An anonymous reader quotes a report from the BBC: The island of Hokkaido has long been an agricultural powerhouse -- now Japan is investing billions to turn it into a global hub for advanced semiconductors. More than half of Japan's dairy produce comes from Hokkaido, the northernmost of its main islands. In winter, it's a wonderland of ski resorts and ice-sculpture festivals; in summer, fields bloom with bands of lavender, poppies and sunflowers. These days, cranes are popping up across the island -- building factories, research centers and universities focused on technology. It's part of Japan's boldest industrial push in a generation: an attempt to reboot the country's chip-making capabilities and reshape its economic future.

Locals say that beyond the cattle and tourism, Hokkaido has long lacked other industries. There's even a saying that those who go there do so only to leave. But if the government succeeds in turning Hokkaido into Japan's answer to Silicon Valley -- or "Hokkaido Valley", as some have begun to call it -- the country could become a new contender in the $600 billion race to supply the world's computer chips. At the heart of the plan is Rapidus, a little-known company backed by the government and some of Japan's biggest corporations including Toyota, Softbank and Sony.

Born out of a partnership with IBM, it has raised billions of dollars to build Japan's first cutting-edge chip foundry in decades. The government has invested $12 billion in the company, so that it can build a massive semiconductor factory or "fab" in the small city of Chitose. In selecting the Hokkaido location, Rapidus CEO Atsuyoshi Koike points to Chitose's water, electricity infrastructure and its natural beauty. Mr Koike oversaw the fab design, which will be completely covered in grass to harmonize with Hokkaido's landscape, he told the BBC. Local authorities have also flagged the region as being at lower risk of earthquakes compared to other potential sites in Japan.

An anonymous reader quotes a report from Ars Technica: The US crackdown on chip exports to China has continued with the arrests of four people accused of a conspiracy to illegally export Nvidia chips. Two US citizens and two nationals of the People's Republic of China (PRC), all of whom live in the US, were charged in an indictment (PDF) unsealed on Wednesday in US District Court for the Middle District of Florida. The indictment alleges a scheme to send Nvidia "GPUs to China by falsifying paperwork, creating fake contracts, and misleading US authorities," John Eisenberg, assistant attorney general for the Justice Department's National Security Division, said in a press release yesterday.

The four arrestees are Hon Ning Ho (aka Mathew Ho), a US citizen who was born in Hong Kong and lives in Tampa, Florida; Brian Curtis Raymond, a US citizen who lives in Huntsville, Alabama; Cham Li (aka Tony Li), a PRC national who lives in San Leandro, California; and Jing Chen (aka Harry Chen), a PRC national who lives in Tampa on an F-1 non-immigrant student visa. The suspects face a raft of charges for conspiracy to violate the Export Control Reform Act of 2018, smuggling, and money laundering. They could serve many decades in prison if convicted and given the maximum sentences and forfeit their financial gains. The indictment says that Chinese companies paid the conspirators nearly $3.9 million. One of the suspects was briefly the CTO of Corvex, a Virginia-based AI cloud computing company that is planning to go public. Corvex told CNBC yesterday that it "had no part in the activities cited in the Department of Justice's indictment," and that "the person in question is not an employee of Corvex. Previously a consultant to the company, he was transitioning into an employee role but that offer has been rescinded."

An anonymous reader quotes a report from Ars Technica: Some Dell and HP laptop owners have been befuddled by their machines' inability to play HEVC/H.265 content in web browsers, despite their machines' processors having integrated decoding support. Laptops with sixth-generation Intel Core and later processors have built-in hardware support for HEVC decoding and encoding. AMD has made laptop chips supporting the codec since 2015. However, both Dell and HP have disabled this feature on some of their popular business notebooks.

HP discloses this in the data sheets for its affected laptops, which include the HP ProBook 460 G11 [PDF], ProBook 465 G11 [PDF], and EliteBook 665 G11 [PDF]. "Hardware acceleration for CODEC H.265/HEVC (High Efficiency Video Coding) is disabled on this platform," the note reads. Despite this notice, it can still be jarring to see a modern laptop's web browser eternally load videos that play easily in media players. HP and Dell didn't explain why the companies disabled HEVC hardware decoding on their laptops' processors.

A statement from an HP spokesperson said: "In 2024, HP disabled the HEVC (H.265) codec hardware on select devices, including the 600 Series G11, 400 Series G11, and 200 Series G9 products. Customers requiring the ability to encode or decode HEVC content on one of the impacted models can utilize licensed third-party software solutions that include HEVC support. Check with your preferred video player for HEVC software support."

Dell's media relations team shared a similar statement: "HEVC video playback is available on Dell's premium systems and in select standard models equipped with hardware or software, such as integrated 4K displays, discrete graphics cards, Dolby Vision, or Cyberlink BluRay software. On other standard and base systems, HEVC playback is not included, but users can access HEVC content by purchasing an affordable third-party app from the Microsoft Store. For the best experience with high-resolution content, customers are encouraged to select systems designed for 4K or high-performance needs."

Autonomous electric tractor startup Monarch Tractor -- which we covered in 2022 -- warned staff Thursday it may need to lay off more than 100 employees, or possibly even "shut down," according to a company-wide memo obtained by TechCrunch. The report adds: The memo comes after Monarch Tractor was already cutting some positions over the last few weeks at its California corporate facilities and remote teams in India and Singapore, according to multiple former employees who spoke with TechCrunch on the condition of anonymity.

Monarch Tractor was founded in 2018 by a team that included a former top executive at Tesla's first gigafactory and Carlo Mondavi, a scion of the famous winemaking family. The company raised at least $220 million, including $133 million in 2024, as it pursued a goal of making "driver optional" autonomous tractors that could perform tasks at places like wineries and other fruit farms.

An anonymous reader quotes a report from Ars Technica: This year's newest iPhones included one momentous change that marked a new phase in the evolution of Apple Silicon: the Apple N1, Apple's first in-house chip made to handle local wireless connections. The N1 supports Wi-Fi 7, Bluetooth 6, and the Thread smart home communication protocol, and it replaces the third-party wireless chips (mostly made by Broadcom) that Apple used in older iPhones. Apple claimed that the N1 would enable more reliable connectivity for local communication features like AirPlay and AirDrop but didn't say anything about how users could expect it to perform. But Ookla, the folks behind the SpeedTest app and website, have analyzed about five weeks' worth of users' testing data to get an idea of how the iPhone 17 lineup stacks up to the iPhone 16, as well as Android phones with Wi-Fi chips from Qualcomm, MediaTek, and others.

While the N1 isn't at the top of the charts, Ookla says Apple's Wi-Fi chip "delivered higher download and upload speeds on Wi-Fi compared to the iPhone 16 across every studied percentile and virtually every region." The median download speed for the iPhone 17 series was 329.56Mbps, compared to 236.46Mbps for the iPhone 16; the upload speed also jumped from 73.68Mbps to 103.26Mbps. Ookla noted that the N1's best performance seemed to improve scores most of all in the bottom 10th percentile of performance tests, "implying Apple's custom silicon lifts the floor more than the ceiling." The iPhone 17 also didn't top Ookla's global performance charts -- Ookla found that the Pixel 10 Pro series slightly edges out the iPhone 17 in download speed, while a Xiaomi 15T Pro with MediaTek Wi-Fi silicon featured better upload speeds.

Nvidia blew past earnings expectations with soaring revenue and profit, easing fears of an AI bubble and reinforcing its position as the engine of the global AI boom. From a report: Nvidia's sales grew 62% year-over-year to $57 billion in the October quarter, ahead of the $54.9 billion Wall Street had projected, signaling that demand for AI chips remains strong even as more questions emerge about whether returns from the technology will keep up with the pace of AI infrastructure investments. It posted profits of $31.9 billion, up 65% from the year-ago quarter and also slightly above expectations.

"Blackwell sales are off the charts, and cloud GPUs are sold out," Nvidia CEO Jensen Huang said in a statement, a message that echoes his earlier arguments that fears of an AI bubble are overblown. The company also posted stronger-than-expected sales guidance of around $65 billion for the fourth quarter, another indicator that the AI spending spree isn't slowing anytime soon.

An anonymous reader quotes a report from Bloomberg: The Dutch government suspended its powers over chipmaker Nexperia, restoring control to its Chinese owner (paywalled; alternative source) and defusing a standoff with Beijing that had begun to hamper automotive production around the world. The order that gave the Netherlands powers to block or revise decisions at Nexperia was dropped as "a show of goodwill," Economic Affairs Minister Vincent Karremans said Wednesday in a post on social media site X.

Bloomberg had reported earlier this month that the Netherlands was prepared to take the step if chip deliveries from the company's site in China could be confirmed. The move marks a significant de-escalation of a dispute that underscored the global nature of supply chains and highlighted Beijing's growing leverage. Even though Nexperia's chips aren't advanced and the company only operates one facility in China, the spat disrupted automakers from Honda Motor Co. to Volkswagen AG.

The reversal by the Dutch government was set in motion after a breakthrough in talks earlier that involved Chinese and Dutch officials, with input from Germany, the European Union as well as the US. To help resolve the stalemate, Beijing agreed to loosen export restrictions from Nexperia's Chinese plant, the largest of its kind in the world. The Dutch economic affairs ministry sent a delegation to Beijing this week to negotiate a "mutually agreeable solution," according to a ministry statement.

An anonymous reader shared this report from CNBC: [T]he computing power of crypto mining generates a lot of heat, most which just ends up vented into the air. According to digital assets brokerage, K33, the bitcoin mining industry generates about 100 TWh of heat annually — enough to heat all of Finland.This energy waste within a very energy-intense industry is leading entrepreneurs to look for ways to repurpose the heat for homes, offices, or other locations, especially in colder weather months.

During a frigid snap earlier this year, The New York Times reviewed HeatTrio, a $900 space heater that also doubles as a bitcoin mining rig. Others use the heat from their own in-home cryptocurrency mining to spread warmth throughout their house. "I've seen bitcoin rigs running quietly in attics, with the heat they generate rerouted through the home's ventilation system to offset heating costs. It's a clever use of what would otherwise be wasted energy," said Jill Ford, CEO of Bitford Digital, a sustainable bitcoin mining company based in Dallas... "Same price as heating the house, but the perk is that you are mining bitcoin," Ford said...

The crypto-heated future may be unfolding in the town of Challis, Idaho, where Cade Peterson's company, Softwarm, is repurposing bitcoin heat to ward off the winter. Several shops and businesses in town are experimenting with Softwarm's rigs to mine and heat. At TC Car, Truck and RV Wash, Peterson says, the owner was spending $25 a day to heat his wash bays to melt snow and warm up the water. "Traditional heaters would consume energy with no returns. They installed bitcoin miners and it produces more money in bitcoin than it costs to run," Peterson said. Meanwhile, an industrial concrete company is offsetting its $1,000 a month bill to heat its 2,500-gallon water tank by heating it with bitcoin. Peterson has heated his own home for two-and-a-half years using bitcoin mining equipment and believes that heat will power almost everything in the future. "You will go to Home Depot in a few years and buy a water heater with a data port on it and your water will be heated with bitcoin," Peterson said.
Derek Mohr, clinical associate professor at the University of Rochester Simon School of Business, remains skeptical. Bitcoin mining is so specialized now that a home computer, or even network of home computers, would have almost zero chance of being helpful in mining a block of bitcoin, according to Mohr, with mining farms use of specialized chips that are created to mine bitcoin much faster than a home computer... "The bitcoin heat devices I have seen appear to be simple space heaters that use your own electricity to heat the room..."
CNBC also spoke to Andrew Sobko, founder of Argentum AI (which is building a marketplace for sharing computing power), who says the idea makes the most sense in larger settings. "We're working with partners who are already redirecting compute heat into building heating systems and even agricultural greenhouse warming. That's where the economics and environmental benefits make real sense. Instead of trying to move the heat physically, you move the compute closer to where that heat provides value."

A new "cold war" between America and China is "pushing leaders to sideline concerns about the dangers of powerful AI models," reports the Wall Street Journal, "including the spread of disinformation and other harmful content, and the development of superintelligent AI systems misaligned with human values..."

"Both countries are driven as much by fear as by hope of progress. " In Washington and Silicon Valley, warnings abound that China's "authoritarian AI," left unchecked, will erode American tech supremacy. Beijing is gripped by the conviction that a failure to keep pace in AI will make it easier for the U.S. to cut short China's resurgence as a global power. Both countries believe market share for their companies across the world is up for grabs — and with it, the potential to influence large swaths of the global population.

The U.S. still has a clear lead, producing the most powerful AI models. China can't match it in advanced chips and has no answer for the financial firepower of private American investors, who funded AI startups to the tune of $104 billion in the first half of 2025, and are gearing up for more. But it has a massive population of capable engineers, lower costs and a state-led development model that often moves faster than the U.S., all of which Beijing is working to harness to tip the contest in its direction. A new "whole of society" campaign looks to accelerate the construction of computing clusters in areas like Inner Mongolia, where vast solar and wind farms provide plentiful cheap energy, and connect hundreds of data centers to create a shared compute pool — some describe it as a "national cloud" — by 2028. China is also funneling hundreds of billions of dollars into its power grid to support AI training and adoption...

"Our lead is probably in the 'months but not years' realm," said Chris McGuire, who helped design U.S. export controls on AI chips while serving on the National Security Council under the Biden administration. Chinese AI models currently rank at or near the top in every task from coding to video generation, with the exception of search, according to Chatbot Arena, a popular crowdsourced ranking platform. China's manufacturing sector, meanwhile, is rocketing past the U.S. in bringing AI into the physical world through robotaxis, autonomous drones and humanoid robots. Given China's progress, McGuire said, the U.S. is "very lucky" to have its advantage in chips...

If AI surpasses human intelligence and acquires the ability to improve itself, it could confer unshakable scientific, economic and military superiority on the country that controls it. Short of that, AI's ability to automate tedious tasks and process vast amounts of data quickly promises to supercharge everything from cancer diagnoses to missile defense. With so much at stake, hacking and cyber espionage are likely to get worse, as AI gives hackers more powerful tools, while increasing incentives for state-backed groups to try to steal AI-related intellectual property. As distrust grows, Washington and Beijing will also find it hard, if not impossible, to cooperate in areas like preventing extremist groups from using AI in destructive ways, such as building bioweapons. "The costs of the AI Cold War are already high and will go much higher," said Paul Triolo, a former U.S. government analyst and current technology policy lead at business consulting firm DGA-Albright Stonebridge Group. "A U.S.-China AI arms race becomes a self-fulfilling prophecy, with neither side able to trust that the other would observe any restrictions on advanced AI capability development...."
The article includes an interesting observation from Helen Toner, director of strategy for Georgetown's Center for Security and Emerging Technology and a former OpenAI board member. Toner points out "We don't actually know" if boosting computing power with better chips will continue producing more-powerful AI models.

So "If performance plateaus," the Journal writes, "despite all the spending by OpenAI and others — a growing concern in Silicon Valley — China has a chance to compete."

Long-time Slashdot reader schwit1 shares a Substack post by economist/entrepreneur Skander Garroum: You know that feeling when you're waiting for the cable guy, and they said 'between 8am and 6pm, and you waste your entire day, and they never show up? Now imagine that, except the cable guy is 'electricity,' the day is '50 years,' and you're one of 600 million people. At some point, you stop waiting and figure it out yourself.

What's happening across Sub-Saharan Africa right now is the most ambitious infrastructure project in human history, except it's not being built by governments or utilities or World Bank consortiums. It's being built by startups selling solar panels to farmers on payment plans. And it's working. Over 30 million solar products sold in 2024. 400,000 new solar installations every month across Africa. 50% market share captured by companies that didn't exist 15 years ago. Carbon credits subsidizing the cost. IoT chips in every device. 90%+ repayment rates on loans to people earning $2/day.

And if you understand what's happening in Africa, you understand the template for how infrastructure will get built everywhere else for the next 50 years.

An anonymous reader shares a report: Costing tens of thousands of dollars each, Nvidia's pioneering AI chips make up a hefty chunk of the $400 billion that Big Tech plans to invest this year -- a bill expected to hit $3 trillion by 2029. But unlike 19th-century railroads, or the Dotcom boom's fiber-optic cables, the GPUs fueling today's AI mania are short-lived assets with a shelf life of perhaps five years.

As with your iPhone, this stuff tends to lose value and may need upgrading soon because Nvidia and its rivals aim to keep launching better models. Customers like OpenAI will have to deploy them to stay competitive. So while it's comforting that the companies spending most wildly have mountains of cash to throw around (OpenAI aside), the brief useful life of the chips and the generous accounting assumptions underpinning all of this investment are less consoling.

Michael Burry, who made his name betting against US housing and who's recently turned to the AI boom, waded in this week, warning on X that hyperscalers -- industry jargon for the giant companies building gargantuan data centers -- are underestimating depreciation. Far from being a one-off outlay, there's a danger of AI capex becoming a huge recurring expense. That's great for Nvidia and co., but not necessarily for hyperscalers such as Google and Microsoft. Some face a depreciation tsunami that's forcing them to be extra vigilant about controlling other costs. Amazon has plans to eliminate roughly 14,000 jobs.

And while Wall Street is used to financing fast-depreciating assets such as aircraft and autos, it's worrying that private credit funds are increasingly using GPUs as collateral to finance loans. This includes lending to more speculative startups known as neoclouds, who offer GPUs for rent. Microsoft alone has signed more than $60 billion of neocloud deals.

Two of the world's biggest data center developers have projects in Nvidia's hometown that may sit empty for years because the local utility isn't ready to supply electricity. From a report: In Santa Clara, California, where the world's biggest supplier of artificial-intelligence chips is based, Digital Realty Trust applied in 2019 to build a data center. Roughly six years later, the development remains an empty shell awaiting full energization. Stack Infrastructure, which was acquired earlier this year by Blue Owl Capital, has a nearby 48-megawatt project that's also vacant, while the city-owned utility, Silicon Valley Power, struggles to upgrade its capacity.

The fate of the two facilities highlights a major challenge for the US tech sector and indeed the wider economy. While demand for data centers has never been greater, driven by the boom in cloud computing and AI, access to electricity is emerging as the biggest constraint. That's largely because of aging power infrastructure, a slow build-out of new transmission lines and a variety of regulatory and permitting hurdles. And the pressure on power systems is only going to increase. Electricity requirements from AI computing will likely more than double in the US alone by 2035, based on BloombergNEF projections. Nvidia's Jensen Huang and OpenAI's Sam Altman are among corporate leaders that have predicted trillions of dollars will pour into building new AI infrastructure.

"Maybe you've heard that artificial intelligence is a bubble poised to burst," writes a Washington Post technology columnist. "Maybe you have heard that it isn't. (No one really knows either way, but that won't stop the bros from jabbering about it constantly.)"

"But I can confidently tell you that the money being thrown around for AI is so huge that numbers have lost all meaning." The companies pouring money in are so rich and so power-hungry (in multiple meanings of that term) that our puny human brains cannot really comprehend. So let's try to give some meaning and context to the stratospheric numbers in AI. Is it a bubble? Eh, who knows. But it is completely bonkers. In just the past year, the four richest companies developing AI — Microsoft, Google, Amazon and Meta — have spent roughly $360 billion combined for big-ticket projects, which included building AI data centers and stuffing them with computer chips and equipment, according to my analysis of financial disclosures.... How do companies pay for the enormous sums they are lavishing on AI? Mostly, these companies make so much money that they can afford to go bananas...

Eight of the world's top 10 most valuable companies are AI-centric or AI-ish American corporate giants — Nvidia, Apple, Microsoft, Google, Amazon, Broadcom, Meta and Tesla. That's according to tallies from S&P Global Market Intelligence based on the total price of the companies' stock held by investors. My analysis of the S&P data shows that the collective worth of those eight giants, $23 trillion, is more than the value of the next 96 most valuable U.S. companies put together, which includes many still very rich names such as JPMorgan, Walmart, Visa and ExxonMobil. No. 1 on that list, the AI computer chip seller Nvidia, last week become the first company in history to reach a stock market value of $5 trillion. That alone was more than the value of entire stock markets in most countries, Bloomberg News reported, other than the five biggest (in the U.S., China, Japan, Hong Kong and India)...

All the announced or under-construction data centers for powering AI would consume roughly as much electricity as 44 million households in the United States if they run full tilt, according to a recent analysis by the Barclays investment bank as reported by the Financial Times. For context, that's nearly one-third of the total number of residential housing units in the entire country, according to U.S. Census Bureau housing estimates for 2024.

An anonymous reader shares a report: The Netherlands is prepared to suspend its powers over Chinese-owned chipmaker Nexperia in a move that would de-escalate a fight with Beijing that threatens to disrupt automotive production around the world. The Dutch government is ready to shelve the ministerial order that gave it the power to block or change key corporate decisions at Nexperia, if China allows exports of its critical chips again, according to people familiar with the matter.

If the shipment of supplies resumes and is verified in the coming days, the Dutch are willing to revoke its powers as soon as next week, said the people, who spoke on the condition of anonymity. Financial issues between Nexperia and its Chinese operations would also need to be resolved. [...] In a sign of easing tensions, the Dutch government said in a statement late Thursday that it expects Nexperia's Chinese unit to resume chip supplies in the coming days.

OpenAI CFO Sarah Friar said late Wednesday that the AI startup is not seeking a government backstop for its infrastructure commitments, clarifying previous comments she made on stage during the Wall Street Journal's Tech Live event. From a report: At the event, Friar said OpenAI is looking to create an ecosystem of banks, private equity and a federal "backstop" or "guarantee" that could help the company finance its investments in cutting-edge chips. But in a LinkedIn post late Wednesday, Friar softened her stance.

"I used the word 'backstop' and it muddied the point," Friar wrote. "As the full clip of my answer shows, I was making the point that American strength in technology will come from building real industrial capacity which requires the private sector and government playing their part." OpenAI has inked more than $1.4 trillion of infrastructure deals in recent months to try and build out the data centers it says are needed to meet soaring demand. The agreements have raised questions around how the company can afford to make such massive commitments.

Nvidia chief executive Jensen Huang has warned that China will beat the US in the AI race, thanks to lower energy costs and looser regulations. From a report: In the starkest comments yet from the head of the world's most valuable company, Huang told the FT: "China is going to win the AI race." Huang's remarks come after the Trump administration maintained a ban on California-based Nvidia selling its most advanced chips to Beijing following a meeting between US President Donald Trump and Chinese leader Xi Jinping last week.

The Nvidia chief said that the west, including the US and UK, was being held back by "cynicism." "We need more optimism," Huang said on Wednesday on the sidelines of the Financial Times' Future of AI Summit. Huang singled out new rules on AI by US states that could result in "50 new regulations." He contrasted that approach with Chinese energy subsidies that made it more affordable for local tech companies to run Chinese alternatives to Nvidia's AI chips. "Power is free," he said.

An anonymous reader quotes a report from MIT Technology Review: The US- and UK-based company Quantinuum today unveiled Helios, its third-generation quantum computer, which includes expanded computing power and error correction capability. Like all other existing quantum computers, Helios is not powerful enough to execute the industry's dream money-making algorithms, such as those that would be useful for materials discovery or financial modeling. But Quantinuum's machines, which use individual ions as qubits, could be easier to scale up than quantum computers that use superconducting circuits as qubits, such as Google's and IBM's. "Helios is an important proof point in our road map about how we'll scale to larger physical systems," says Jennifer Strabley, vice president at Quantinuum, which formed in 2021 from the merger of Honeywell Quantum Solutions and Cambridge Quantum. Honeywell remains Quantinuum's majority owner.

Located at Quantinuum's facility in Colorado, Helios comprises a myriad of components, including mirrors, lasers, and optical fiber. Its core is a thumbnail-size chip containing the barium ions that serve as the qubits, which perform the actual computing. Helios computes with 98 barium ions at a time; its predecessor, H2, used 56 ytterbium qubits. The barium ions are an upgrade, as they have proven easier to control than ytterbium. These components all sit within a chamber that is cooled to about 15 Kelvin (-432.67 ), on top of an optical table. Users can access the computer by logging in remotely over the cloud. [...] Helios is noteworthy for its qubits' precision, says Rajibul Islam, a physicist at the University of Waterloo in Canada, who is not affiliated with Quantinuum. The computer's qubit error rates are low to begin with, which means it doesn't need to devote as much of its hardware to error correction. Quantinuum had pairs of qubits interact in an operation known as entanglement and found that they behaved as expected 99.921% of the time. "To the best of my knowledge, no other platform is at this level," says Islam.

[...] Besides increasing the number of qubits on its chip, another notable achievement for Quantinuum is that it demonstrated error correction "on the fly," says David Hayes, the company's director of computational theory and design, That's a new capability for its machines. Nvidia GPUs were used to identify errors in the qubits in parallel. Hayes thinks that GPUs are more effective for error correction than chips known as FPGAs, also used in the industry. Quantinuum has used its computers to investigate the basic physics of magnetism and superconductivity. Earlier this year, it reported simulating a magnet on H2, Quantinuum's predecessor, with the claim that it "rivals the best classical approaches in expanding our understanding of magnetism." Along with announcing the introduction of Helios, the company has used the machine to simulate the behavior of electrons in a high-temperature superconductor. Quantinuum is expanding its Helios line with a new system in Minnesota. It's also started developing its fourth-generation quantum computer, Sol, set for 2027 with 192 qubits. Then, a fifth-generation system, Apollo, is expected in 2029 with thousands of qubits and full fault tolerance.

The Chinese government has issued guidance requiring new data centre projects that have received any state funds to only use domestically-made AI chips, Reuters reported Wednesday, citing sources familiar with the matter. From the report: In recent weeks, Chinese regulatory authorities have ordered such data centres that are less than 30% complete to remove all installed foreign chips, or cancel plans to purchase them, while projects in a more advanced stage will be decided on a case-by-case basis, the sources said.

The move could represent one of China's most aggressive steps yet to eliminate foreign technology from its critical infrastructure amid a pause in trade hostilities between Washington and Beijing, and achieve its quest for AI chip self-sufficiency. China's access to advanced AI chips, including those made by Nvidia, has been a key point of friction with the U.S., as the two wrestle for dominance in high-end computing power and AI. U.S. President Donald Trump said in an interview aired on Sunday following talks with Chinese President Xi Jinping last week that Washington will "let them deal with Nvidia but not in terms of the most advanced" chips.

Longtime Slashdot reader dbialac shares a report from EL PAIS: For decades, the progress of electronics has followed a simple rule: smaller is better. Since the 1960s, each new generation of chips has packed more transistors into less space, fulfilling the famous Moore's Law. Formulated by Intel co-founder Gordon Moore in 1965, this law predicted that the number of transistors in an integrated circuit approximately doubles each year. But this race to the minuscule is reaching its physical limits. Now, an international team of scientists is proposing a solution as obvious as it is revolutionary: if we can't keep reducing the size of chips, let's build them up.

Xiaohang Li, a researcher at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia, and his team have designed a chip with 41 vertical layers of semiconductors and insulating materials, approximately ten times higher than any previously manufactured chip. The work, recently published in the journal Nature Electronics, not only represents a technical milestone but also opens the door to a new generation of flexible, efficient, and sustainable electronic devices. "Having six or more layers of transistors stacked vertically allows us to increase circuit density without making the devices smaller laterally," Li explains. "With six layers, we can integrate 600% more logic functions in the same area than with a single layer, achieving higher performance and lower power consumption."

OpenAI "hasn't yet turned a profit," notes Wall Street Journal business columnist Tim Higgins. "Its annual revenue is 2% of Amazon.com's sales.

"Its future is uncertain beyond the hope of ushering in a godlike artificial intelligence that might help cure cancer and transform work and life as we know it. Still, it is brimming with hope and excitement.

"But what if OpenAI fails?" There's real concern that through many complicated and murky tech deals aimed at bolstering OpenAI's finances, the startup has become too big to fail. Or, put another way, if the hype and hope around Chief Executive Sam Altman's vision of the AI future fails to materialize, it could create systemic risk to the part of the U.S. economy likely keeping us out of recession.

That's rarefied air, especially for a startup. Few worried about what would happen if Pets.com failed in the dot-com boom. We saw in 2008-09 with the bank rescues and the Chrysler and General Motors bailouts what happens in the U.S. when certain companies become too big to fail...

[A]fter a lengthy effort to reorganize itself, OpenAI announced moves that will allow it to have a simpler corporate structure. This will help it to raise money from private investors and, presumably, become a publicly traded company one day. Already, some are talking about how OpenAI might be the first trillion-dollar initial public offering... Nobody is saying OpenAI is dabbling in anything like liar loans or subprime mortgages. But the startup is engaging in complex deals with the key tech-industry pillars, the sorts of companies making the guts of the AI computing revolution, such as chips and Ethernet cables. Those companies, including Nvidia and Oracle, are partnering with OpenAI, which in turn is committing to make big purchases in coming years as part of its growth ambitions.

Supporters would argue it is just savvy dealmaking. A company like Nvidia, for example, is putting money into a market-making startup while OpenAI is using the lofty value of its private equity to acquire physical assets... They're rooting for OpenAI as a once-in-a-generational chance to unseat the winners of the last tech cycles. After all, for some, OpenAI is the next Apple, Facebook, Google and Tesla wrapped up in one. It is akin to a company with limitless potential to disrupt the smartphone market, create its own social-media network, replace the search engine, usher in a robot future and reshape nearly every business and industry.... To others, however, OpenAI is something akin to tulip mania, the harbinger of the Great Depression, or the next dot-com bubble. Or worse, they see, a jobs killer and mad scientist intent on making Frankenstein.

But that's counting on OpenAI's success.