Musk's got his mitts on the first one. The company relays, "Nvidia founder and CEO Jensen Huang arrived at the SpaceX facility—amid towering engines and gleaming steel—to hand-deliver the company’s just-launched DGX Spark to Elon Musk."

Huang joked, "Imagine delivering the smallest supercomputer next to the biggest rocket," referring to Starship, an in-development orbital rocket with the biggest capacity of any so far.

Nvidia's DGX Spark was first known as Project Digits and is a small home-user AI supercomputer built with Grace Blackwell silicon. More specifically, that silicon is GB10, a chip with a one petaFLOP Blackwell GPU and a Grace CPU with 20 Arm cores, plus 128 GB of LPDDR5X unified memory and up to 4 TB of NVMe storage.

Part of the reason we've had our eye on GB10 and DGX Spark as PC gamers is that there's been lots of talk about it perhaps being transplanted into an N1 APU to make for Windows on Arm laptop chips. That's recently been confirmed by Huang, too, who said Nvidia has "a new Arm product that's called N1", which goes into DGX Spark.

That all-Nvidia N1 laptop chip has a bit of an air of myth about it, though, given its seemingly never-ending delays. These delays seem to have made at least some in the industry a little sceptical about GB10 in general.

Charlie Demerjian of SemiAccurate, for instance, reckons this GB10/N1X launch is a 'PR stunt' because despite the chip "now looking like it will be 18 months late", Nvidia's strategy, he thinks, is to "seed a few units to the media and claim it is production."

Apparently, "SemiAccurate has heard multiple claims of volumes for this seeding program but none exceed two digits. That is a total for all manufacturers, not per OEM." And several "were given a pretty stringent list of do’s and don’ts for their ‘independent’ testing," which Demerjian sees to mean that "Nvidia is seeding a scant few units that don’t actually work right to select media" to "make things look like it is production, or close to."

I can't confirm or deny any of this, but whether it's a "PR stunt" or otherwise, we can at least see that DGX Spark exists in the wild and is in the hands of at least some researchers and so on. On Nvidia's side, the company says these "early recipients" are "testing, validating and optimizing their tools, software and models for DGX Spark."

Also, according to Nvidia, "Acer, ASUS, Dell Technologies, GIGABYTE, HP, Lenovo and MSI are rolling out systems that put petaflop AI on your desk, transforming the desktop into an AI launchpad."

No word on those N1 laptops with Windows on Arm, though. Previous rumours—veritably ancient rumours, now, really—had it that we'd see them featuring in some Alienware gaming laptops with RTX 4070-level performance. Call me a dreamer, but I'm still holding out for that one. Don't burst my bubble, okay?

The explosion of generative AI over the last few years signals a change in the job market alongside it, and this brings with it worries of job instability and losses. With big players like Nvidia, Meta, X, and the governments worldwide further committing to AI, questions are posed to those at the very top.

In a recent interview with the British news channel, Channel 4, Nvidia's CEO Jensun Huang, gave his thoughts on what's next. He says, "If you're an electrician, if you're a plumber, if you're a carpenter, we're going to need hundreds of thousands of them. To build all of these factories."

Huang argues, "The skilled craft segment of every economy is going to boom".

"You're going to have to build. You're going to keep doubling and doubling… every single year."

Just last week, Nvidia shared plans to spend $100 billion on OpenAI. This cash is intended to go towards greater supplies of data centre chips, to further train upcoming AI models. Just weeks before that, Nvidia's earnings report showed it made almost 10 times more from AI than gaming. Nvidia's stock price is also at an all-time high, over 10 times what it was half a decade ago.

OpenAI's spending has also skyrocketed, alongside ChatGPT's popularity, and the US government is firmly behind cementing "US dominance in artificial intelligence". From a PC gaming perspective, we've even seen brands like Razer jump on the AI bandwagon. This is all to say AI doesn't appear to be going away, and it has backing in the hundreds of billions.

When asked what could happen if the UK doesn't 'grasp this opportunity', Huang says, "just as the last industrial revolution, the reason why it came about was because you needed it. And so the industrial revolution that started here in the UK came out of need. You need it now, too."

Earlier this year, the UK's Department for Science, Innovation and Technology signed an agreement with OpenAI to push the chatbot into the public sector in a further bid to make the UK an AI powerhouse.

Though highlighting future employment seems relevant to current fears around the job market, this doesn't address those who have degrees and experience in fields being replaced. Senator Bernie Sanders argued in June that "Artificial intelligence is going to displace millions and millions of workers". A month after this, OpenAI's Sam Altman shared that he thinks some jobs will be "totally, totally gone" due to AI. A former Google executive in August argued AI will lead to a "short-term dystopia" because it will struggle to create new jobs for those it is replacing.

Huang tells reporters, "You're going to be building out AI infrastructure here in the UK for a decade," but it's not clear what the plan is for workers after that.

Nvidia CEO Jensen Huang claims that China is "nanoseconds behind" the US in terms of AI technology and chipmaking. During an interview on the BG2 podcast, a tech and investment focused bi-weekly program, the CEO of Nvidia echoed a sentiment similar to that of comments he made back in May of this year about how his company and the wider American tech industry needs to "go compete" in China.

Huang emphasises, "We’re up against a formidable, innovative, hungry, fast-moving, underregulated [competitor in China]" (via Tom's Hardware). These comments follow a podcast passage where Huang is generally complementary about the current US administration. Huang said, "[President Trump] wants America to win the AI race. This is going to be a very long-term race, and he understands this is a pivotal time. He wants the technology industry to run. He wants everybody in the world to be built on American technology."

But China has been busy, accelerating its own AI infrastructure plans with a reported mandate that its domestic data centres source at least 50% of their chips from similarly domestic manufacturers to avoid a reliance on US-made tech. Huawei, and the company's Ascend 910B chips and CUDA-free systems, are arguably at the forefront of that push.

"People think that they're centrally governed but, remember that the genius of China was distributed economic systems," Huang goes on to elaborate, "And so all of these 33 provinces and all the mayor economy has driven an enormous amount of internal competition, internal economic vibrancy, which of course has some of its side effects. But this is a vibrant entrepreneurial, high tech, modern industry."

These latest comments are spoken amid an incredibly complex geopolitical stage. For one thing, it's a strange state of play on the home field of the US; though the Trump administration appears to be all in on AI with infrastructure projects like Stargate, the latest beat in the tech tariff saga is a plan to hit US companies that don't equally source their chips from the States as well as China with yet another tariff fee.

During the BG2 podcast interview, Huang himself offers further context about Nvidia's place in China, saying the company had previously held a "95% market share" there but was now losing out to home-grown tech competitor Huawei. Though Huang comments in the BG2 podcast that his guidance to investors reassures that there are plenty of opportunities for growth outside of China, the country is still hugely important to Nvidia.

Huang says, "I believe it is in the best interests of China that Nvidia is able to serve that market and compete in that market. [...] It is of course in the fantastic interest of the United States. But those two truths can coexist. It is possible for both to be true and I believe it is both true."

Nvidia has 30 years of history with China and its tech industry—but the company's H20 chips have become something of a flashpoint in this relationship. Nvidia announced back in July that it was applying to export its H20 GPUs to China again. These chips were originally designed to comply with the prior Biden administration's AI diffusion rule (which Nvidia's VP of government affairs, Ned Finkle, was not a fan of).

But despite tech firms in China wanting these chips, Nvidia had to pause production of H20 back in August amid security concerns raised by the Chinese government (some choice remarks from President Trump may not have helped). China's internet regulator, the Cyberspace Administration of China, has also apparently banned some of the country's biggest tech companies from picking up Nvidia's RTX Pro 6000D, a product specifically designed with the Chinese market in mind. Is it any wonder then that major Chinese firm Tencent has moved to build its systems upon homegrown silicone?

With such challenging markets on either side of the geopolitical divide, will the good, profitable-AI-times continue to roll for Nvidia? Or is the company's recent $100 billion deal with OpenAI the beginning of the snake eating its own tail? Time can only tell.

Among other tidbits that emerged from the recent Intel-Nvidia love in is confirmation of what we'd long suspected, namely that the upcoming Nvidia N1 Arm chip for PCs is indeed the very same as GB10, the "Superchip" at the heart of the DGX Spark AI box.

"We also have a new Arm product that's called N1," said Nvidia CEO Jensen Huang at the press conference for the newly announced Intel-Nvidia alliance. "That processor is going to go into the DGX Spark and many other versions of products like that. And so we're super excited about the Arm road map, and this doesn't affect any of that."

Taken at face value, that's both good and bad news. For starters, it means we have a good idea of the specifications of the chip, which Nvidia has already published, if not quite such a clear feel for its real-world performance. That's especially true in the context of PC gaming as opposed to the AI workloads the DGX Spark is aimed at.

Specifically, that means an Arm CPU SoC with 10 Arm Cortex X925 cores and 10 Arm Cortex A725 cores. To that is attached an Nvidia GPU chiplet with 6,144 CUDA cores.

On paper, that gives N1 exactly the same CUDA core count as the RTX 5070, albeit the RTX 5070 runs with a partially disabled GB205 chip, the latter containing 6,400 CUDA cores all told. Of course, it's far from clear what configuration Nvidia might use for N1 when targeted at PCs.

But arguably a bigger question mark hangs over the broader issue of playing PC games on Arm CPUs. Despite the arrival of the Qualcomm Snapdragon X series of Arm CPUs for PCs and a push from Microsoft to support Arm better on Windows, in part courtesy of the Prism translation layer for running x86 code on Arm CPU cores, PC game support and performance on Arm chips is patchy at best.

Now, if any company has the resources and will power to get games running nicely on an Arm CPU as opposed to an x86 CPU, you would think that company is Nvidia. It has relationships with most if not all major game developers and endless cash to spend, should it choose.

What's more, emulation needn't be a dirty word when it comes to PC gaming. Apple has shown how effective emulation can be when done right with its Apple silicon chips offering very high performance x86 emulation.

Of course, Apple added specific hardware features to its custom Arm cores to support that, while the Nvidia N1 chip uses off-the-shelf CPU cores designed by Arm itself. But emulation can definitely work.

Indeed, the Proton compatibility layer for Valve's SteamOS, as used by the Steam Deck proves that translating code on the fly can be a goer, even if Proton is a slightly different beast in translating between Microsoft's DirectX API and Vulkan, while still running on x86 CPUs in both cases.

But the basic question remains: Regardless of how much theoretical GPU power N1 offers, will its Arm CPU cores play nicely with games?

Beyond all that there's the question of price. The DGX Spark is a $4,000 box, which is pretty scary in a PC context. But then the DGX Spark is a pretty specific kind of machine aimed at AI worklaods and comes packed with 128 GB of RAM, Nvidia's ConnectX network interface and more. It's not trying to be built down to the price of an RTX 5070 gaming PC.

On the subject of the price, the obvious comparison here is AMD's Strix Halo chip, another chiplet-based APU with a big fat GPU. That too is arguably too expensive to be interesting as a PC gaming solution and, a bit like DGX Spark, is basically a chip for running AI models locally.

Oh, yes, and the DGX Spark has missed its original launch window of July and still hasn't shipped to customers at the time of writing, amid rumours that the whole Nvidia Arm CPU for PCs thing is being delayed until at least early next year.

All of which means we're a little cool on N1. It has plenty to prove, that's for sure.

It's not too often that I get a complete 'out of the blue' surprise in PC hardware land, but the recent announcement of an Intel-Nvidia partnership certainly fits that bill. And it's even more surprising to discover the two companies, which will now be working together on both datacentre and consumer systems, have been working towards this for a while, keeping it quiet.

During a press conference yesterday, Nvidia CEO Jensen Huang explained: "The two technology teams have been discussing and architecting solutions now for probably coming up to a year, and the two architecture teams—well, it's three architecture teams—are working across, of course, the CPU architecture, as well as product lines for server and PCs."

Why did we not know about these teams working together for the past few months? Simple, they kept schtum:

"There were no communications with anybody else, except between [Intel CEO] Lip-Bu, myself, and the technical teams that were working on this partnership, and we kept it really quiet."

The partnership involves a $5 billion buy-in from Nvidia, and is expected to centre mostly around AI but we're hoping there's at least a smidge of gaming goodness to come from it. Intel processors are going to be NVLink'd upto Nvidia GPUs in datacentres, and in the consumer market we can expect what is sure to initially seem like Frankenstein's monster chips melding Intel and Nvidia chips into single system-on-chips (SoCs). I'm sure we'll get used to that, though.

While Nvidia is sure to get something out of all this—namely, even more foothold in the datacentre market, more pressure on AMD, and more presence in the laptop market—Intel arguably has a lot more to gain. Huang certainly sees much in it for Chipzilla (can we call Intel that, anymore?):

"You know, obviously, it's a very substantial partnership. This is going to expand the market opportunity for Intel in AI infrastructure that is largely unexposed to them today, and it's going to expose to Intel in the consumer notebook market, where really exquisite GPUs are necessary. And so these two markets are unexposed to Intel today, and it's going to be brand new growth markets for Intel."

That is of course not to mention all the Intel shares Nvidia has just bought up.

We're not expecting to see any Intel-Nvidia SoCs in the near future, but in three or four years, the chip landscape might start to seem very different. It could certainly open the door to a big enough change that I can appreciate the left-field announcement after months of secrecy.