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Capitalism can seem so perverse. Take Microsoft, which is celebrating record financial performance by inviting 60,000 employees to consider continuing their careers outside the company. Voluntary redundancy may seem to make sense when a company's running out of cash, but Microsoft is dripping with the stuff. It was a very good fiscal '26 at Redmond. Its Azure business is up over 40 percent, it's has 30 million paid seats on CoPilot, revenues are through the roof, and it has so much moolah it returned $10.2 billion to shareholders in the form of dividends and share repurchases. This latter move probably soothed CEO Satya Nadella, who suffered, due to the vagaries of C-suite reimbursement and incentive packages, a 6 percent cut in his pocket money. But as he’s also a stockholder with about 0.01 percent of the company, his share of the cash return presumably eased the pain. He won't have been offered redundo. Jenkins, the large wheelbarrow if you please. Microsoft, then, can afford all its employees, each who contributes about $1.5 million to SatNad's bottom line. The "massive efficiencies and ROI of AI" make a great line for a company flogging magic LLM juice, but the evidence remains elusive. AI is, of course, still the reason. Nothing else matters these days. It’s just that it's not today's AI. Among all the fulsome figures, analysts noted that Microsoft's capital expenditure wasn't as spendy as expected. Quite a lot has been pushed into next calendar year, not because it's not there to be spent – Microsoft could build a 1:1 scale model of the Vatican filled with robot priests if it wanted – but because so much it wanted to mash the Buy Now button for was "Out of stock. More expected soon." This is bad. MS added 88 datacenters in its most recent full financial year. That’s not enough datacenters for a cloud business expected to grow by half again in 2027, and hugely not enough to do the other thing. Lags in the cadence of deforestation, dewatering and detonation of the planet can't be tolerated. Thus there are contracts signed to get things back on track PDQ, with mucho, mucho, mucho sponduiks. Microsoft is hinting, those selfsame analysts say, that it will have to go to the debt market and go into "negative free cash flow" territory in 2028. In other words, as well as spending its own bank, the company will be taking out massive loans. This is why Billy and Bhavya Dev have to go. The cost of borrowing depends on the financial health of the borrower, and that boils down to how much profit you're making from the money you earn. A big round of redundancies, which are very costly in themselves, sits on the books of the year they happen. The hole in expenditure left by the vanished salaries lives on. The capital must flow. Will this work? Last week, we listed the reasons why it might not — price competition between rivals and increasingly powerful local and open weight models, supply side shortages, you know the litany by now. This week is Groundhog week, with fresh stories singing the same songs from different choirs. Any sensible soul, especially developers sitting on the sharp end of AI's forcible insertion into their working lives, will know how uncertain the job market is. Voluntary redundancy is a very high stakes bet, and the game is very different if you're in an organization that's going downhill and may need to get rid of you later with far less cash available than if you're nominally making $1.5 million in a place whose biggest problem is that it physically can't move into a bigger shell. On average, only 5 percent or so of those offered voluntary redundancy take it, which Microsoft HR will have factored in. It's cold outside and snug within, so that may be on the high side. The biggest knock-on of such schemes is cultural, with only the very confident moving on out, a disproportionate loss of talent and role models. Hey, the cost of doing business, right? For those who do decide to leave and watch the fireworks from outside the tent, part of the deal is career development resources. Sounds great, if anyone knows what technical careers will look like if either AI works and does indeed do all the work, or it fails and the global financial system throws a humongous wobble. Or anything in between. So, here's an exercise in very dark humor quite fitting for the Halloween season. Ask your favorite AI what careers will be available for coders made redundant by AI. It will give you a long and plausible list. Then ask it – and yourself – why AI won't be able to do any of those jobs too. Buying a truck and a wrench and calling yourself a plumber is probably safest. Nobody will ever want AI to fix their toilet. ®

Capitalism can seem so perverse. Take Microsoft, which is celebrating record financial performance by inviting 60,000 employees to consider continuing their careers outside the company. Voluntary redundancy may seem to make sense when a company's running out of cash, but Microsoft is dripping with the stuff. It was a very good fiscal '26 at Redmond. Its Azure business is up over 40 percent, it's has 30 million paid seats on CoPilot, revenues are through the roof, and it has so much moolah it returned $10.2 billion to shareholders in the form of dividends and share repurchases. This latter move probably soothed CEO Satya Nadella, who suffered, due to the vagaries of C-suite reimbursement and incentive packages, a 6 percent cut in his pocket money. But as he’s also a stockholder with about 0.01 percent of the company, his share of the cash return presumably eased the pain. He won't have been offered redundo. Jenkins, the large wheelbarrow if you please. Microsoft, then, can afford all its employees, each who contributes about $1.5 million to SatNad's bottom line. The "massive efficiencies and ROI of AI" make a great line for a company flogging magic LLM juice, but the evidence remains elusive. AI is, of course, still the reason. Nothing else matters these days. It’s just that it's not today's AI. Among all the fulsome figures, analysts noted that Microsoft's capital expenditure wasn't as spendy as expected. Quite a lot has been pushed into next calendar year, not because it's not there to be spent – Microsoft could build a 1:1 scale model of the Vatican filled with robot priests if it wanted – but because so much it wanted to mash the Buy Now button for was "Out of stock. More expected soon." This is bad. MS added 88 datacenters in its most recent full financial year. That’s not enough datacenters for a cloud business expected to grow by half again in 2027, and hugely not enough to do the other thing. Lags in the cadence of deforestation, dewatering and detonation of the planet can't be tolerated. Thus there are contracts signed to get things back on track PDQ, with mucho, mucho, mucho sponduiks. Microsoft is hinting, those selfsame analysts say, that it will have to go to the debt market and go into "negative free cash flow" territory in 2028. In other words, as well as spending its own bank, the company will be taking out massive loans. This is why Billy and Bhavya Dev have to go. The cost of borrowing depends on the financial health of the borrower, and that boils down to how much profit you're making from the money you earn. A big round of redundancies, which are very costly in themselves, sits on the books of the year they happen. The hole in expenditure left by the vanished salaries lives on. The capital must flow. Will this work? Last week, we listed the reasons why it might not — price competition between rivals and increasingly powerful local and open weight models, supply side shortages, you know the litany by now. This week is Groundhog week, with fresh stories singing the same songs from different choirs. Any sensible soul, especially developers sitting on the sharp end of AI's forcible insertion into their working lives, will know how uncertain the job market is. Voluntary redundancy is a very high stakes bet, and the game is very different if you're in an organization that's going downhill and may need to get rid of you later with far less cash available than if you're nominally making $1.5 million in a place whose biggest problem is that it physically can't move into a bigger shell. On average, only 5 percent or so of those offered voluntary redundancy take it, which Microsoft HR will have factored in. It's cold outside and snug within, so that may be on the high side. The biggest knock-on of such schemes is cultural, with only the very confident moving on out, a disproportionate loss of talent and role models. Hey, the cost of doing business, right? For those who do decide to leave and watch the fireworks from outside the tent, part of the deal is career development resources. Sounds great, if anyone knows what technical careers will look like if either AI works and does indeed do all the work, or it fails and the global financial system throws a humongous wobble. Or anything in between. So, here's an exercise in very dark humor quite fitting for the Halloween season. Ask your favorite AI what careers will be available for coders made redundant by AI. It will give you a long and plausible list. Then ask it – and yourself – why AI won't be able to do any of those jobs too. Buying a truck and a wrench and calling yourself a plumber is probably safest. Nobody will ever want AI to fix their toilet. ®

Capitalism can seem so perverse. Take Microsoft, which is celebrating record financial performance by inviting 60,000 employees to consider continuing their careers outside the company. Voluntary redundancy may seem to make sense when a company's running out of cash, but Microsoft is dripping with the stuff. It was a very good fiscal '26 at Redmond. Its Azure business is up over 40 percent, it's has 30 million paid seats on CoPilot, revenues are through the roof, and it has so much moolah it returned $10.2 billion to shareholders in the form of dividends and share repurchases. This latter move probably soothed CEO Satya Nadella, who suffered, due to the vagaries of C-suite reimbursement and incentive packages, a 6 percent cut in his pocket money. But as he’s also a stockholder with about 0.01 percent of the company, his share of the cash return presumably eased the pain. He won't have been offered redundo. Jenkins, the large wheelbarrow if you please. Microsoft, then, can afford all its employees, each who contributes about $1.5 million to SatNad's bottom line. The "massive efficiencies and ROI of AI" make a great line for a company flogging magic LLM juice, but the evidence remains elusive. AI is, of course, still the reason. Nothing else matters these days. It’s just that it's not today's AI. Among all the fulsome figures, analysts noted that Microsoft's capital expenditure wasn't as spendy as expected. Quite a lot has been pushed into next calendar year, not because it's not there to be spent – Microsoft could build a 1:1 scale model of the Vatican filled with robot priests if it wanted – but because so much it wanted to mash the Buy Now button for was "Out of stock. More expected soon." This is bad. MS added 88 datacenters in its most recent full financial year. That’s not enough datacenters for a cloud business expected to grow by half again in 2027, and hugely not enough to do the other thing. Lags in the cadence of deforestation, dewatering and detonation of the planet can't be tolerated. Thus there are contracts signed to get things back on track PDQ, with mucho, mucho, mucho sponduiks. Microsoft is hinting, those selfsame analysts say, that it will have to go to the debt market and go into "negative free cash flow" territory in 2028. In other words, as well as spending its own bank, the company will be taking out massive loans. This is why Billy and Bhavya Dev have to go. The cost of borrowing depends on the financial health of the borrower, and that boils down to how much profit you're making from the money you earn. A big round of redundancies, which are very costly in themselves, sits on the books of the year they happen. The hole in expenditure left by the vanished salaries lives on. The capital must flow. Will this work? Last week, we listed the reasons why it might not — price competition between rivals and increasingly powerful local and open weight models, supply side shortages, you know the litany by now. This week is Groundhog week, with fresh stories singing the same songs from different choirs. Any sensible soul, especially developers sitting on the sharp end of AI's forcible insertion into their working lives, will know how uncertain the job market is. Voluntary redundancy is a very high stakes bet, and the game is very different if you're in an organization that's going downhill and may need to get rid of you later with far less cash available than if you're nominally making $1.5 million in a place whose biggest problem is that it physically can't move into a bigger shell. On average, only 5 percent or so of those offered voluntary redundancy take it, which Microsoft HR will have factored in. It's cold outside and snug within, so that may be on the high side. The biggest knock-on of such schemes is cultural, with only the very confident moving on out, a disproportionate loss of talent and role models. Hey, the cost of doing business, right? For those who do decide to leave and watch the fireworks from outside the tent, part of the deal is career development resources. Sounds great, if anyone knows what technical careers will look like if either AI works and does indeed do all the work, or it fails and the global financial system throws a humongous wobble. Or anything in between. So, here's an exercise in very dark humor quite fitting for the Halloween season. Ask your favorite AI what careers will be available for coders made redundant by AI. It will give you a long and plausible list. Then ask it – and yourself – why AI won't be able to do any of those jobs too. Buying a truck and a wrench and calling yourself a plumber is probably safest. Nobody will ever want AI to fix their toilet. ®

As robotaxis continue trials in London, an independent research group thinks the UK needs to answer some serious questions before heading any further down the road. To kick off, the sovereignty question, or "Will Britain become dependent on autonomous vehicle services for any key activities and what fallback options will exist if a supplier fails or withdraws?" as the Institute for Driverless Transport (IfDT) puts it. Another question concerns employment: "To what extent does professional driving form part of the UK's employment safety net and how will this function be recreated if demand for professional drivers is significantly reduced?" The objective for IfDT — an independent UK research and convening body focused on the consequences of autonomous vehicles — is to cast the net a bit wider than simply thinking about whether the software is sufficient to navigate London’s wiggly streets and narrow alleys. The research draws on work with operators trying to bring AVs to London and the regulators responsible for policy. It also relied on more than 30 conversations with councils, operators, industry, unions, charities, insurers, lawyers and universities. James Hutt, IfDT co-founder, said: "What struck us most in the interviews was how far this reaches: into jobs, public services, the built environment and national resilience. The people who know those areas best are rarely part of the conversation about AVs. "Our next step is to bring funding and researchers together with the businesses and public bodies that need answers. If you can fund research or offer a place to test it, we would like to hear from you." In August, Transport for London (TfL) granted private hire licences to autonomous vehicle operators provided that a human driver is present during journeys. Wayve and Uber have since launched self-driving rides in the UK capital, with 15 electric Ford Mustangs, equipped with the Wayve AI driver, set to pick up passengers with a safety driver on board. UK company Wayve also demoed a Nissan LEAF, running the Wayve AI Driver using NVIDIA DRIVE Hyperion with self-driving equipment built more closely into the car's design. IfDT points out that Waymo and Baidu are also preparing services for London, while Uber, Pony.ai and Verne have begun testing in Manchester. The research organization said UK authorities still need to answer a long list of questions in order to shape long-term infrastructure plans for local areas and prepare for AI's impact on the labor market. The question of who needs to do this also remains unanswered, as the IfDT asks: "Which are the key public bodies that should already be anticipating the impact of AVs on their own work and who within those organisations should lead a response?"®

As robotaxis continue trials in London, an independent research group thinks the UK needs to answer some serious questions before heading any further down the road. To kick off, the sovereignty question, or "Will Britain become dependent on autonomous vehicle services for any key activities and what fallback options will exist if a supplier fails or withdraws?" as the Institute for Driverless Transport (IfDT) puts it. Another question concerns employment: "To what extent does professional driving form part of the UK's employment safety net and how will this function be recreated if demand for professional drivers is significantly reduced?" The objective for IfDT — an independent UK research and convening body focused on the consequences of autonomous vehicles — is to cast the net a bit wider than simply thinking about whether the software is sufficient to navigate London’s wiggly streets and narrow alleys. The research draws on work with operators trying to bring AVs to London and the regulators responsible for policy. It also relied on more than 30 conversations with councils, operators, industry, unions, charities, insurers, lawyers and universities. James Hutt, IfDT co-founder, said: "What struck us most in the interviews was how far this reaches: into jobs, public services, the built environment and national resilience. The people who know those areas best are rarely part of the conversation about AVs. "Our next step is to bring funding and researchers together with the businesses and public bodies that need answers. If you can fund research or offer a place to test it, we would like to hear from you." In August, Transport for London (TfL) granted private hire licences to autonomous vehicle operators provided that a human driver is present during journeys. Wayve and Uber have since launched self-driving rides in the UK capital, with 15 electric Ford Mustangs, equipped with the Wayve AI driver, set to pick up passengers with a safety driver on board. UK company Wayve also demoed a Nissan LEAF, running the Wayve AI Driver using NVIDIA DRIVE Hyperion with self-driving equipment built more closely into the car's design. IfDT points out that Waymo and Baidu are also preparing services for London, while Uber, Pony.ai and Verne have begun testing in Manchester. The research organization said UK authorities still need to answer a long list of questions in order to shape long-term infrastructure plans for local areas and prepare for AI's impact on the labor market. The question of who needs to do this also remains unanswered, as the IfDT asks: "Which are the key public bodies that should already be anticipating the impact of AVs on their own work and who within those organisations should lead a response?"®

Nanjing Iron & Steel Co., Ltd. (NISCO) has worked with Huawei and ecosystem partners to commercially deploy the world's first steel model powered by swarm intelligence - the YuanYe Steel Large Model (YuanYe) - across multiple scenarios at scale. This helps NISCO transition its core operations from relying on experience to being powered by data and intelligence collaboration. As a traditional manufacturer navigating the challenges of transformation and cost efficiency, NISCO has built a robust digital and intelligent foundation by adopting industry-leading products including Ascend, Kunpeng, Huawei Cloud Stack, and Pangu models. By embedding AI into every core stage of production - ironmaking, steelmaking, rolling, and quality inspection - NISCO is forging green and high-end AI-powered super steel plants. Unlike general-purpose monolithic models, YuanYe innovatively fuses multiple AI models with the steel industry's metallurgical mechanism models to create a dual-drive, multi-model cluster architecture. This architecture features a "right brain" for probabilistic computing and a "left brain" for precise and scientific decision-making. Powered by massive amounts of sensing data aggregated from millions of operational technology (OT) data points across 26 business domains, NISCO has achieved real-time digital twin mapping within its intelligent operations center, laying solid data and scenario foundations for YuanYe. This enables the entire steelmaking process to become not only visible, but also capable of precise control and intelligent assessment. Now 100 percent of NISCO's key equipment is connected and digitally controlled and its new product R&D cycles have been shortened by 50 percent, reducing annual costs by over CNY100m (approx. US$15m). As the model continues to iterate, NISCO had launched 25 business agents by October 2026. These agents cover a wide range of scenarios, from visual quality inspection and process optimization to production scheduling and operations management, setting a new benchmark for digital and intelligent steel transformation. Breakthroughs in four core scenarios: YuanYe redefines traditional operations for significant safety, efficiency, and quality gains In the ironmaking stage, AI makes traditionally invisible blast furnaces transparent. YuanYe leverages blast furnaces' internal sensor data and metallurgical mechanism analysis to perform real-time dynamic simulations of the ironmaking process. Assisted by furnace temperature prediction and health diagnosis models, furnace operators can predict temperatures and identify issues two hours in advance, with over 90 percent accuracy. This shifts furnace operations from reactive post-event remediation to proactive pre-control, increasing prime-grade molten iron yield by over 10 percent while significantly cutting unit energy consumption. In the rolling stage, AI drives precise predictions and codifies expert experience to enhance the operational stability of steel rolling and secure leadership in product quality. To tackle the highly dynamic and complex operating conditions during the rolling process, YuanYe's rolling-force prediction model achieves millisecond-level response, narrowing the thickness tolerance to ±0.2 mm and reducing the steel thickness deviation to 1.9 percent to reach a world-leading standard. The rolling-force hit rate has jumped from 88 percent to 98 percent, supporting a steady annual output of over 2.5 million tons of steel plates and increasing the overall yield rate by 0.5 percent. Enhanced dimensional precision and physical-chemical stability allow NISCO's products to meet demanding steel specifications across diverse applications, ranging from mega stadiums and oil pipelines to 10,000-ton cruise ships and LNG storage tanks. In quality inspection, the synergy between robots and AI models serves as a discerning "eagle eye", doubling metallographic inspection efficiency. During metallographic inspection for finished steel, the integrated smart metallographic inspection system built on YuanYe has achieved full-process automation, covering sample grinding and polishing, image acquisition, and smart grading. Inspection accuracy has risen to over 95 percent, while per-sample inspection time has been shortened from 10 minutes down to 3–5 minutes. This 80 percent increase in overall inspection efficiency frees human operators to focus on anomaly analysis and high-level decision-making. In the energy and environmental control stage, NISCO leverages the YuanYe architecture to develop the S-Link Intelligent Agent for Gas and Flue Gas Sulfur Control. Integrating 602 process parameters alongside multi-modal image and knowledge capabilities, the agent achieves a smart closed loop across source prediction, process optimization, and end-of-pipe compliance. By combining mechanism inversion with time-series forecasting, it issues precise sulfur-risk warnings one hour in advance, achieving a sulfur prediction accuracy of over 95 percent. Operational optimization algorithms then calculate the optimal gas blending scheme within seconds. Finally, game-theoretic models dynamically allocate emission quotas, slashing natural gas co-firing consumption by nearly 50 percent. This has reduced downtime caused by emission exceedance by over 25 percent, and delivered more than CNY600,000 (approx. US$90,000) in annual economic benefits - securing both environmental compliance and drastic cost reduction. From automating labor to empowering people: Defining a new paradigm of inclusive AI Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, said: "Digital and intelligent transformation is inherently human-centric. Its purpose is not to replace people, but to unleash human potential. Our goal is to lift employees out of the endless sea of data, empowering them to direct their creative energy toward work of higher value." To date, NISCO has deployed over 300 AI models across its plants, alongside more than 1,000 low-code agents and lightweight applications built independently by frontline employees. As Cheng Yongfu, Senior Industrial Solution Expert at Huawei's Steel & Non-ferrous BU, noted: "The real value of industrial AI can only be realized when it expands from single-point applications to comprehensive integration with production, operations, and management, which can unlock sustained, scalable empowerment." Looking ahead, as model deployment expands and computing demands continue to grow, NISCO will team up with Huawei and other partners to explore the construction of dedicated data centers for smart steel plants. Centered on the AI-native three-tier architecture (AI-native OS, AI-native factory, and AI-native enterprise) and powered by the YuanYe model, NISCO is accelerating high-quality steel development, aiming to provide a replicable and scalable benchmark for the digital and intelligent transformation of the global steel and manufacturing industries. Supplied by Huawei

Nanjing Iron & Steel Co., Ltd. (NISCO) has worked with Huawei and ecosystem partners to commercially deploy the world's first steel model powered by swarm intelligence - the YuanYe Steel Large Model (YuanYe) - across multiple scenarios at scale. This helps NISCO transition its core operations from relying on experience to being powered by data and intelligence collaboration. As a traditional manufacturer navigating the challenges of transformation and cost efficiency, NISCO has built a robust digital and intelligent foundation by adopting industry-leading products including Ascend, Kunpeng, Huawei Cloud Stack, and Pangu models. By embedding AI into every core stage of production - ironmaking, steelmaking, rolling, and quality inspection - NISCO is forging green and high-end AI-powered super steel plants. Unlike general-purpose monolithic models, YuanYe innovatively fuses multiple AI models with the steel industry's metallurgical mechanism models to create a dual-drive, multi-model cluster architecture. This architecture features a "right brain" for probabilistic computing and a "left brain" for precise and scientific decision-making. Powered by massive amounts of sensing data aggregated from millions of operational technology (OT) data points across 26 business domains, NISCO has achieved real-time digital twin mapping within its intelligent operations center, laying solid data and scenario foundations for YuanYe. This enables the entire steelmaking process to become not only visible, but also capable of precise control and intelligent assessment. Now 100 percent of NISCO's key equipment is connected and digitally controlled and its new product R&D cycles have been shortened by 50 percent, reducing annual costs by over CNY100m (approx. US$15m). As the model continues to iterate, NISCO had launched 25 business agents by October 2026. These agents cover a wide range of scenarios, from visual quality inspection and process optimization to production scheduling and operations management, setting a new benchmark for digital and intelligent steel transformation. Breakthroughs in four core scenarios: YuanYe redefines traditional operations for significant safety, efficiency, and quality gains In the ironmaking stage, AI makes traditionally invisible blast furnaces transparent. YuanYe leverages blast furnaces' internal sensor data and metallurgical mechanism analysis to perform real-time dynamic simulations of the ironmaking process. Assisted by furnace temperature prediction and health diagnosis models, furnace operators can predict temperatures and identify issues two hours in advance, with over 90 percent accuracy. This shifts furnace operations from reactive post-event remediation to proactive pre-control, increasing prime-grade molten iron yield by over 10 percent while significantly cutting unit energy consumption. In the rolling stage, AI drives precise predictions and codifies expert experience to enhance the operational stability of steel rolling and secure leadership in product quality. To tackle the highly dynamic and complex operating conditions during the rolling process, YuanYe's rolling-force prediction model achieves millisecond-level response, narrowing the thickness tolerance to ±0.2 mm and reducing the steel thickness deviation to 1.9 percent to reach a world-leading standard. The rolling-force hit rate has jumped from 88 percent to 98 percent, supporting a steady annual output of over 2.5 million tons of steel plates and increasing the overall yield rate by 0.5 percent. Enhanced dimensional precision and physical-chemical stability allow NISCO's products to meet demanding steel specifications across diverse applications, ranging from mega stadiums and oil pipelines to 10,000-ton cruise ships and LNG storage tanks. In quality inspection, the synergy between robots and AI models serves as a discerning "eagle eye", doubling metallographic inspection efficiency. During metallographic inspection for finished steel, the integrated smart metallographic inspection system built on YuanYe has achieved full-process automation, covering sample grinding and polishing, image acquisition, and smart grading. Inspection accuracy has risen to over 95 percent, while per-sample inspection time has been shortened from 10 minutes down to 3–5 minutes. This 80 percent increase in overall inspection efficiency frees human operators to focus on anomaly analysis and high-level decision-making. In the energy and environmental control stage, NISCO leverages the YuanYe architecture to develop the S-Link Intelligent Agent for Gas and Flue Gas Sulfur Control. Integrating 602 process parameters alongside multi-modal image and knowledge capabilities, the agent achieves a smart closed loop across source prediction, process optimization, and end-of-pipe compliance. By combining mechanism inversion with time-series forecasting, it issues precise sulfur-risk warnings one hour in advance, achieving a sulfur prediction accuracy of over 95 percent. Operational optimization algorithms then calculate the optimal gas blending scheme within seconds. Finally, game-theoretic models dynamically allocate emission quotas, slashing natural gas co-firing consumption by nearly 50 percent. This has reduced downtime caused by emission exceedance by over 25 percent, and delivered more than CNY600,000 (approx. US$90,000) in annual economic benefits - securing both environmental compliance and drastic cost reduction. From automating labor to empowering people: Defining a new paradigm of inclusive AI Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, said: "Digital and intelligent transformation is inherently human-centric. Its purpose is not to replace people, but to unleash human potential. Our goal is to lift employees out of the endless sea of data, empowering them to direct their creative energy toward work of higher value." To date, NISCO has deployed over 300 AI models across its plants, alongside more than 1,000 low-code agents and lightweight applications built independently by frontline employees. As Cheng Yongfu, Senior Industrial Solution Expert at Huawei's Steel & Non-ferrous BU, noted: "The real value of industrial AI can only be realized when it expands from single-point applications to comprehensive integration with production, operations, and management, which can unlock sustained, scalable empowerment." Looking ahead, as model deployment expands and computing demands continue to grow, NISCO will team up with Huawei and other partners to explore the construction of dedicated data centers for smart steel plants. Centered on the AI-native three-tier architecture (AI-native OS, AI-native factory, and AI-native enterprise) and powered by the YuanYe model, NISCO is accelerating high-quality steel development, aiming to provide a replicable and scalable benchmark for the digital and intelligent transformation of the global steel and manufacturing industries. Supplied by Huawei

Welcome to Monday morning, an occasion The Register marks with a new instalment of "Who, Me?" It's our reader-contributed column in which you confess to workplace mistakes and share your escapes from subsequent scrapes. This week, meet a reader we'll Regomize as "Gordon" who told us he once worked as an engineer at a major semiconductor corporation. Gordon rose to become manager of an engineering team which worked on a very popular PC chipset. One of the chaps on this team wasn't pulling his weight, so Gordon got the job of telling him to improve, or leave. "In all fairness, he was a nice guy but not a great engineer and needed to be better," Gordon told The Register. Not long after that moment of managerial unpleasantness, Gordon's team got the job of doing a full backup of the chipset's "production stepping" – the silicon equivalent of a minor point release. The idea was to create a detailed record that could be used as a restore point. "This was not a nightly backup, but a purposeful backup to retain a snapshot of the entire cleaned-up design database for future cases where we might need to spin another stepping quickly," Gordon explained. Gordon told his underperforming colleague to do the backup. "Because I was overworked, I did not think this through," he told The Register. The at-risk worker quickly proved why he was under the pump by deciding the backup wasn't necessary until the team completed the next stepping – but didn't tell anyone about that plan. Before that next stepping was done, the employee's past indiscretions caught up with him and he was let go. The story now fast-forwards six years, to a moment when Gordon learned that a customer wanted to buy the old chipset design so they could make a radiation-hardened version to use on satellites. The major semiconductor company liked the sound of that, and asked Gordon to find the backup. "My colleague and I then pieced together what had happened," he wrote. "Being good engineers, we said nothing. We searched through old nightly backup tapes until we found bits and pieces of different steppings of the design database and copied them all to one place, then handed this off to the customer." To this day, Gordon doesn't know if the customer was able to produce a useful chip from the bits of backup he cobbled together. "Did they realize they received bits and pieces of two slightly different databases? Did they care? Was the project canceled before anyone realized it?" "From then on, I was more careful about who I assigned the task of creating restore backups for each design project," he told The Register. "And I kept a record of the emails requesting backups and confirmation that backups had been done." Have you given a job to the wrong person? Or given clients slightly dodgy data? In either case, click here to send email to Who, Me? We would love to tell your tale on a future Monday. ®

Welcome to Monday morning, an occasion The Register marks with a new instalment of "Who, Me?" It's our reader-contributed column in which you confess to workplace mistakes and share your escapes from subsequent scrapes. This week, meet a reader we'll Regomize as "Gordon" who told us he once worked as an engineer at a major semiconductor corporation. Gordon rose to become manager of an engineering team which worked on a very popular PC chipset. One of the chaps on this team wasn't pulling his weight, so Gordon got the job of telling him to improve, or leave. "In all fairness, he was a nice guy but not a great engineer and needed to be better," Gordon told The Register. Not long after that moment of managerial unpleasantness, Gordon's team got the job of doing a full backup of the chipset's "production stepping" – the silicon equivalent of a minor point release. The idea was to create a detailed record that could be used as a restore point. "This was not a nightly backup, but a purposeful backup to retain a snapshot of the entire cleaned-up design database for future cases where we might need to spin another stepping quickly," Gordon explained. Gordon told his underperforming colleague to do the backup. "Because I was overworked, I did not think this through," he told The Register. The at-risk worker quickly proved why he was under the pump by deciding the backup wasn't necessary until the team completed the next stepping – but didn't tell anyone about that plan. Before that next stepping was done, the employee's past indiscretions caught up with him and he was let go. The story now fast-forwards six years, to a moment when Gordon learned that a customer wanted to buy the old chipset design so they could make a radiation-hardened version to use on satellites. The major semiconductor company liked the sound of that, and asked Gordon to find the backup. "My colleague and I then pieced together what had happened," he wrote. "Being good engineers, we said nothing. We searched through old nightly backup tapes until we found bits and pieces of different steppings of the design database and copied them all to one place, then handed this off to the customer." To this day, Gordon doesn't know if the customer was able to produce a useful chip from the bits of backup he cobbled together. "Did they realize they received bits and pieces of two slightly different databases? Did they care? Was the project canceled before anyone realized it?" "From then on, I was more careful about who I assigned the task of creating restore backups for each design project," he told The Register. "And I kept a record of the emails requesting backups and confirmation that backups had been done." Have you given a job to the wrong person? Or given clients slightly dodgy data? In either case, click here to send email to Who, Me? We would love to tell your tale on a future Monday. ®

A designer named Marcin Wichary has revealed the story of how he freaked out a decent slab of the world’s Firefox-using population with Pac-Man. Wichary has held senior design roles at Figma, Medium, and Google. As he wrote here, in 2010 Google decided to celebrate the 30th anniversary of Pac-Man by changing its logo at Google.com to a playable version of the game. The Google of 2010 could still mention its motto of the time, “Don’t be evil,” without making anyone who heard it guffaw incredulously. The company’s frequent changes to the logo on its homepage – called Google Doodles, and which persist to this day – were still a notable part of net culture. Wichary got the job of building the playable logo, and tweaking Pac-Man to replace its usual maze with a course that instead navigated around the letters GOOGLE. “It was, frankly, a terrifying proposition,” Wichary wrote. “The homepage was then a very important destination, and my job title was only adjacent to ‘software engineer.’ But I started researching the game and recreating it all in HTML and CSS." Google wanted a full Pac-Man experience, including sound, "because so many of Pac-Man’s sounds are beyond iconic: the starting melody, the waka-wakas, the death jingle." Wichary began work before Google sought permission from Pac-Man’s owner Namco, because the search giant was “planning to wow them with a close-to-finished doodle.” “The project was … going really well. I had fun coding the game and we seemed to have fun playing it. Namco eventually got onboard, too,” he wrote. Google liked the game work so much, higher-ups decided it would be a great idea to have it start automatically if visitors to google.com stayed idle for ten seconds. The designer liked that idea. “If there was anything scary about it at the time, it was only the thought of my code getting even more exposure – but I wasn’t worried about distraction, since the homepage was not a destination page you would ever linger on.” What Google didn’t realise was that some people lingered on the home page without ever knowing they were there. Those people used the Firefox browser with an extension called CoolPreviews that let users hover over a link to see a preview of a web page. “The extension would quietly start at the same time Firefox was opened,” Wichary explained. “And it would immediately, in the background, invisibly and unbeknownst to the user, open a website.” That website was Google’s home page, which now featured an auto-playing and version of Pac-Man that CoolPreviews users simply did not expect. Which explained why, not long after setting the Pac-Man doodle live, Google received plenty of praise, but also reports about computers making strange noises due to CoolPreviews invisibly opening the noisy game. “I pushed a patch within hours,” Wichary wrote, explaining that he added a mute button and a requirement to click something to make the game and its noises start. CoolPreviews couldn’t make those clicks, so the phantom Pac-Man sounds went away. “Ironically, I don’t believe we ever heard of normal people being bothered by the autoplay – it seemed that indeed, few people stayed on the homepage for 10 seconds doing absolutely nothing,” Wichary wrote. “The funny thing is that emergency live-patching [the] internet’s at the time most valuable homepage was perhaps the scariest part of that day for me, but that completely went over my sleep-deprived head,” he added. Google changed Wichary’s title after this incident. His post shows an image describing him as “User experience designer. The Michael Bay of doodles.” ®

A designer named Marcin Wichary has revealed the story of how he freaked out a decent slab of the world’s Firefox-using population with Pac-Man. Wichary has held senior design roles at Figma, Medium, and Google. As he wrote here, in 2010 Google decided to celebrate the 30th anniversary of Pac-Man by changing its logo at Google.com to a playable version of the game. The Google of 2010 could still mention its motto of the time, “Don’t be evil,” without making anyone who heard it guffaw incredulously. The company’s frequent changes to the logo on its homepage – called Google Doodles, and which persist to this day – were still a notable part of net culture. Wichary got the job of building the playable logo, and tweaking Pac-Man to replace its usual maze with a course that instead navigated around the letters GOOGLE. “It was, frankly, a terrifying proposition,” Wichary wrote. “The homepage was then a very important destination, and my job title was only adjacent to ‘software engineer.’ But I started researching the game and recreating it all in HTML and CSS." Google wanted a full Pac-Man experience, including sound, "because so many of Pac-Man’s sounds are beyond iconic: the starting melody, the waka-wakas, the death jingle." Wichary began work before Google sought permission from Pac-Man’s owner Namco, because the search giant was “planning to wow them with a close-to-finished doodle.” “The project was … going really well. I had fun coding the game and we seemed to have fun playing it. Namco eventually got onboard, too,” he wrote. Google liked the game work so much, higher-ups decided it would be a great idea to have it start automatically if visitors to google.com stayed idle for ten seconds. The designer liked that idea. “If there was anything scary about it at the time, it was only the thought of my code getting even more exposure – but I wasn’t worried about distraction, since the homepage was not a destination page you would ever linger on.” What Google didn’t realise was that some people lingered on the home page without ever knowing they were there. Those people used the Firefox browser with an extension called CoolPreviews that let users hover over a link to see a preview of a web page. “The extension would quietly start at the same time Firefox was opened,” Wichary explained. “And it would immediately, in the background, invisibly and unbeknownst to the user, open a website.” That website was Google’s home page, which now featured an auto-playing and version of Pac-Man that CoolPreviews users simply did not expect. Which explained why, not long after setting the Pac-Man doodle live, Google received plenty of praise, but also reports about computers making strange noises due to CoolPreviews invisibly opening the noisy game. “I pushed a patch within hours,” Wichary wrote, explaining that he added a mute button and a requirement to click something to make the game and its noises start. CoolPreviews couldn’t make those clicks, so the phantom Pac-Man sounds went away. “Ironically, I don’t believe we ever heard of normal people being bothered by the autoplay – it seemed that indeed, few people stayed on the homepage for 10 seconds doing absolutely nothing,” Wichary wrote. “The funny thing is that emergency live-patching [the] internet’s at the time most valuable homepage was perhaps the scariest part of that day for me, but that completely went over my sleep-deprived head,” he added. Google changed Wichary’s title after this incident. His post shows an image describing him as “User experience designer. The Michael Bay of doodles.” ®

As debate and legal argument continue over the extent to which developers of large language models are entitled to feed the world’s data into their systems without paying for it, India’s government has come up with an idea to regulate and secure the flow of information. India’s motive is to create AI models trained on local data, because it thinks offshore model-makers won’t be motivated to address the nation’s issues or to ensure owners of data stay in control. The scheme India’s Ministry of Electronics and Information Technology (MeitY) thinks can make that happen is called the “Data Empowerment and Protection Architecture (DEPA) for AI Training.” As described by Professor Ajay Kumar Sood, Principal Scientific Adviser to the Government of India, DEPA means “the model travels to the data, rather than the data travelling to the model.” The scheme envisions “Training Data Providers” (TDPs) – examples of which include hospitals, banks, and government agencies – sharing anonymized and encrypted data with a “Data Exchange Platform” (DEP). Entities called “Training Data Consumers” (TDCs) access the data stored at the DEPs to train their models. DEPs will operate what MeitY calls “hardware-based Secure Data Environments” in which “data remains encrypted and isolated even during processing.” They also enforce rules set by TDPs that describe how TDCs can use data. MeitY’s DEPA framework [PDF] says this scheme means “Differential privacy techniques are systematically applied to prevent the model from learning or revealing individual specific information,” adding “All activities inside the secure data environments are immutably logged for audit purposes, ensuring that the process is both secure and transparent.” India’s government already operates several data exchanges, but it is unclear how much work remains to make DEPA a reality. Once DEPA is working, MeitY envisions model-makers will use it to do things like “unlock currently fragmented health data to power breakthroughs in AI-driven diagnostics, drug discovery, and public health management.” The optimism extends to financial services. India is home to literally thousands of banks, and MeitY thinks “DEPA can enable secure sharing of diverse financial data, potentially extending formal credit to 400 million underserved individuals and MSMEs and fueling next-generation fintech innovation.” India’s government has long believed that if financial services companies can lend to more people, it will boost economic development. “Similarly, in Education, DEPA can overcome data interoperability challenges to enable AI-powered personalized learning for millions and create portable skill credentials essential for a future-ready workforce of its 250 million students in a $29 billion EdTech sector,” the framework states. “The successful adoption of DEPA Training across these domains is the essential catalyst for realizing India’s vision of inclusive growth and responsible AI leadership on the global stage.” While the purpose of the framework is to build Indian AIs for Indians, the document also has half an eye on the nation’s international standing. “DEPA is India’s contribution to global science diplomacy, advancing the efforts of institutions such as the World Bank and the United Nations to shape a more inclusive and responsible global AI ecosystem,” the framework states. It also makes several mentions of digital public infrastructure (DPI), an idea pioneered by India that involves government funding creation of tools like the Unified Payments Interface payment systems and the Bharat Taxi zero-commission ride-sharing platform, to ensure Big Tech companies don’t dominate the local market. India also uses its DPI as a diplomatic tool, by giving it away to friendly nations. ®

As debate and legal argument continue over the extent to which developers of large language models are entitled to feed the world’s data into their systems without paying for it, India’s government has come up with an idea to regulate and secure the flow of information. India’s motive is to create AI models trained on local data, because it thinks offshore model-makers won’t be motivated to address the nation’s issues or to ensure owners of data stay in control. The scheme India’s Ministry of Electronics and Information Technology (MeitY) thinks can make that happen is called the “Data Empowerment and Protection Architecture (DEPA) for AI Training.” As described by Professor Ajay Kumar Sood, Principal Scientific Adviser to the Government of India, DEPA means “the model travels to the data, rather than the data travelling to the model.” The scheme envisions “Training Data Providers” (TDPs) – examples of which include hospitals, banks, and government agencies – sharing anonymized and encrypted data with a “Data Exchange Platform” (DEP). Entities called “Training Data Consumers” (TDCs) access the data stored at the DEPs to train their models. DEPs will operate what MeitY calls “hardware-based Secure Data Environments” in which “data remains encrypted and isolated even during processing.” They also enforce rules set by TDPs that describe how TDCs can use data. MeitY’s DEPA framework [PDF] says this scheme means “Differential privacy techniques are systematically applied to prevent the model from learning or revealing individual specific information,” adding “All activities inside the secure data environments are immutably logged for audit purposes, ensuring that the process is both secure and transparent.” India’s government already operates several data exchanges, but it is unclear how much work remains to make DEPA a reality. Once DEPA is working, MeitY envisions model-makers will use it to do things like “unlock currently fragmented health data to power breakthroughs in AI-driven diagnostics, drug discovery, and public health management.” The optimism extends to financial services. India is home to literally thousands of banks, and MeitY thinks “DEPA can enable secure sharing of diverse financial data, potentially extending formal credit to 400 million underserved individuals and MSMEs and fueling next-generation fintech innovation.” India’s government has long believed that if financial services companies can lend to more people, it will boost economic development. “Similarly, in Education, DEPA can overcome data interoperability challenges to enable AI-powered personalized learning for millions and create portable skill credentials essential for a future-ready workforce of its 250 million students in a $29 billion EdTech sector,” the framework states. “The successful adoption of DEPA Training across these domains is the essential catalyst for realizing India’s vision of inclusive growth and responsible AI leadership on the global stage.” While the purpose of the framework is to build Indian AIs for Indians, the document also has half an eye on the nation’s international standing. “DEPA is India’s contribution to global science diplomacy, advancing the efforts of institutions such as the World Bank and the United Nations to shape a more inclusive and responsible global AI ecosystem,” the framework states. It also makes several mentions of digital public infrastructure (DPI), an idea pioneered by India that involves government funding creation of tools like the Unified Payments Interface payment systems and the Bharat Taxi zero-commission ride-sharing platform, to ensure Big Tech companies don’t dominate the local market. India also uses its DPI as a diplomatic tool, by giving it away to friendly nations. ®

As debate and legal argument continue over the extent to which developers of large language models are entitled to feed the world’s data into their systems without paying for it, India’s government has come up with an idea to regulate and secure the flow of information. India’s motive is to create AI models trained on local data, because it thinks offshore model-makers won’t be motivated to address the nation’s issues or to ensure owners of data stay in control. The scheme India’s Ministry of Electronics and Information Technology (MeitY) thinks can make that happen is called the “Data Empowerment and Protection Architecture (DEPA) for AI Training.” As described by Professor Ajay Kumar Sood, Principal Scientific Adviser to the Government of India, DEPA means “the model travels to the data, rather than the data travelling to the model.” The scheme envisions “Training Data Providers” (TDPs) – examples of which include hospitals, banks, and government agencies – sharing anonymized and encrypted data with a “Data Exchange Platform” (DEP). Entities called “Training Data Consumers” (TDCs) access the data stored at the DEPs to train their models. DEPs will operate what MeitY calls “hardware-based Secure Data Environments” in which “data remains encrypted and isolated even during processing.” They also enforce rules set by TDPs that describe how TDCs can use data. MeitY’s DEPA framework [PDF] says this scheme means “Differential privacy techniques are systematically applied to prevent the model from learning or revealing individual specific information,” adding “All activities inside the secure data environments are immutably logged for audit purposes, ensuring that the process is both secure and transparent.” India’s government already operates several data exchanges, but it is unclear how much work remains to make DEPA a reality. Once DEPA is working, MeitY envisions model-makers will use it to do things like “unlock currently fragmented health data to power breakthroughs in AI-driven diagnostics, drug discovery, and public health management.” The optimism extends to financial services. India is home to literally thousands of banks, and MeitY thinks “DEPA can enable secure sharing of diverse financial data, potentially extending formal credit to 400 million underserved individuals and MSMEs and fueling next-generation fintech innovation.” India’s government has long believed that if financial services companies can lend to more people, it will boost economic development. “Similarly, in Education, DEPA can overcome data interoperability challenges to enable AI-powered personalized learning for millions and create portable skill credentials essential for a future-ready workforce of its 250 million students in a $29 billion EdTech sector,” the framework states. “The successful adoption of DEPA Training across these domains is the essential catalyst for realizing India’s vision of inclusive growth and responsible AI leadership on the global stage.” While the purpose of the framework is to build Indian AIs for Indians, the document also has half an eye on the nation’s international standing. “DEPA is India’s contribution to global science diplomacy, advancing the efforts of institutions such as the World Bank and the United Nations to shape a more inclusive and responsible global AI ecosystem,” the framework states. It also makes several mentions of digital public infrastructure (DPI), an idea pioneered by India that involves government funding creation of tools like the Unified Payments Interface payment systems and the Bharat Taxi zero-commission ride-sharing platform, to ensure Big Tech companies don’t dominate the local market. India also uses its DPI as a diplomatic tool, by giving it away to friendly nations. ®

Google has revealed some of its Asian customers – almost certainly Chinese e-tailers – are buying fewer ads. Speaking on Alphabet’s Q3 earnings call last week, chief business officer Philipp Schindler addressed the slowdown in ad sales growth with the following remark: “In retail, some of our APAC advertisers were impacted by the EU eliminating its de minimis exemption.” That’s a reference to the European Union’s changes to import duties, which saw the bloc introduce a temporary €3 customs duty for every consignment valued at under €150 imported from outside the EU. The EU previously operated the de minimis exemption that Schindler referred to, meaning it collected no import duty on almost 5.9 billion low-value items shipped to the continent in 2025 alone. The new regime aims to protect European retailers from cheap imports. A great many of those items came from Chinese e-tail giants – the likes of Temu, Shein, and Alibaba – who are thought to account for perhaps ten percent of advertising revenue at Google and Meta. EU policy has therefore contributed to slower growth at Google. Huawei’s brake pedals reportedly break Huawei’s automotive efforts appear to have driven it into a cul de sac of controversy. The Chinese tech giant works with a company called Anhui Jianghuai Automobile Group Co. (JAC) under the Harmony Intelligent Mobility Alliance, which aims to produce intelligent cars. The flagship model produced by Huawei and JAC is a luxury EV called the Maextro V800, which when tested by Chinese automotive review site Dongchedi produced a rather terrifying fault: the brake pedal bracket broke when drivers exerted maximum force during tests to assess the car's ability to decelerate suddenly at 100 km/h. The site’s drivers were still able to stop the car, but rather more slowly than is optimal. Within days of the review site posting its findings, reports of its work started to disappear from the internet, according to China Digital Times, a US-based outlet that says it publishes independent news on Chinese affairs. Even some opinion pieces that called for further assessment of the car’s safety disappeared, giving rise to theories that Beijing is displeased with negative coverage of its technology champions and automotive industry. North Korea named as Binance hacker The USA’s Federal Bureau of Investigation (FBI) on Saturday named North Korea’s elite cybercrime crew “TraderTraitor” as the source of last week’s attack on cryptocurrency exchange Binance. Cyber-defense company TRM also reached the same conclusion. Its analysts last week declared they have “high confidence” that “on and off-chain intelligence” suggest TraderTraitor did the deed. “On the evening of October 29, billions of dollars in crypto began leaving wallets belonging to Binance,” TRM’s analysts wrote. “Within minutes, Binance wallets on the XRP Ledger, Ethereum, Bitcoin, Tron, Solana and four other networks had sent their balances to addresses controlled by a single attacker. A second wave around 23:05 UTC reached Binance wallets on Avalanche and Polygon.” TRM thinks Trader Traitor started its raid 36 hours before the theft. “The attacker's operator wallet received three small withdrawals from Tornado Cash, a service that obscures where crypto comes from, starting the morning of October 28,” TRM wrote. “Early on October 29, the operator deployed a first piece of code for the attack and tested it on two wallets. Later that day, it rehearsed the final version on a third wallet, then routed the test funds back to itself. Four hours after that rehearsal, the same code was installed on a Binance hot wallet.” Binance first said the cause of the incident was a single compromised laptop. It has since detected “additional points of breach” but has not offered additional information while it investigates the matter. The crypto exchange continues to reassure users that its platform is safe and that it will make good any losses. North Korea steals cryptocurrency to fund its government, especially its belligerent defense efforts. Samsung posts monster profit Samsung last week delivered the monster profits it promised early in October. The Korean giant announced record Q3 revenue of ₩195.3 trillion ($146.2 billion ) and operating profit of ₩107 trillion ($80 billion). Samsung’s DS division, which covers all its chipmaking efforts, earned over 99 percent of that operating profit and $110 billion of the company’s revenue. The company said its foundry business “experienced a notable revenue and earnings improvement on HBM base-die sales growth” and expects it will notch up “double-digit revenue growth and continued earnings improvement on new mobile products, mass production ramp-up of 4nm NPUs, and expanded memory product sales” in its next quarterly report. “In 2027, the Business will aim for revenue growth led by 4nm and 2nm advanced nodes based on strong AI and HPC demand. It also expects to strengthen its global supply capabilities with the commencement of operations at its new fab in Taylor, Texas,” the company said. That last item is welcome news as the reason Samsung and other memory-makers are making so much money is shortages mean they can inflate prices. More factories coming online may help to ease price pressures. Fast-charging batteries set for takeoff Dr Rachid Yazami, the scientist who developed the graphite anode that made lithium-ion batteries mainstream, has shown off a new battery design that can achieve 70 percent charge in under four minutes. In tests of its lithium iron phosphate (LFP) battery cell, Dr Yazami’s startup KVI was able to go from 10 percent to 70 percent charge in 3.7 minutes, and to full charge in seven minutes, using “Non-Linear Voltammetry (NLV)” technology that he says “uses a proprietary, stepwise voltage-controlled approach” that “allows the current to respond to the battery’s changing electrochemical characteristics” during charging. “The challenge is not simply to push more electricity into a battery in less time,” Dr Yazami said. “It is to understand how the battery responds during charging and use that information to deliver energy more effectively.” Japanese company SkyDrive, which hopes to manufacture electric-powered flying vehicles, has signed up to test the tech. ®

Google has revealed some of its Asian customers – almost certainly Chinese e-tailers – are buying fewer ads. Speaking on Alphabet’s Q3 earnings call last week, chief business officer Philipp Schindler addressed the slowdown in ad sales growth with the following remark: “In retail, some of our APAC advertisers were impacted by the EU eliminating its de minimis exemption.” That’s a reference to the European Union’s changes to import duties, which saw the bloc introduce a temporary €3 customs duty for every consignment valued at under €150 imported from outside the EU. The EU previously operated the de minimis exemption that Schindler referred to, meaning it collected no import duty on almost 5.9 billion low-value items shipped to the continent in 2025 alone. The new regime aims to protect European retailers from cheap imports. A great many of those items came from Chinese e-tail giants – the likes of Temu, Shein, and Alibaba – who are thought to account for perhaps ten percent of advertising revenue at Google and Meta. EU policy has therefore contributed to slower growth at Google. Huawei’s brake pedals reportedly break Huawei’s automotive efforts appear to have driven it into a cul de sac of controversy. The Chinese tech giant works with a company called Anhui Jianghuai Automobile Group Co. (JAC) under the Harmony Intelligent Mobility Alliance, which aims to produce intelligent cars. The flagship model produced by Huawei and JAC is a luxury EV called the Maextro V800, which when tested by Chinese automotive review site Dongchedi produced a rather terrifying fault: the brake pedal bracket broke when drivers exerted maximum force during tests to assess the car's ability to decelerate suddenly at 100 km/h. The site’s drivers were still able to stop the car, but rather more slowly than is optimal. Within days of the review site posting its findings, reports of its work started to disappear from the internet, according to China Digital Times, a US-based outlet that says it publishes independent news on Chinese affairs. Even some opinion pieces that called for further assessment of the car’s safety disappeared, giving rise to theories that Beijing is displeased with negative coverage of its technology champions and automotive industry. North Korea named as Binance hacker The USA’s Federal Bureau of Investigation (FBI) on Saturday named North Korea’s elite cybercrime crew “TraderTraitor” as the source of last week’s attack on cryptocurrency exchange Binance. Cyber-defense company TRM also reached the same conclusion. Its analysts last week declared they have “high confidence” that “on and off-chain intelligence” suggest TraderTraitor did the deed. “On the evening of October 29, billions of dollars in crypto began leaving wallets belonging to Binance,” TRM’s analysts wrote. “Within minutes, Binance wallets on the XRP Ledger, Ethereum, Bitcoin, Tron, Solana and four other networks had sent their balances to addresses controlled by a single attacker. A second wave around 23:05 UTC reached Binance wallets on Avalanche and Polygon.” TRM thinks Trader Traitor started its raid 36 hours before the theft. “The attacker's operator wallet received three small withdrawals from Tornado Cash, a service that obscures where crypto comes from, starting the morning of October 28,” TRM wrote. “Early on October 29, the operator deployed a first piece of code for the attack and tested it on two wallets. Later that day, it rehearsed the final version on a third wallet, then routed the test funds back to itself. Four hours after that rehearsal, the same code was installed on a Binance hot wallet.” Binance first said the cause of the incident was a single compromised laptop. It has since detected “additional points of breach” but has not offered additional information while it investigates the matter. The crypto exchange continues to reassure users that its platform is safe and that it will make good any losses. North Korea steals cryptocurrency to fund its government, especially its belligerent defense efforts. Samsung posts monster profit Samsung last week delivered the monster profits it promised early in October. The Korean giant announced record Q3 revenue of ₩195.3 trillion ($146.2 billion ) and operating profit of ₩107 trillion ($80 billion). Samsung’s DS division, which covers all its chipmaking efforts, earned over 99 percent of that operating profit and $110 billion of the company’s revenue. The company said its foundry business “experienced a notable revenue and earnings improvement on HBM base-die sales growth” and expects it will notch up “double-digit revenue growth and continued earnings improvement on new mobile products, mass production ramp-up of 4nm NPUs, and expanded memory product sales” in its next quarterly report. “In 2027, the Business will aim for revenue growth led by 4nm and 2nm advanced nodes based on strong AI and HPC demand. It also expects to strengthen its global supply capabilities with the commencement of operations at its new fab in Taylor, Texas,” the company said. That last item is welcome news as the reason Samsung and other memory-makers are making so much money is shortages mean they can inflate prices. More factories coming online may help to ease price pressures. Fast-charging batteries set for takeoff Dr Rachid Yazami, the scientist who developed the graphite anode that made lithium-ion batteries mainstream, has shown off a new battery design that can achieve 70 percent charge in under four minutes. In tests of its lithium iron phosphate (LFP) battery cell, Dr Yazami’s startup KVI was able to go from 10 percent to 70 percent charge in 3.7 minutes, and to full charge in seven minutes, using “Non-Linear Voltammetry (NLV)” technology that he says “uses a proprietary, stepwise voltage-controlled approach” that “allows the current to respond to the battery’s changing electrochemical characteristics” during charging. “The challenge is not simply to push more electricity into a battery in less time,” Dr Yazami said. “It is to understand how the battery responds during charging and use that information to deliver energy more effectively.” Japanese company SkyDrive, which hopes to manufacture electric-powered flying vehicles, has signed up to test the tech. ®

Linus Torvalds has posted the first release candidate for version 7.4 of the Linux kernel and offered his opinion that the project has found a “much healthier model” for using AI. “This is a *BIG* merge window,” he wrote in his weekly state of the kernel update, as it contains almost 20,000 commits compared to the usual ~15,000 that developers submit for a new cut of the kernel. “I think the reason is the by now obvious one, but I'm actually taking it as a good sign: I'm *much* happier with the flood of AI triggered work going into the merge window than it showing up mainly as extra fixes during the -rc period.” He therefore hopes that the unusually large number of commits “is a sign that the AI fixes are becoming more part of the ‘normal development’ than a flood of fixes that go into the whole stabilization phase.” “I think that's a much healthier model,” he added, before hedging with the observation that “people are expecting 7.4 to be the next LTS [long-term support] release, which is another independent reason why some releases tend larger than others.” “So it may not *just* be the flood of AI patches.” Torvalds also seems not to be completely convinced that all AI submissions are entirely helpful, by describing this release as “Large, and full of fixes for issues found by AI (and more and more the patches have been suggested by AI too, although they often get rewritten).” AMD GPU register offsets and bit masks make up a third of the changes this time around. “We've been here before, and I'm sure we'll see it many times again in the future,” Torvalds wrote. “Just ignore the noise.” The kernel-watchers at Phoronix rate the major inclusions in Linux 7.4 as improved support for processors from AMD, Apple, and Google. Other additions include some handy tweaks to improve security for virtual machines, support for the Raspberry Pi 10-inch monitor and more work to get Linux running happily on Qualcomm’s Snapdragon X2 SoC for PCs. ®

Linus Torvalds has posted the first release candidate for version 7.4 of the Linux kernel and offered his opinion that the project has found a “much healthier model” for using AI. “This is a *BIG* merge window,” he wrote in his weekly state of the kernel update, as it contains almost 20,000 commits compared to the usual ~15,000 that developers submit for a new cut of the kernel. “I think the reason is the by now obvious one, but I'm actually taking it as a good sign: I'm *much* happier with the flood of AI triggered work going into the merge window than it showing up mainly as extra fixes during the -rc period.” He therefore hopes that the unusually large number of commits “is a sign that the AI fixes are becoming more part of the ‘normal development’ than a flood of fixes that go into the whole stabilization phase.” “I think that's a much healthier model,” he added, before hedging with the observation that “people are expecting 7.4 to be the next LTS [long-term support] release, which is another independent reason why some releases tend larger than others.” “So it may not *just* be the flood of AI patches.” Torvalds also seems not to be completely convinced that all AI submissions are entirely helpful, by describing this release as “Large, and full of fixes for issues found by AI (and more and more the patches have been suggested by AI too, although they often get rewritten).” AMD GPU register offsets and bit masks make up a third of the changes this time around. “We've been here before, and I'm sure we'll see it many times again in the future,” Torvalds wrote. “Just ignore the noise.” The kernel-watchers at Phoronix rate the major inclusions in Linux 7.4 as improved support for processors from AMD, Apple, and Google. Other additions include some handy tweaks to improve security for virtual machines, support for the Raspberry Pi 10-inch monitor and more work to get Linux running happily on Qualcomm’s Snapdragon X2 SoC for PCs. ®

No lesser authority than the MIT Technology Review says that the Emacs editor has turned 50 years old. But then, it is biased — Emacs was invented in MIT's AI lab. Simson Garfinkel's article is simply called EMACS turns 50, but the sub-heading explains why it matters more: "How the MIT AI Lab's text editor gave birth to the free software movement." There are multiple timelines and accounts of the origins of Emacs, and it is not a single monolithic application. The name is an abbreviation for "Editing MACroS", and the original editor for which this set of macros was developed was TECO – "Text Editor and COrrector," written by Dan Murphy in 1962. Murphy died earlier this year at the age of 83. The inimitable Jamie Zawinski has an encyclopedic Emacs Timeline – as he mentions at the start, his interest being that he long ago maintained a fork of GNU Emacs, originally called Lucid Emacs. It's still around, under its later name XEmacs. There are a lot of forks and re-implementations of Emacs out there, and we are not going to go into all of them, or this article would become a book – one only interesting to programmer-archeologists (to use a term coined by the late great Vernor Vinge). As for who originally wrote those Editing Macros, though, another history has quotations from several of the people involved: On the Origin of Emacs in 1976. (Note – some of the quotes still contain the | symbols that marked quoted text.) This credits Lisp boffin Guy L. Steele Jr with the original work in 1975, but in it, Steele says: "RMS is responsible for the names 'E' and 'EMACS'. RMS still deserves 99% or 99.9% or 99.99% or 99.999% of the credit for taking a package of TECO macros and turning it into the most powerful editor on the planet." RMS is of course Richard Stallman, and the page also quotes some emails from RMS on October 23 and 31, 1976. Mind you, just a few years after the event, in a 1981 talk now preserved on the GNU website, Stallman said, "I began the development of EMACS in 1974 with an improvement to TECO". Like all the best FOSS, even in its very early stages, it was a collaborative effort – but around late October 1976 is when RMS took over the bulk of the development. Of the many forks of Emacs over its half a century of development, some are still just about hanging on in there. When we looked up the link for XEmacs, we were surprised to see that there was a new release: XEmacs 21.5.37 "lettuce" appeared just last month. And even the forks have forks: in this case, SXEmacs, last updated in 2020. Most of the changes in XEmacs and SXEmacs eventually made their way back upstream to GNU Emacs, which is still in active development, although as The Register reported in 2008, RMS is no longer the primary maintainer. GNU Emacs 31.1 appeared in August. Cards on the metaphorical table: this vulture is not an Emacs user. We have tried. A major influence was one of the Reg FOSS desk's favorite writers, Neal Stephenson, who in 1999 published an essay called In the Beginning… Was the Command Line. (It was later republished as a rather short book, but the text is still online.) In it, he says: "In the GNU/Linux world there are two major text editing programs: the minimalist vi (known in some implementations as elvis) and the maximalist emacs. I use emacs, which might be thought of as a thermonuclear word processor. It was created by Richard Stallman; enough said. It is written in Lisp, which is the only computer language that is beautiful. It is colossal, and yet it only edits straight ASCII text files, which is to say, no fonts, no boldface, no underlining. In other words, the engineer-hours that, in the case of Microsoft Word, were devoted to features like mail merge, and the ability to embed feature-length motion pictures in corporate memoranda, were, in the case of emacs, focused with maniacal intensity on the deceptively simple-seeming problem of editing text. If you are a professional writer–i.e., if someone else is getting paid to worry about how your words are formatted and printed–emacs outshines all other editing software in approximately the same way that the noonday sun does the stars." Emacs is 50-plus-year-old software, and it shows. This is a huge and complicated program: decades ago, the joke was that EMACS stood for "Eight Megs And Constantly Swapping". It is not an easy program to learn. Despite lavish documentation and a built-in tutorial, this is software so old that its terminology predates microprocessors and the personal computer. Its exhaustive manual is 804 pages long, and to pick some trivial examples, its terms for parts of the screen use “frame” to mean what’s now called a window, and “window” to mean what’s now called a pane. In the section on Keys, it discusses the Control and Meta keys. That’s a slight snag: you don’t have a Meta key, and neither do the authors of Emacs. It was a key on the now almost legendarily rare Space Cadet Keyboard, of which the Deskthority keyboard wiki says: “It is known as the holy grail of keyboards.” You can buy a modern replica, the Keymacs keyboard. They are hand-made in the Czech Republic, and depending on exactly what model and specifications you want, they cost from €2,998 for the Lispsaver up to €6,878 for the A624N Space Cadet. In other words, you can have a keyboard with a real Meta key if you want, but it is going to cost you. One of the problems with these historical terms, unfamiliar to anyone who wasn’t already programming in the 1970s, is that meanings drift. In the context of Emacs, "Meta" means Alt, or Opt on Macs. However, KDE also uses the Meta key – but what the KDE documentation calls "Meta" is the Windows key – or Command on Macs. Like most Linux folks, the GNOME documentation calls it the Super key. Names are important. They matter. Who's right, the Emacs folks or the KDE folks? Well, neither: nobody has Meta keys any more. We have Ctrl, Alt, and Cmd/Super/Windows. There have been valiant efforts to modernize Emacs and bring it into line with modern UI and terminology. This vulture tried to learn Aquamacs, which modernized Emacs with a native macOS UI, but sadly it's no longer maintained. Another, which we enjoyed trying, is ErgoEmacs, which changes the key bindings and rearranges the UI into something much more like the IBM Common User Access arrangement, as used in Windows and most Linux desktops. However, it never really caught on and you need to know your way around Emacs to install it and configure it for your regional keyboard layout. So complex is it to configure Emacs that there are multiple pre-configured distributions of Emacs, such as Doom Emacs, or the minimalist Emacs Solo. We wish someone did a "CUA-Macs" config, with ErgoEmacs integrated and able to pick up your existing keyboard config. Come to that, the Gershwin Desktop project that we mentioned along with GhostBSD last year is in active development, and it's based around GNUstep. Maybe its developers could pick up Aquamacs, and adapt it to GNUstep. There is a long history of such Emacs facelifts. One instance is Borland’s Sprint word-processor, one of the selling points of which was that it could emulate the user interfaces of most of the leading MS-DOS word-processors of its day (just before they all converged on IBM CUA). Before Borland acquired it, Sprint was called The Final Word, developed by musical equipment makers Mark of the Unicorn. FinalWord was based on an Emacs clone called MINCE. The Great Rival Another well-known Emacs distribution is Spacemacs, which adapts Emacs to have a more Vi-like user interface. Vi is the other seminal Unix text editor, as the Stephenson quote above mentions. As this article on Origins and the Evolution of Vi & Vim notes, it too dates back to 1976. Indeed, that’s the reason we chose the year in this story: Tilde, a text editor that doesn’t work like it’s 1976. One feature of Tilde we enjoy is that it supports use of the mouse even on the Linux console – which is the headline new feature of GNU Emacs 31.1. Vi is very much alive and well today. GNU Emacs is based on the original source code, but Vi mainly survives as re-implementations. The recreation Stephenson mentions, Elvis, lives on today in the form of nvi. However, by far the best known is Vim, maintained by Bram Moolenaar until his death in 2023. In the grand FOSS forking tradition, it too has forks, including Neovim, as used in Omarchy, and more recently, the AI-free Vim Classic – a new project led by Drew DeVault, who just launched the similarly LLM-free AlpineBSD. ®

No lesser authority than the MIT Technology Review says that the Emacs editor has turned 50 years old. But then, it is biased — Emacs was invented in MIT's AI lab. Simson Garfinkel's article is simply called EMACS turns 50, but the sub-heading explains why it matters more: "How the MIT AI Lab's text editor gave birth to the free software movement." There are multiple timelines and accounts of the origins of Emacs, and it is not a single monolithic application. The name is an abbreviation for "Editing MACroS", and the original editor for which this set of macros was developed was TECO – "Text Editor and COrrector," written by Dan Murphy in 1962. Murphy died earlier this year at the age of 83. The inimitable Jamie Zawinski has an encyclopedic Emacs Timeline – as he mentions at the start, his interest being that he long ago maintained a fork of GNU Emacs, originally called Lucid Emacs. It's still around, under its later name XEmacs. There are a lot of forks and re-implementations of Emacs out there, and we are not going to go into all of them, or this article would become a book – one only interesting to programmer-archeologists (to use a term coined by the late great Vernor Vinge). As for who originally wrote those Editing Macros, though, another history has quotations from several of the people involved: On the Origin of Emacs in 1976. (Note – some of the quotes still contain the | symbols that marked quoted text.) This credits Lisp boffin Guy L. Steele Jr with the original work in 1975, but in it, Steele says: "RMS is responsible for the names 'E' and 'EMACS'. RMS still deserves 99% or 99.9% or 99.99% or 99.999% of the credit for taking a package of TECO macros and turning it into the most powerful editor on the planet." RMS is of course Richard Stallman, and the page also quotes some emails from RMS on October 23 and 31, 1976. Mind you, just a few years after the event, in a 1981 talk now preserved on the GNU website, Stallman said, "I began the development of EMACS in 1974 with an improvement to TECO". Like all the best FOSS, even in its very early stages, it was a collaborative effort – but around late October 1976 is when RMS took over the bulk of the development. Of the many forks of Emacs over its half a century of development, some are still just about hanging on in there. When we looked up the link for XEmacs, we were surprised to see that there was a new release: XEmacs 21.5.37 "lettuce" appeared just last month. And even the forks have forks: in this case, SXEmacs, last updated in 2020. Most of the changes in XEmacs and SXEmacs eventually made their way back upstream to GNU Emacs, which is still in active development, although as The Register reported in 2008, RMS is no longer the primary maintainer. GNU Emacs 31.1 appeared in August. Cards on the metaphorical table: this vulture is not an Emacs user. We have tried. A major influence was one of the Reg FOSS desk's favorite writers, Neal Stephenson, who in 1999 published an essay called In the Beginning… Was the Command Line. (It was later republished as a rather short book, but the text is still online.) In it, he says: "In the GNU/Linux world there are two major text editing programs: the minimalist vi (known in some implementations as elvis) and the maximalist emacs. I use emacs, which might be thought of as a thermonuclear word processor. It was created by Richard Stallman; enough said. It is written in Lisp, which is the only computer language that is beautiful. It is colossal, and yet it only edits straight ASCII text files, which is to say, no fonts, no boldface, no underlining. In other words, the engineer-hours that, in the case of Microsoft Word, were devoted to features like mail merge, and the ability to embed feature-length motion pictures in corporate memoranda, were, in the case of emacs, focused with maniacal intensity on the deceptively simple-seeming problem of editing text. If you are a professional writer–i.e., if someone else is getting paid to worry about how your words are formatted and printed–emacs outshines all other editing software in approximately the same way that the noonday sun does the stars." Emacs is 50-plus-year-old software, and it shows. This is a huge and complicated program: decades ago, the joke was that EMACS stood for "Eight Megs And Constantly Swapping". It is not an easy program to learn. Despite lavish documentation and a built-in tutorial, this is software so old that its terminology predates microprocessors and the personal computer. Its exhaustive manual is 804 pages long, and to pick some trivial examples, its terms for parts of the screen use “frame” to mean what’s now called a window, and “window” to mean what’s now called a pane. In the section on Keys, it discusses the Control and Meta keys. That’s a slight snag: you don’t have a Meta key, and neither do the authors of Emacs. It was a key on the now almost legendarily rare Space Cadet Keyboard, of which the Deskthority keyboard wiki says: “It is known as the holy grail of keyboards.” You can buy a modern replica, the Keymacs keyboard. They are hand-made in the Czech Republic, and depending on exactly what model and specifications you want, they cost from €2,998 for the Lispsaver up to €6,878 for the A624N Space Cadet. In other words, you can have a keyboard with a real Meta key if you want, but it is going to cost you. One of the problems with these historical terms, unfamiliar to anyone who wasn’t already programming in the 1970s, is that meanings drift. In the context of Emacs, "Meta" means Alt, or Opt on Macs. However, KDE also uses the Meta key – but what the KDE documentation calls "Meta" is the Windows key – or Command on Macs. Like most Linux folks, the GNOME documentation calls it the Super key. Names are important. They matter. Who's right, the Emacs folks or the KDE folks? Well, neither: nobody has Meta keys any more. We have Ctrl, Alt, and Cmd/Super/Windows. There have been valiant efforts to modernize Emacs and bring it into line with modern UI and terminology. This vulture tried to learn Aquamacs, which modernized Emacs with a native macOS UI, but sadly it's no longer maintained. Another, which we enjoyed trying, is ErgoEmacs, which changes the key bindings and rearranges the UI into something much more like the IBM Common User Access arrangement, as used in Windows and most Linux desktops. However, it never really caught on and you need to know your way around Emacs to install it and configure it for your regional keyboard layout. So complex is it to configure Emacs that there are multiple pre-configured distributions of Emacs, such as Doom Emacs, or the minimalist Emacs Solo. We wish someone did a "CUA-Macs" config, with ErgoEmacs integrated and able to pick up your existing keyboard config. Come to that, the Gershwin Desktop project that we mentioned along with GhostBSD last year is in active development, and it's based around GNUstep. Maybe its developers could pick up Aquamacs, and adapt it to GNUstep. There is a long history of such Emacs facelifts. One instance is Borland’s Sprint word-processor, one of the selling points of which was that it could emulate the user interfaces of most of the leading MS-DOS word-processors of its day (just before they all converged on IBM CUA). Before Borland acquired it, Sprint was called The Final Word, developed by musical equipment makers Mark of the Unicorn. FinalWord was based on an Emacs clone called MINCE. The Great Rival Another well-known Emacs distribution is Spacemacs, which adapts Emacs to have a more Vi-like user interface. Vi is the other seminal Unix text editor, as the Stephenson quote above mentions. As this article on Origins and the Evolution of Vi & Vim notes, it too dates back to 1976. Indeed, that’s the reason we chose the year in this story: Tilde, a text editor that doesn’t work like it’s 1976. One feature of Tilde we enjoy is that it supports use of the mouse even on the Linux console – which is the headline new feature of GNU Emacs 31.1. Vi is very much alive and well today. GNU Emacs is based on the original source code, but Vi mainly survives as re-implementations. The recreation Stephenson mentions, Elvis, lives on today in the form of nvi. However, by far the best known is Vim, maintained by Bram Moolenaar until his death in 2023. In the grand FOSS forking tradition, it too has forks, including Neovim, as used in Omarchy, and more recently, the AI-free Vim Classic – a new project led by Drew DeVault, who just launched the similarly LLM-free AlpineBSD. ®