Tech
Is there no stopping the AI spending spree? | Computer Weekly
Expect datacentre spending to increase tenfold. That was among the claims Nvidia CEO Jensen Huang made during the company’s latest quarterly earnings call. He forecast that capital expenditure (CapEx) on datacentres would increase from the $300-400bn mark today to $3-4tn by 2030.
Huang’s remarks at the end of February came a few days after Microsoft’s AI Tour London event, when CEO Satya Nadella effectively called for enterprise software developers to use the capabilities now built into Microsoft 365 to create agentic AI workflows for streamlining business processes.
Nadella discussed the need to have an efficient token factory, where phrases or tokens can be streamed into AI engines that interpret natural language for querying large language models (LLMs). The Microsoft vision of enterprise AI is built on the M365 foundation, which acts as a knowledge store on which a new category of knowledge-based software can be built.
During his keynote presentation, Nadella spoke about the intelligence that exists in the various IT systems used across the business. He said that businesses should be able to harness the intelligence that already exists enterprise-wide, starting with what he described as the “data underneath Microsoft 365”, which, according to Nadella, represents the people in the business, their relationship to coworkers, and work artefacts such as projects, calendars and communications data. “This is massive information,” he said, which can be used to bootstrap agentic AI projects.
“Our goal is to have all of the innovation and the systems available in the token factory,” said Nadella. “That way you can build software which has the ability to use all of the capability [we provide] to train models and deliver models for inference.”
In effect, he sees the Windows software developer ecosystem evolving to where it is now a Microsoft 365 ecosystem, where enterprise data is stored in AI-enabled office productivity tools such as Word, Excel, PowerPoint, Teams and Outlook, and these can be used as the foundation for a new generation of applications that can draw on these AI knowledge sources.
It is this idea that all software will need to be knowledge-aware, which Huang spoke about during the company’s earnings call. “Token generation is at the centre of almost everything that relates to software in the future and relates to computing,” he said. “If you look at the way we use computing in the past, however, the amount of computation demand for software in the past is a tiny fraction of what is necessary in the future.”
According to Huang, the amount of computation necessary to run AI is 1,000 times higher than the computing power needed to run non-AI software. “The computing demand is just a lot higher,” he said. “And so, if we continue to believe there’s value in it, then the world will invest to produce that token.”
When asked whether Nvidia is confident that its customers will continue to have the ability to spend more on AI infrastructure, which could impact Nvidia’s ability to grow, Huang spoke about the opportunity in enterprises to make use of agentic AI and its widespread usefulness across organisations.
“We have now seen the inflection of agentic AI, and the usefulness of agents across the world and enterprises everywhere,” he said. “You’re seeing incredible compute demand because of it. In this new world of AI, compute is revenues. Without compute, there’s no way to generate tokens. Without tokens, there’s no way to grow revenues.”
At least, that is how he positioned AI for the investment bank analysts on the earnings call. The company posted fourth quarter revenue of $68bn, up 73% year-over-year. Datacentre revenue increased by 75% to $62bn, which Nvidia said was being driven by demand for its Blackwell architecture and AI inference deployments. It also reported networking revenue of $1bn, up 3.5x year-over-year, fuelled by adoption of NVLink, Spectrum X and other Nvidia ethernet technologies.
Last year, during his keynote presentation at the GTC conference in the US, Huang claimed that the lowest cost per token was being achieved using the most expensive GPU – which at the time was the Grace Blackwell NVLink 72.
Nvidia describes the GB200 Grace Blackwell as a “superchip”, which connects two high-performance Nvidia Blackwell Tensor Core GPUs and the Nvidia Grace CPU with the NVLink-Chip-to-Chip (C2C) interface, capable of delivering 900 GBytes/s of bidirectional bandwidth.
Significantly, the architecture means that applications have coherent access to a unified memory space. According to Nvidia, this simplifies programming and supports the larger memory needs of trillion-parameter LLMs, transformer models for multimodal tasks, models for large-scale simulations, and generative models for 3D data.
‘Huang’s Law’
Some industry observers have coined the term “Huang’s Law” to describe his perspective of how each new generation of GPU delivers a 10x increase in performance, compared with Moore’s Law’s doubling of performance every 18 months.
Nadella and Huang both spoke about how newer hardware is more energy-efficient at running AI workloads. During the Microsoft AI tour, Nadella noted that today’s system supports an entirely different memory hierarchy, which he said means “there’s now no latency with AI inference”.
The messaging from both the Microsoft and Nvidia chiefs is that the best efficiency is achieved by taking advantage of the capabilities available in these new systems. “There’s an unbelievable renaissance happening with these systems and workloads, whether they’re training workloads or inference workloads, they are unlike anything we’ve seen in the past,” said Nadella.
The tech sector is dead set on getting enterprises to adopt more and more AI. It is being built into knowledge-aware enterprise software likely to draw on the capabilities available in the newest generation of AI acceleration hardware.
Clearly, the business models of Microsoft and Nvidia are tied to increased demand for AI. But it is also apparent that the cost of deploying advanced AI systems is not going to get any cheaper. If anything, capital expenditure on datacentres will continue to increase at a phenomenal rate, fuelled by demand for these new AI systems and the AI acceleration hardware they need.
Tech
A Humanoid Robot Set a Half-Marathon Record in China
Over the weekend in China, a humanoid robot shattered world half-marathon record—the human record—by seven minutes.
The star performer was a robot developed by the Chinese company Honor (the smartphone maker), which finished the 13.1-mile race in 50 minutes, 26 seconds. The human record, set by Ugandan Olympic medalist Jacob Kiplimo, is 57 minutes, 20 seconds. The result marks an impressive milestone especially considering that, just a year earlier, the fastest robot at this half-marathon event took two and a half hours to complete the same distance.
But Honor’s robot was not the only participant. The event consisted of more than 100 humanoid robots from 76 institutions across China. The robots lined up alongside 12,000 human runners in Beijing’s E-Town, albeit on separate courses to avoid accidents. The contrast in performance between humans and robots was more than evident.
Run, Robot, Run
A humanoid robot is designed to mimic the structure and movement of the human body, with legs, arms, and sensors that allow it to interact with its environment. In this case, the winning robot incorporated features inspired by elite runners: long legs (almost a meter), advanced balance systems, and a liquid cooling mechanism, similar to that of smartphones, to prevent overheating during the race.
In addition, many of the participating robots operated autonomously, meaning without direct human control. Thanks to artificial intelligence algorithms, they could adjust their pace, maintain balance, and adapt to the terrain in real time. Notably, the Honor robot that achieved the 50-minute mark operated autonomously. The Chinese manufacturer presented another robot, operated by remote control, that ran the same stretch in even less time: 48 minutes, 19 seconds.
As expected, there were some accidents in the race. Some robots fell down, others veered off the path, and several needed technical assistance along the way. While the physical performance of humanoid robots has advanced rapidly, their reliability is still developing. Of course, the laughter and jeers are no longer as frequent as they used to be, replaced by applause and exclamations of surprise.
Robot Superiority
Just like the robots that went viral for their impressive martial arts display a few weeks ago, this long-distance race is part of a broader strategy by China to show off its leadership in the development of advanced robots.
You don’t need to be a robotics expert to see that this achievement demonstrates that machines can outperform humans at specific physical tasks under controlled conditions. (It’s hard to imagine that the winning robot could achieve the same result, for example, if it started to rain during the race.) But humans still have a few tricks up their sleeve: Running in a straight line is very different from performing complex real-world activities, such as manipulating delicate objects or interacting socially.
However, it’s understandable that the image of a robot crossing the finish line in record time, ahead of human athletes, raises several questions. Is this the beginning of a new era in which machines redefine physical limits?
One could argue that a car is a machine, and those have always been faster than humans. But a humanoid robot is designed to mimic humans. It’s more alarming to see one beat humanity at its own game—even if so many of them are still tripping over themselves.
This story originally appeared in WIRED en Español and has been translated from Spanish.
Tech
War Memes Are Turning Conflict Into Content
As ceasefire announcements between the US and Iran—and separately between Israel and Lebanon—dominated headlines over the past two weeks, they also prompted a look back at how war spread online: through memes.
There were jokes about conscription. Captions about getting drafted, but at least with a Bluetooth device. The song “Bazooka” went viral, with users lip-syncing to: “Rest in peace my granny, she got hit by a bazooka.” Military filters followed. So did posts about Americans wanting to be sent to Dubai “to save all the IG models.”
Across the Gulf, the tone was different but the instinct was the same. Memes joked that Iran was replying to Israel faster than the person you’re thinking about. Delivery drivers were shown “dodging missiles.” “Eid fits” became hazmat suits and tactical vests.
Dark humor is one of the oldest responses to fear, a way of reclaiming control, however briefly, over events that offer none. Variations of that idea appear across psychology and philosophy, including Freud’s relief theory, which frames humor as a release of tension.
But social media changes the scale and speed of that instinct.
A joke once shared within a small community can become a global template in minutes. Algorithms do not reward depth or accuracy; they reward engagement. The memes that travel fastest are usually stripped of context, easy to recognize and simple to remix.
Middle East scholar and media analyst Adel Iskandar traces political satire back centuries, from banned satirical papyri in ancient Egypt to cartoons during revolutions and gallows humor in modern wars. “Where there is hardship, there is satire,” he says. “Where there is loss of hope, there is hope in comedy.”
That tradition still exists online. But today it is fused with recommendation systems designed to keep attention moving.
Memes Spread Faster Than Facts
The word “meme” was coined by Richard Dawkins in his 1976 book The Selfish Gene, where he described how ideas replicate like genes. On today’s internet, replication follows platform logic.
Fitness means generality. A meme does not need to be accurate. It needs to feel familiar. It needs the right format, paired with trending audio and the right emotional shorthand.
“A meme is like a virus,” Iskandar says. “If it doesn’t travel, it’ll die.”
The most visible response online is not always the truest one. It is often just the easiest to spread. And once context disappears, one crisis can start to resemble any other.
Geography shapes humor too, and adds another level of tension. “If you live far away from the threat, you’re capable of producing content that ridicules it with an element of safety,” says Iskandar. “Whereas if you happen to be within close proximity, it is more of a fatalism.”
That divide matters. For some users, war exists mainly as mediated spectacle: clips, edits, graphics, headlines, and reaction posts. For others, it is sirens, uncertainty, disrupted flights, rising prices, and messages checking who is safe.
The same meme can function as entertainment in one country and emotional survival in another. Take the American experience of violence, which Sut Jhally, professor of communication at the University of Massachusetts Amherst, says “is very mediated.”
What much of the Western world has consumed instead is what cultural critic George Gerbner called “happy violence”: spectacular, consequence-free, and detached from the aftermath.
Jhally argues that the September 11 attacks remain the defining modern American experience of war-adjacent political violence. Much else has been cinematic: distant invasions, blockbuster destruction, video-game logic, apocalypse franchises.
The teenager from the Midwest joking about being drafted is drawing from zombie films and superhero apocalypses. “There is almost no discussion about what an actual Third World War would look like,” he says. “People do not have a perception of what that really looks like.”
Tech
Hyundai’s New Ioniq 3 Has Hot-Hatch Looks, but Can It Beat BYD?
Hyundai has unveiled its Ioniq 3, a fully electric compact hatchback for urban driving designed to be as aerodynamically efficient as possible yet still offer up a surprisingly spacious interior—a trick the carmaker is loftily calling Aero Hatch. The 3 is intended to fill the gap between Hyundai’s Inster supermini and Ioniq 5 crossover.
In profile, the Ioniq 3 has a sleek front end that transitions into a roofline that stays straight over both front and rear occupants before dropping to merge with the rear spoiler. It’s this roofline that maximizes interior headroom for the rear passengers, but it also offers a supposed class-leading drag coefficient of 0.263.
The car has the same underpinnings as its sibling brand, Kia’s EV2. Two battery options will deliver a projected WLTP distance of 344 km (around 214 miles) for the Standard Range Ioniq 3; the Long Range version is supposedly good for a competitive 308-mile range. Built on the group’s Electric-Global Modular Platform (E-GMP), the car has a 400-volt architecture to lower costs rather than the 800-volt system of the Ioniq 5 N, 6, or 9 SUV. Still, this means that if you can find sufficiently fast DC charging, you can, in theory, top up from 10 to 80 percent in approximately 29 minutes (AC charging capability is up to 22 kW).
This is fine, but it is not a match for BYD’s new Blade 2.0 battery tech that WIRED tried, astonishingly allowing the Denza Z9 GT to charge its battery in just over nine minutes from 10 percent. True, that battery tech was in a $100,000 “premium” EV, but it’s coming to BYD’s wider models. And if BYD makes good on its plans to deliver a charging network to rival Tesla’s Supercharger, then very soon buyers will be expecting comparable charge times, and 30 minutes will quickly feel awfully long.
I asked José Muñoz, Hyundai Motor Company president and CEO, whether this new battery technology from BYD concerns him, whether Hyundai—leading the EV pack with 800-volt architectures for so long—needs to match the Blade 2.0’s performance. “We welcome the challenge,” Muñoz tells me. “Every challenge is an opportunity to do better. And I can tell you that, lately, we have a lot of opportunities to do better.”
“We are also working on fast charging,” Muñoz says, adding that Hyundai’s success will be built on not merely one leading technology but many. “There are not more elements that may be offered by the Chinese that we can offer. It’s only a matter of how you mix them. A lot of times, you get stuck into one indicator. I’m an engineer. And we always have the example of the airplanes: What is more important in an airplane, altitude or speed? There is only one answer. You need to achieve both.”
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