An anonymous reader quotes a report from the BBC: Sweeping job cuts at Big Tech companies have become an annual tradition. How executives explain those decisions, however, has changed. Out are buzzwords like efficiency, over-hiring, and too many management layers. Today, all explanations stem from artificial intelligence (AI). In recent weeks, giants including Google, Amazon, Meta, as well as smaller firms such as Pinterest and Atlassian, have all announced or warned of plans to shrink their workforce, pointing to developments in AI that they say are allowing their firms to do more with fewer people. [...] But explaining cuts by pointing to advances in AI sounds better than citing cost pressures or a desire to please shareholders, says tech investor Terrence Rohan, who has had a seat on many company boards. "Pointing to AI makes a better blog post," Rohan says. "Or it at least doesn't make you seem as much the bad guy who just wants to cut people for cost-effectiveness."

That does not mean there is no substance behind the words, Rohan added. Some of the companies he's backing are using code that is 25% to 75% AI-generated. That is a sign of the real threat that AI tools for writing code represent to jobs such as software developer, computer engineer and programmer, posts once considered a near-guarantee of highly paid, stable careers. "Some of it is that the narrative is changing, some of it is that we really are starting to see step changes in productivity," Anne Hoecker, a partner at Bain who leads the consultancy's technology practice, says of the recent job cuts. "Leaders more recently are seeing these tools are good enough that you really can do the same amount of work with fundamentally less people."

There is another way that AI is driving job cuts -- and it has nothing to do with the technical abilities of coding tools and chatbots. Amazon, Meta, Google and Microsoft are collectively planning to pour $650 billion into AI in the coming year. As executives hunt for ways to try to ease investor shock at those costs, many are landing on payroll, typically tech firms' single biggest expense. [...] Although the expense of, for example, 30,000 corporate Amazon employees is dwarfed by that company's AI spending plans, firms of this size will now take any opportunity to cut costs, Rohan says. "They're playing a game of inches," Rohan says of cuts at Big Tech firms. "If you can even slightly tune the machine, that is helpful." Hoecker says cutting jobs also signals to stock market investors worried about the "real and huge" cost of AI development that executives are not blithely writing blank cheques. "It shows some discipline," says Hoecker. "Maybe laying off people isn't going to make much of a dent in that bill, but by creating a little bit of cashflow, it helps."

When Block cut 4,000 jobs — nearly half its workforce — co-founder Jack Dorsey "pointed to AI as the culprit," writes Entrepreneur magazine. "Dorsey claimed that AI tools now allow fewer employees to accomplish the same work."

"But analysts see a different explanation: poor management." Block more than tripled its employee base between 2019 and 2022, growing from 3,835 to 12,430 workers. The company's stock had fallen 40% since early 2025, creating pressure to cut costs. "This is more about the business being bloated for so long than it is about AI," Zachary Gunn, a Financial Technology Partners analyst, told Bloomberg.

The phenomenon has earned a nickname: "AI-washing," where companies use artificial intelligence as cover for traditional cost-cutting. Goldman Sachs economists estimate that AI is eliminating only 5,000 to 10,000 jobs per month across all U.S. sectors, hardly enough to justify Block's massive cuts.
"European Central Bank President Christine Lagarde told lawmakers in Brussels last week that ECB economists are monitoring for signs that AI is causing job losses," reports Bloomberg, "and are 'not yet seeing' the 'waves of redundancies that are feared'..." And "a recent survey of global executives published in the Harvard Business Review found that while AI has been cited as the reason for some layoffs, those cuts are almost entirely anticipatory: executives expect big efficiency gains that have not yet been realized."

Even a former senior Block executive "is questioning whether AI is truly the reason behind the cuts," writes Inc.: In a recent opinion piece for The New York Times, Aaron Zamost, Block's former head of communications, policy, and people, asked whether the layoffs reflect a genuine "new reality in which the work they do might no longer be viable," or whether artificial intelligence is "just a convenient and flashy new cover for typical corporate downsizing." Zamost acknowledged that the answer is unclear and perhaps unknowable, even within Block itself...

Looking more closely at the layoffs, Zamost argued that the specific roles affected suggest more traditional corporate cost-cutting than a sweeping AI transformation... Many of the responsibilities being eliminated, he argued, rely on distinctly human skills that AI systems still cannot replicate. "A chatbot can't meet with the mayor, cast commercial actors, or negotiate with the Securities and Exchange Commission," Zamost wrote. "Not all the roles I've heard that Block is eliminating can be handled by AI, yet executives are treating it as equally useful today to all disciplines."

Ultimately, Zamost suggested that the sincerity of companies' AI explanations may not really matter. "It matters less whether a company knows how to deploy AI and more whether investors believe it is on track to do so," he wrote.
Indeed, whatever the rationale for Dorsey's statement, " Wall Street didn't seem to mind..." Entrepreneur magazine — since Block's stock shot up 15% after the announcement.

"Seagate says it is now shipping its Mozaic 4+ HAMR-based hard drives at up to 44TB per drive," writes Slashdot reader BrianFagioli, "with production deployments already underway at two hyperscale cloud providers.

"The company claims the platform is the only heat-assisted magnetic recording [HAMR] implementation currently operating at scale, and it is targeting a path from today's 4+TB per disk toward 10TB per disk, eventually enabling 100TB-class drives." In a one-exabyte deployment, Seagate estimates Mozaic could improve infrastructure efficiency by roughly 47% compared to standard 30TB drives, cutting both footprint and energy consumption... HAMR uses a tiny laser to heat the disk surface during writes, allowing higher recording density without sacrificing stability. With most major cloud storage providers reportedly qualified on the Mozaic platform, Seagate is positioning spinning disks, not flash, as the long-term answer for cost-effective AI-scale data growth.

"Reservation holders, it's finally time to get ready," writes long-time Slashdot reader AirHog. The EV news site Electrek reports: Aptera Motors, "the little startup that could," announced another important milestone... completing the first example of its flagship solar EV on its validation assembly line in Southern California...

While the validation line at its headquarters remains a low-volume assembly process, its successful operation represents the startup's transition from hand-built validation SEVs to a more structured assembly line process that will be fine-tuned for mass production... With low-volume assembly now being validated, Aptera is starting to publicly utter encouraging terms like "EPA certification" and, better yet, that holy grail of "initial customer deliveries." Before then, however, the Aptera Solar EVs built on this low-volume validation line will be used for testing programs such as thermal validation, brake performance, and "some destructive testing." Aptera shared that its assembly and integration team has grown to become the largest at the startup, "reflecting the beginning of its transition from engineering development to testing and production execution"...

As of March 2026, Aptera says it has over 50,000 reservations totaling over $2 billion in sales if all were to solidify following the launch of a deliverable vehicle.
Clean Technica notes the vehicles' "generous cargo space that comes out to 60% more storage than a Honda Accord and 20% more storage than a Prius, according to the company." "Built with recyclable materials, this eco-friendly vehicle features a lightweight carbon fiber structure and no-welding assembly for maximum cost and production efficiency," Aptera adds. The emphasis on lightweighting supports the goal of engineering a car that can travel on the electricity provided by its onboard solar panels.

The company currently advertises that the vehicle can travel 40 miles on solar power alone, with the battery providing extra juice as needed. Ideally, the car can keep recharging itself with sunlight, further elongating the time between charging sessions... [Its range is up to 1,000 miles with plug-in charging.] The new autocycle could also appeal to drivers who enjoy the challenge of hypermiling, which involves deploying a suite of driving techniques to minimize fuel consumption. Hypermiling can apply to gas-powered cars, but the magic really kicks in with the regenerative braking capability of EVs. Aptera's onboard solar panels add another dimension to the fun.

OpenAI CEO Sam Altman is pushing back on growing concerns about AI's environmental footprint, dismissing claims about ChatGPT's water consumption as "totally fake" and arguing that the fairer way to measure AI's energy use is to compare it against humans.

In an interview with Indian Express, Altman acknowledged that evaporative cooling in data centers once made water usage a real concern but said that is no longer the case, calling internet claims of 17 gallons of water per query "completely untrue, totally insane, no connection to reality."

On energy, he conceded it is "fair" to worry about total consumption given how heavily the world now relies on AI, and called for a rapid shift toward nuclear, wind and solar power. He took particular issue with comparisons that pit the cost of training a model against a single human inference, noting it "takes like 20 years of life and all of the food you eat" before a person gets smart -- and that on a per-query basis, AI has "probably already caught up on an energy efficiency basis."

Researchers at the Thomas Jefferson National Accelerator Facility are advancing Accelerator-Driven Systems (ADS) that use high-energy proton beams to transmute long-lived nuclear waste into shorter-lived isotopes. "The process also generates significant heat, which can be harnessed to produce additional electricity for the grid," reports Interesting Engineering. The projects are supported by $8.17 million in grants from the Department of Energy's NEWTON (Nuclear Energy Waste Transmutation Optimized Now) program. From the report: The researchers are developing ADS technology. This system uses a particle accelerator to fire high-energy protons at a target (such as liquid mercury), triggering a process called "spallation." This releases a flood of neutrons that interact with unwanted, long-lived isotopes in nuclear waste. The technology can effectively "burn" the most hazardous components of the waste by transmuting these elements. While unprocessed fuel remains dangerous for approximately 100,000 years, partitioning and recycling via ADS can reduce that window to just 300 years. [...]

To make ADS economically viability, Jefferson Lab is tackling two primary technical hurdles: efficiency and power. Traditional particle accelerators require massive, expensive cryogenic cooling systems to reach superconducting temperatures. Jefferson Lab is pioneering a more cost-effective approach by coating the interior of pure niobium cavities with tin. These niobium-tin cavities can operate at higher temperatures, allowing for the use of standard commercial cooling units rather than custom, large-scale cryogenic plants. The team is also developing spoke cavities, which is a complex design intended to drive even higher efficiency in neutron spallation.

The second project focuses on the power source behind the beam. Researchers are adapting the magnetron -- the same component that powers microwave ovens -- to provide the 10 megawatts of power required for ADS. The primary challenge is that the energy frequency must match the accelerator cavity precisely at 805 Megahertz. In collaboration with Stellant Systems, researchers are prototyping advanced magnetrons that can be combined to reach the necessary high-power thresholds with maximum efficiency. The NEWTON program aims to enable the recycling of the entire US commercial nuclear fuel stockpile within the next 30 years.

The Detroit Big Three -- General Motors, Ford and Stellantis -- have collectively announced more than $50 billion in write-downs on their electric-vehicle businesses after years of aggressive investment into a transition that, even before Republican lawmakers abolished a $7,500 federal tax credit last fall, was already running below expectations.

U.S. EV sales fell more than 30% in the fourth quarter of 2025 once the credit expired in September, and Congress also eliminated federal fuel-efficiency mandates. More than $20 billion in previously announced investments in EV and battery facilities were canceled last year -- the first net annual decrease in years, according to Atlas Public Policy.

GM has laid off thousands of workers and is converting plants once earmarked for EV trucks and motors to produce gas-powered trucks and V-8 engines. Ford dissolved a joint venture with a South Korean conglomerate to make batteries and now plans to build just one low-cost electric pickup by 2027. Stellantis is unloading its stake in a battery-making business after booking the largest EV-related charge of any automaker so far. Outside the U.S., the trajectory looks different: China's BYD recently overtook Tesla as the world's largest EV seller.

Can Aircela's machine "create gasoline using little more than electricity and the air that we breathe"? Jalopnik reports... The Aircela machine works through a three-step process. It captures carbon dioxide directly from the air... The machine also traps water vapor, and uses electrolysis to break water down into hydrogen and oxygen... The oxygen is released, leaving hydrogen and carbon dioxide, the building blocks of hydrocarbons. This mixture then undergoes a process known as direct hydrogenation of carbon dioxide to methanol, as documented in scientific papers.

Methanol is a useful, though dangerous, racing fuel, but the engine under your hood won't run on it, so it must be converted to gasoline. ExxonMobil has been studying the process of doing exactly that since at least the 1970s. It's another well-established process, and the final step the Aircela machine performs before dispensing it through a built-in ordinary gas pump. So while creating gasoline out of thin air sounds like something only a wizard alchemist in Dungeons & Dragons can do, each step of this process is grounded in science, and combining the steps in this manner means it can, and does, really work.

Aircela does not, however, promise free gasoline for all. There are some limitations to this process. A machine the size of Aircela's produces just one gallon of gas per day... The machine can store up to 17 gallons, according to Popular Science, so if you don't drive very much, you can fill up your tank, eventually... While the Aircela website does not list a price for the machine, The Autopian reports it's targeting a price between $15,000 and $20,000, with hopes of dropping the price once mass production begins. While certainly less expensive than a traditional gas station, it's still a bit of an investment to begin producing your own fuel. If you live or work out in the middle of nowhere, however, it could be close to or less than the cost of bringing gas to you, or driving all your vehicles into a distant town to fill up. You're also not limited to buying just one machine, as the system is designed to scale up to produce as much fuel as you need.

The main reason why this process isn't "something for nothing" is that it takes twice as much electrical energy to produce energy in the form of gasoline. As Aircela told The Autopian " Aircela is targeting >50% end to end power efficiency. Since there is about 37kWh of energy in a gallon of gasoline we will require about 75kWh to make it. When we power our machines with standalone, off-grid, photovoltaic panels this will correspond to less than $1.50/gallon in energy cost."
Thanks to long-time Slashdot reader Quasar1999 for sharing the news.

Companies are spending vast sums on AI expecting the technology to boost efficiency, but a new survey from AI consulting firm Section found that two-thirds of non-management workers among 5,000 white-collar respondents say they save less than two hours a week or no time at all, while more than 40% of executives report the technology saves them upward of eight hours weekly.

Workers were far more likely to describe themselves as anxious or overwhelmed about AI than excited -- the opposite of C-suite respondents -- and 40% of all surveyed said they would be fine never using AI again. A separate Workday report of roughly 1,600 employees found that though 85% reported time savings of one to seven hours weekly, much of it was offset by correcting errors and reworking AI-generated content -- what the company called an "AI tax" on productivity.

At the World Economic Forum in Davos this week, a PricewaterhouseCoopers survey of nearly 4,500 CEOs found more than half have seen no significant financial benefit from AI so far, and only 12% said the technology has delivered both cost and revenue gains.

Energy costs will be key to deciding which country wins the AI race, Microsoft CEO Satya Nadella has said. CNBC: As countries race to build AI infrastructure to capitalize on the technology's promise of huge efficiency gains, Nadella told the World Economic Forum (WEF) on Tuesday that "GDP growth in any place will be directly correlated" to the cost of energy in using AI.

He pointed to a new global commodity in "tokens" -- basic units of processing that are bought by users of AI models, allowing them to run tasks. "The job of every economy and every firm in the economy is to translate these tokens into economic growth, then if you have a cheaper commodity, it's better."

"I would say we will quickly lose even the social permission to actually take something like energy, which is a scarce resource, and use it to generate these tokens, if these tokens are not improving health outcomes, education outcomes, public sector efficiency, private sector competitiveness across all sectors," Nadella said.

An anonymous reader quotes a report from Network World: The global technology sector eliminated some 244,851 jobs in 2025, according to a report from RationalFX. The U.K.-based financial services company says the worldwide downsizing reflects how companies in 2025 restructured their operations to focus on efficiency, profitability, and AI-driven productivity. The RationalFX analysis, which examined layoffs reported by TrueUp, TechCrunch, and multiple state WARN databases, points to economic uncertainty, elevated interest rates, and accelerating AI and automation adoption as reasons that 2025 marked "another year of sustained downsizing following the post-pandemic correction that began in 2022."

Companies indicated that AI and automation were among the most frequently cited drivers for layoffs in 2025. Some companies retrained employees when faced with the technology; many replaced roles entirely, RationalFX reports. "Tech sector layoffs in 2025 displaced hundreds of thousands of workers worldwide as companies accelerated structural resets rather than short-term cost corrections," said Alan Cohen, analyst at RationalFX, in a statement. "While macroeconomic pressures such as high interest rates, trade restrictions, and geopolitical uncertainty continued to weigh on business confidence, the dominant force behind last year's job cuts was the rapid adoption of automation and artificial intelligence."

The analysis also uncovered that U.S.-headquartered technology companies were responsible for the majority of job losses, accounting for approximately 69.7% of all global tech layoffs. This resulted in more than 170,000 employees being cut across both domestic and offshore operations from U.S. tech companies. California spearheaded layoffs in the U.S. tech sector this year, with 73,499 job cuts accounting for roughly 43.08% of all tech layoffs in the country, according to the RationalFX report. The report also points out that Washington has seen 42,221 tech jobs cut since the start of the year, accounting for 24.74% of all U.S. tech layoffs. Intel contributed the single largest number of layoffs last year, reducing its headcount from 109,000 people at the end of 2024 to around 75,000 by the end of 2025. Other major U.S. tech companies with large-scale layoffs last year include Amazon (more than 20,000 jobs cut), Microsoft (approximately 19,215 layoffs), Verizon (15,000 employees), Accenture (11,000 employees), IBM (9,000 job cuts), and HP (6,000 roles).

"China recently placed a supercritical carbon dioxide power generator into commercial operation," writes CleanTechnica, "and the announcement was widely framed as a technological breakthrough." The system, referred to as Chaotan One, is installed at a steel plant in Guizhou province in mountainous southwest China and is designed to recover industrial waste heat and convert it into electricity. Each unit is reported to be rated at roughly 15 MW, with public statements describing configurations totaling around 30 MW. Claimed efficiency improvements range from 20% to more than 30% higher heat to power conversion compared with conventional steam based waste heat recovery systems. These are big numbers, typical of claims for this type of generator, and they deserve serious attention.

China doing something first, however, has never been a reliable indicator that the thing will prove durable, economic, or widely replicable. China is large enough to try almost everything. It routinely builds first of a kind systems precisely because it can afford to learn by doing, discarding what does not work and scaling what does. This approach is often described inside China as crossing the river by feeling for stones. It produces valuable learning, but it also produces many dead ends. The question raised by the supercritical CO2 deployment is not whether China is capable of building it, but whether the technology is likely to hold up under real operating conditions for long enough to justify broad adoption.

A more skeptical reading is warranted because Western advocates of specific technologies routinely point to China's limited deployments as evidence that their preferred technologies are viable, when the scale of those deployments actually argues the opposite. China has built a single small modular reactor and a single experimental molten salt reactor, not fleets of them, despite having the capital, supply chains, and regulatory capacity to do so if they made economic sense... If small modular reactors or hydrogen transportation actually worked at scale and cost, China would already be building many more of them, and the fact that it is not should be taken seriously rather than pointing to very small numbers of trials compared to China's very large denominators...

What is notably absent from publicly available information is detailed disclosure of materials, operating margins, impurity controls, and maintenance assumptions. This is not unusual for early commercial deployments in China. It does mean that external observers cannot independently assess long term durability claims.
The article notes America's Energy Department funded a carbon dioxide turbine in Texas rated at roughly 10 MW electric that "reached initial power generation in 2024 after several years of construction and commissioning." But for both these efforts, the article warns that "early efficiency claims should be treated as provisional. A system that starts at 15 MW and delivers 13 MW after several years with rising maintenance costs is not a breakthrough. It is an expensive way to recover waste heat compared with mature steam based alternatives that already operate for decades with predictable degradation..."

"If both the Chinese and U.S. installations run for five years without significant reductions in performance and without high maintenance costs, I will be surprised. In that case, it would be worth revisiting this assessment and potentially changing my mind."

Thanks to long-time Slashdot reader cusco for sharing the article.

Israel has operationally deployed Iron Beam, a 100,000-watt laser air-defense system capable of shooting down drones, rockets, and mortars at negligible per-shot cost. According to Tom's Hardware, it marks the first real-world deployment of a high-energy laser as part of a modern, multi-layered missile defense network. From the report: The Iron Beam is a short-range line-of-sight laser interceptor that is extremely cheap to run and, therefore, perfectly suited for intercepting low-cost, high-volume threats. According to the official Israeli announcement, Iron Beam systems have "successfully intercepted rockets, mortars, and UAVs."

A complex mix of government, military, scientific, and commercial interests were responsible for the research and development of the Iron Beam laser system. Central to the Iron Beam are "an advanced laser source and a unique electro-optical targeting system, enabling the interception of a wide range of targets at an enhanced operational range, with maximum precision and superior efficiency," boasted the press release by Israel's MoD. Moreover, it works "at a negligible marginal cost, which constitutes the laser system's primary advantage."

We don't get much more by way of technical details, perhaps understandably. However, Rafael Advanced Defense Systems execs heralded the system's "unique adaptive optics technology," in what it calls "the world's most advanced laser-based system for intercepting aerial threats." Its operational debut "marks the beginning of the era of high-energy laser defense," they claimed.

The global airline industry is on track to post an all-time profit high of nearly $40 billion in 2025, according to trade group IATA, surpassing the pre-pandemic 2019 figure of $26 billion, but carriers are still managing a net margin of just 4% -- roughly $7.90 per passenger. Economist adds: Not everything has been in the ascent. European and North American airlines, which account for three-fifths of the industry's net profits, have had to contend with circuitous long-haul routes to avoid Russian airspace since the start of the war in Ukraine. This year parts of the Middle East became no-go zones after Israel's strike on Iran in June. America's airlines were hit by a government shutdown that stopped federal workers from travelling and kept unpaid air-traffic controllers at home, disrupting flights.

What is more, despite a drop in fuel prices, which account for 25-30% of airlines' operating expenses, other costs have risen. Airlines flew 4.8 billion passengers in 2024, beating the 2019 peak, and that figure likely reached 5 billion in 2025 as combined revenues topped $1 trillion for the first time and load factors hit a record of nearly 84%.

But the industry is flying older planes because Boeing and Airbus can't deliver enough new ones. The duopoly shipped under 1,400 aircraft in 2025, well below the 2018 record of just over 1,600. Boeing has struggled since two fatal 737 MAX crashes in late 2018 and early 2019 led to a 20-month grounding, and a fuselage panel blew off another 737 MAX mid-flight in early 2024. Airbus cut its 2025 delivery target from 820 to 790 in early December due to a supplier's production flaw, and Pratt & Whitney engine problems have grounded a third of the global A320neo fleet.

IATA estimates the aircraft shortage won't resolve before 2031 at the earliest, and the global fleet's average age has climbed to 15 years from 13 in 2019. Annual fuel efficiency gains have slowed from about 2% to 0.3% in 2025, and an IATA and Oliver Wyman report pegs the cost of aging fleets -- extra fuel, repairs, spare parts -- at over $11 billion in 2025.

Goldman Sachs analysts have identified a notable shift in how investors respond to corporate layoff announcements, finding that even job cuts attributed to automation and AI-driven restructuring are now causing stock prices to fall rather than rise. The investment bank linked recent layoff announcements to public companies' earnings reports and stock market data, concluding that stocks dropped by an average of 2% following such announcements, and companies citing restructurings faced even harsher punishment.

The traditional Wall Street playbook held that layoffs tied to strategic restructuring would boost stock prices, while cuts driven by declining sales would hurt them. That distinction appears to have collapsed.

Goldman's analysts suggest investors simply don't believe what companies are saying -- firms announcing layoffs have experienced higher capex, debt and interest expense growth alongside lower profit growth compared to industry peers this year. The real driver, analysts suspect, may be cost reduction to offset rising interest expenses and declining profitability rather than any forward-looking efficiency play.

Goldman expects layoffs to keep rising, motivated in part by companies' stated desire to use AI to reduce labor costs.

An anonymous reader shares a report: It's been more than eight years since Amazon bought Whole Foods, but the two companies still haven't aligned their setup for the Microsoft software their employees use. That disconnect was flagged in an 8-week Deloitte review of Whole Foods' use of Microsoft 365 apps earlier this year, according to an internal document obtained by Business Insider. Deloitte found that Whole Foods relies on "fragmented" Microsoft toolsets, has loose security and data-retention practices, and employs a complex user-management setup -- all of which contribute to inefficiencies and lower productivity when working with Amazon employees.

The consulting firm recommended a 24-month integration plan that would first move Whole Foods' corporate employees onto Amazon's backend system, followed by its frontline workers. The phased approach would ensure a "smooth transition for users and minimal disruption to business processes," while generating cost savings, the document said. The review, completed in May, highlights Amazon's ongoing challenges in integrating Whole Foods. Since acquiring the chain in 2017, the company has struggled to scale the business and integrate operations, resulting in frequent reorganizations and shifting strategic priorities.

One developer tells MIT Technology Review that AI tools weaken the coding instincts he used to have. And beyond that, "It's just not fun sitting there with my work being done for me."

But is AI making coders faster? "After speaking to more than 30 developers, technology executives, analysts, and researchers, MIT Technology Review found that the picture is not as straightforward as it might seem..." For some developers on the front lines, initial enthusiasm is waning as they bump up against the technology's limitations. And as a growing body of research suggests that the claimed productivity gains may be illusory, some are questioning whether the emperor is wearing any clothes.... Data from the developer analytics firm GitClear shows that most engineers are producing roughly 10% more durable code — code that isn't deleted or rewritten within weeks — since 2022, likely thanks to AI. But that gain has come with sharp declines in several measures of code quality. Stack Overflow's survey also found trust and positive sentiment toward AI tools falling significantly for the first time. And most provocatively, a July study by the nonprofit research organization Model Evaluation & Threat Research (METR) showed that while experienced developers believed AI made them 20% faster, objective tests showed they were actually 19% slower...

Developers interviewed by MIT Technology Review generally agree on where AI tools excel: producing "boilerplate code" (reusable chunks of code repeated in multiple places with little modification), writing tests, fixing bugs, and explaining unfamiliar code to new developers. Several noted that AI helps overcome the "blank page problem" by offering an imperfect first stab to get a developer's creative juices flowing. It can also let nontechnical colleagues quickly prototype software features, easing the load on already overworked engineers. These tasks can be tedious, and developers are typically glad to hand them off. But they represent only a small part of an experienced engineer's workload. For the more complex problems where engineers really earn their bread, many developers told MIT Technology Review, the tools face significant hurdles...

The models also just get things wrong. Like all LLMs, coding models are prone to "hallucinating" — it's an issue built into how they work. But because the code they output looks so polished, errors can be difficult to detect, says James Liu, director of software engineering at the advertising technology company Mediaocean. Put all these flaws together, and using these tools can feel a lot like pulling a lever on a one-armed bandit. "Some projects you get a 20x improvement in terms of speed or efficiency," says Liu. "On other things, it just falls flat on its face, and you spend all this time trying to coax it into granting you the wish that you wanted and it's just not going to..." There are also more specific security concerns, she says. Researchers have discovered a worrying class of hallucinations where models reference nonexistent software packages in their code. Attackers can exploit this by creating packages with those names that harbor vulnerabilities, which the model or developer may then unwittingly incorporate into software.
Other key points from the article:

• LLMs can only hold limited amounts of information in context windows, so "they struggle to parse large code bases and are prone to forgetting what they're doing on longer tasks."

• "While an LLM-generated response to a problem may work in isolation, software is made up of hundreds of interconnected modules. If these aren't built with consideration for other parts of the software, it can quickly lead to a tangled, inconsistent code base that's hard for humans to parse and, more important, to maintain."

• "Accumulating technical debt is inevitable in most projects, but AI tools make it much easier for time-pressured engineers to cut corners, says GitClear's Harding. And GitClear's data suggests this is happening at scale..."

• "As models improve, the code they produce is becoming increasingly verbose and complex, says Tariq Shaukat, CEO of Sonar, which makes tools for checking code quality. This is driving down the number of obvious bugs and security vulnerabilities, he says, but at the cost of increasing the number of 'code smells' — harder-to-pinpoint flaws that lead to maintenance problems and technical debt."

Yet the article cites a recent Stanford University study that found employment among software developers aged 22 to 25 dropped nearly 20% between 2022 and 2025, "coinciding with the rise of AI-powered coding tools."

The story is part of MIT Technology Review's new Hype Correction series of articles about AI.

Longtime Slashdot reader ukoda shares a report from the Associated Press: China is replacing its diesel trucks with electric models faster than expected, potentially reshaping global fuel demand and the future of heavy transport. In 2020, nearly all new trucks in China ran on diesel. By the first half of 2025, battery-powered trucks accounted for 22% of new heavy truck sales, up from 9.2% in the same period in 2024, according to Commercial Vehicle World, a Beijing-based trucking data provider. The British research firm BMI forecasts electric trucks will reach nearly 46% of new sales this year and 60% next year.

China's trucking fleet, the world's second-largest after the U.S., still mainly runs on diesel, but the landscape is shifting. Transport fuel demand is plateauing, according to the International Energy Agency and diesel use in China could decline faster than many expect, said Christopher Doleman, an analyst at the Institute for Energy Economics and Financial Analysis. Electric trucks now outsell LNG models in China, so its demand for fossil fuels could fall, and "in other countries, it might never take off," he said. [...]

The share of electrics in new truck sales, from 8% in 2024 to 28% by August 2025, has more than tripled as prices have fallen. Electric trucks outsold LNG-powered vehicles in China for five consecutive months this year, according to Commercial Vehicle World. While electric trucks are two to three times more expensive than diesel ones and cost roughly 18% more than LNG trucks, their higher energy efficiency and lower costs can save owners an estimated 10% to 26% over the vehicle's lifetime, according to research by Chinese scientists. "When it comes to heavy trucks, the fleet owners in China are very bottom-line driven," Doleman said.

Android's security team published a blog post this week about their experience using Rust. Its title? "Move fast and fix things." Last year, we wrote about why a memory safety strategy that focuses on vulnerability prevention in new code quickly yields durable and compounding gains. This year we look at how this approach isn't just fixing things, but helping us move faster.

The 2025 data continues to validate the approach, with memory safety vulnerabilities falling below 20% of total vulnerabilities for the first time. We adopted Rust for its security and are seeing a 1000x reduction in memory safety vulnerability density compared to Android's C and C++ code. But the biggest surprise was Rust's impact on software delivery. With Rust changes having a 4x lower rollback rate and spending 25% less time in code review, the safer path is now also the faster one... Data shows that Rust code requires fewer revisions. This trend has been consistent since 2023. Rust changes of a similar size need about 20% fewer revisions than their C++ counterparts... In a self-reported survey from 2022, Google software engineers reported that Rust is both easier to review and more likely to be correct. The hard data on rollback rates and review times validates those impressions.

Historically, security improvements often came at a cost. More security meant more process, slower performance, or delayed features, forcing trade-offs between security and other product goals. The shift to Rust is different: we are significantly improving security and key development efficiency and product stability metrics.

With Rust support now mature for building Android system services and libraries, we are focused on bringing its security and productivity advantages elsewhere. Android's 6.12 Linux kernel is our first kernel with Rust support enabled and our first production Rust driver. More exciting projects are underway, such as our ongoing collaboration with Arm and Collabora on a Rust-based kernel-mode GPU driver. [They've also been deploying Rust in firmware for years, and Rust "is ensuring memory safety from the ground up in several security-critical Google applications," including Chromium's parsers for PNG, JSON, and web fonts.]
2025 was the first year more lines of Rust code were added to Android than lines of C++ code...

Amazon CEO Andy Jassy says the company's latest big round of layoffs -- about 14,000 corporate jobs -- wasn't triggered by financial strain or AI replacing workers, but rather a push to stay nimble. From a report: Speaking with analysts on Amazon's quarterly earnings call Thursday, Jassy said the decision stemmed from a belief that the company had grown too big and too layered. "The announcement that we made a few days ago was not really financially driven, and it's not even really AI-driven -- not right now, at least," he said. "Really, it's culture."

Jassy's comments are his first public explanation of the layoffs, which reportedly could ultimately total as many as 30,000 people -- and would be the largest workforce reduction in Amazon's history. The news this week prompted speculation that the cuts were tied to automation or AI-related restructuring. Earlier this year, Jassy wrote in a memo to employees that he expected Amazon's total corporate workforce to shrink over time due to efficiency gains from AI. But his comments Thursday framed the layoffs as a cultural reset aimed at keeping the company fast-moving amid what he called "the technology transformation happening right now."