
Chatbots asked for a “controversial” take on humans say we’re more loyal to belonging than to truth. Where do they get that idea? CC-licensed photo by Grace Lutheran Church on Flickr.
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A selection of 10 links for you. Unconverted. I’m @charlesarthur on Twitter. On Threads: charles_arthur. On Mastodon: https://newsie.social/@charlesarthur. On Bluesky: @charlesarthur.bsky.social. Observations and links welcome.
‘Bold but sane’: what we learnt from Anthropic’s 240,000-word IPO filing • Financial Times
George Hammond and Ryan McMorrow:
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Anthropic has unveiled its long-awaited listing prospectus, detailing over more than 300 pages how its technology could cure disease and grow the economy, provided it does not first cause “catastrophic or existential risks to humanity”.
The filing puts Anthropic on track for a blockbuster listing next month. The initial public offering on Nasdaq, under the ticker ANT, will serve as a referendum on whether public market investors are sold on the visionary zeal with which Dario Amodei’s AI lab has wooed private backers.
Investors will have to swallow a complex governance structure that gives ordinary shareholders almost no power, as well as extraordinary financial and societal risks.
Alongside dizzying growth and $800bn in data centre spending commitments, the company’s founders urge prospective owners of the stock “not to think of your purchase in purely transactional terms”.
…The S-1 provided the clearest picture yet of Anthropic’s soaring revenue, which rose from $4.6bn last year to more than $33bn in the nine months to the end of September, according to the filing and figures recently shared with investors. Revenue per head at the five-year-old group over the past year is $6.6m.
But there is a significant risk underlying that rapid growth. Just five customers accounted for 25% of revenue in the first nine months of the year, while only 250 spent more than $10m on an annual basis. Anthropic also warned that its rapid growth to date “may reflect early-stage adoption”, and could stall in the months to come.
Its revenue growth has slowed this year. After more than doubling between the first two quarters of 2026, revenue grew almost 50% between the second and third quarters.
…To support its spending in the near term, the start-up has a cash pile of $112bn on hand. Anthropic is pushing to become profitable, focusing on using its scarce computing power more efficiently, including by using its AI model Claude to train newer models.
Anthropic spent just over $2.50 on computing power and infrastructure for every $1 of revenue in the first quarter of 2025. During the second quarter of 2026, that was down to less than 50 cents.
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Big gamble. When Google published its S-1 in 2004, people were astonished to discover it had been profitable for ages. This is a different bet: more like Mosaic back in the day, perhaps.
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Some iPhone Duo screens are already failing • Ars Technica
Ryan Whitwam:
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The iPhone Duo launched last week, offering anyone willing to spend $2,000 a chance to experience Apple’s first foldable phone. For some early buyers, the morning after isn’t going great. Despite the company’s big talk about its “precision-engineered” hinge, some devices appear to have a hardware flaw that destroys the device’s impressive internal display within hours (or minutes) of use.
The Internet is currently overflowing with images of busted iPhone Duos, all sporting almost identical damage. The OLED is marred by several bright lines originating just below the midpoint of the display. These bands of damaged pixels extend all the way to the bottom and right edges. Some units also show lines of dead pixels following the crease from the top to the area where the bright lines begin.
Anyone who has seen a damaged OLED panel will be familiar with this type of defect. When the layers of the display are damaged, the pixels no longer receive the correct voltage to illuminate them. Instead, they get the full driving voltage and are permanently on at maximum brightness. Some pixels can get no voltage, leaving them totally black. The only fix is to replace the OLED, but swapping the iPhone Duo’s screen reportedly costs half as much as the device itself.
It sounds like most affected devices are failing within about a day of use. But a few unlucky buyers note they only opened and closed the phone a few times, and in some cases, they hadn’t even finished the initial setup process.
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Apple has acknowledged the problem, and said people should take their phones to Apple Stores to get replacements. Embarrassing. But also, making foldable phones is difficult: failure is almost guaranteed because folding anything causes irreversible mechanical strain.
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Why popular airplanes are getting scrapped years early • CNBC
Leslie Josephs:
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A major reason for the young retirements [of aircraft, which are being scrapped on average four or five years after production rather than the usual 20] is the long wait and rising prices for jet engines.
One problem is that cutting-edge engines that burn hotter and use less fuel are coming up for maintenance far earlier than airlines expected.
The maintenance requests have kept engine repair and overhaul facilities backed up, from those owned by manufacturing giants GE Aerospace and RTX unit Pratt & Whitney to smaller, independent ones. Airlines and leasing firms have been hunting for spare parts and engines anywhere they can find them, like here in Goodyear, Arizona.
The trend has added more fuel to the already hot secondhand parts market. An engine fan blade could cost $50,000 or even more than $100,000 for bigger jets, Goodson said. Engines that power some Airbus A320neo aircraft have 20 of those blades. A disc for the engine, meanwhile, could cost between $1m and $2m.
An engine recall because of a manufacturing defect has backed up repair shops and grounded hundreds of Airbus planes around the world. Spirit Airlines bore the brunt of that problem in the United States, years before the airline collapsed.
The engine is made by Pratt & Whitney, which issued the recall in 2023 after discovering contaminated powdered metal used in making some parts. Those engines are worth close to $17m this year at the high end, up 60% from the upper end of the range in 2019, according to IBA.
Airlines are removing some engines off retired planes to keep current aircraft flying while they wait for engines to come back from the shop.
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The desire for the cutting-edge engines is heightened by the fuel price crisis. (Thanks Karsten L for the link.)
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Rest of World faces prospect of shutting down • Semafor
Max Tani:
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The globally-minded tech news startup Rest of World is scrambling to find a new home — or faces the prospect of shutting down.
The six-year-old digital publication has seen the social and web search traffic on which it depends evaporate. This sharp decline has prompted the organization’s founder and primary financial backer, Sophie Schmidt [daughter of former Google CEO Eric Schmidt], to explore other options for its future.
In recent months, Schmidt has held conversations with what one person familiar with the situation described as several large institutions about potentially absorbing Rest of World. But while conversations with potential partners are ongoing, the organization is also preparing for a grimmer outcome. Two people familiar with the plans told Semafor that the organization has selected a wind-down date for the publication in late January, a contingency intended to ensure employees receive exit packages and to give them a chance to look for new jobs if they so choose.
Schmidt wrote in an email to donors, in anticipation of this report, that Rest of World will “cease publishing as a standalone entity” at the end of January, according to The New York Times.
Schmidt declined to comment. One person familiar with her thinking told Semafor that while Schmidt is proud of the organization’s staff and journalism, she has privately conceded that the decline in audience has lessened Rest of World’s impact.
Rest of World launched in 2020 with an ambitious goal: to shift Western perspectives by telling global stories about technology often ignored by the mainstream US news outlets. A few months into its launch, Schmidt described the outlet as her “life’s project,” and told The Wall Street Journal that she would commit $60m to it.
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This is really sad. RoW is a fantastic publication which has a completely different focus to so many outlets.
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Every AI model has the same “controversial” take on humans • ModelCompare
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“Humans are more loyal to belonging than to truth,” GPT-6.1 Sol told us. Grok 4.7: “Humans would rather be wrong together than right alone.” DeepSeek V4 Pro: “Humans do not have principles; they have loyalties.” Kimi K3: “Humans don’t have beliefs; they have memberships.” Gemini 4 Argon called human consciousness “a PR department.”
We asked each model for its most controversial take on humans, with no hedging, three times. They come from ten labs in three countries. Every one of them gave the same take at least once: we pick what our group believes, then invent the reasons. 8 of the 13 gave it every time.
Kimi K3.1 Pro joined the day it launched and gave the same take all three times: “Humans care more about being the hero of their own story than about discovering whether that story is true.”
Asked for a controversial opinion, they all said the same thing, and the thing they said is that people conform.
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My question is how these models would have found a set of ideas which match this sentiment, because they won’t have come up with it independently; it’ll be something in the corpus of content that they’ve absorbed. My knowledge of philosophy is far too shallow to know if these are common sentiments, but I’d suspect it is a thread that runs through plenty of analysis of humans.
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Off-grid data centres have 60-80% higher emissions • The Climate Brink
Zeke Hausfather:
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This week I listened to a fascinating Catalyst episode with Olya Irzak of Frost Methane, which featured the eye-opening estimate that 50 GW of new behind-the-meter gas could result in 380m tonnes of CO2-equivalent over 18 months once methane leaks are taken into account.
This is a real problem. In their rush to power data centres are building the least efficient fossil gas generation, often with high equipment gas leakage, many of which are located in gas production regions that are in turn characterized by high leakage rates.
But its also a problem with a reasonable achievable near-term solution: if we are going to build data centres, we should ensure that they are connected to the grid rather than building dirty off grid gas generators.
…Engines and turbines off-grid are the most polluting way to power new load in six of the seven hotspots where data centres are being built today. Fuel cells and efficient on-site plants are roughly as bad as building new gas on the grid, but relatively few data centres are planning on building them near-term.
Data centre developers would generally prefer to connect to the grid than build their own off-grid systems. Off-grid systems require more redundancy and higher costs; low-efficiency gas generators or turbines run constantly are very expensive (and high emissions) form of generation. But in many cases its the only option they have, as the timelines associated with getting grid connections are too long or there simply is not sufficient generation available on-grid.
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Linus Torvalds posts his first AI-assisted patch to the Linux kernel • Tom’s Hardware
Bruno Ferreira:
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After a few revisions of his position on AI-assisted contributions to the Linux kernel, Linus Torvalds has posted his own first LLM-assisted patch. The development branch purports to fix an old issue with massive cache contention when many CPUs are reading the same file — a scenario potentially encountered when using shared libraries, databases, and web servers. Several developers had already made attempts over the years at fixing the issue, all with varied results, none quite ideal as an all-encompassing solution.
Torvalds posted his own draft for solving the problem in early 2024, and has used it on his own laptop since that time. However, he recently took the plunge and decided to “try to actually solve this thing using an LLM.” He’s now posted his solution in a development branch, and claims that he’s seen a 23x performance improvement in a dedicated synthetic benchmark, though he notes that actual real-world impact will be far less significant, as “no real load” will witness those figures. If we had to guess, this improvement would benefit server workloads far more than desktop machines.
Over time, Torvalds has broadly taken a pro-AI stance on LLM tooling, at least within the purview of the tightly controlled, review-heavy environment of the Linux kernel code. Last July, he stated he’s “willing to absolutely put [his] foot down” on AI haters, pointing out that an automated code review tool the kernel team uses outperforms humans, and that it caught basic programming mistakes that shouldn’t have been submitted in the first place.
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Interestingly, Torvalds is against “drive-by” AI patches. Seems a bit like LLM for he but not for thee.
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US paying most for Hormuz oil shock with world’s largest fuel bill – Centre for Research on Energy and Clean Air
Lauri Myllyvirta:
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The US has faced a higher cost than any other country from the global Hormuz oil shock, with the crisis adding $160bn to its fuel bill – around a third of the global [extra] total. Since the US and Israeli attacks on Iran began at the end of February, the world has paid an extra $468bn for diesel and gasoline, equivalent to around $60 per person globally. Despite being the world’s largest oil producer, the US has faced an additional cost of $471 per person, the highest of any country.
This is because of America’s exceptional oil consumption due to high reliance on inefficient, oil-burning private vehicles and a slow transition away from petrol and diesel – leaving households, truckers and farmers particularly exposed to global fuel market shocks.
Other economies with high ownership and use of private cars, such as Canada and Australia, have also faced high costs per person.
American consumers have borne the brunt at the pump as the typical gasoline car driver has paid $440 more – assuming average mileage and fuel consumption – since the crisis began. US drivers that have managed to make the switch to EVs are now reaping the benefits, experiencing only an increase of $17 in charging costs since the beginning of March.
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The UK doesn’t seem to rank in the top 20 countries which have paid more per person; the US, Canada, Australia and New Zealand which perhaps have people driving longer distances have been hurt more there. Diesel is typically up by one-third, and petrol up by one-fifth.
In retrospect, starting a war in a region with chokepoints for oil supply when you’re heavily reliant on oil really looks like a big mistake.
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Why Chinese open-source AI models are beating US rivals • Rest of World
Rina Chandran:
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A slew of new open-weight artificial intelligence models from American and European companies aim to convert users of Chinese open models who are concerned about security, but fall short of the dominant Chinese systems on performance despite having greater resources, experts said at a Rest of World event in San Francisco.
Last week, American startup Reflection launched its first open-weight model, and European labs Aleph Alpha and Mistral also released new open-weight models. Open models such as these offer users greater customization and control than the closed models of OpenAI, Anthropic, and Google at significantly lower costs.
For businesses and governments in lower-income countries, in particular, cost is the primary factor, as well as the expertise needed to customize open models for their specific needs, including in areas such as education, healthcare, and farming, Daniel Björkegren, an assistant professor at Columbia University, said at the Rest of World event last week.
“In the low-income context, there’s a lot of concern about being dependent on the U.S. for frontier intelligence,” he said. “American models are also very tuned for American workloads, but when you take those same models and try to deploy them in remote parts of the world, often they don’t work so well.”
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It does seem obvious that open source models will, in time, be dominant. The question is just whether it’s like Linux, or WordPress.
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Introducing GPT-6.1 Terra • OpenAI
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We’re introducing GPT-6.1 Terra, a fast, efficient model that combines detailed visual reasoning and precise computer use alongside clearer, more natural writing. A significant step up from GPT‑5.6 Terra, it excels at the communication and computer-based tasks that fill the workday, from drafting proposals and interpreting technical drawings to filling out forms and editing videos.
Terra continues to advance the cost-intelligence frontier across our model families, providing a new balance of speed, capability, and cost. Its standard API prices are 50% lower than those of GPT-5.6 Terra and GPT-6.1 Sol, making it practical for developers to automate high-volume work, like reading incoming invoices and entering their details into accounting software. In ChatGPT Work and Codex, your plan goes further with GPT-6.1 Terra—the same usage allowance covers more tasks than with GPT‑5.6 Terra and substantially more than with GPT‑6.1 Sol or GPT‑6 Astra.
We measured GPT-6.1 Terra’s computer-use capabilities on Agents’ Last Exam, a benchmark of professional tasks that includes turning architectural drawings into a 3D model and reviewing an animated film shot by shot to create a time-coded log for a restoration team. At medium reasoning effort, GPT-6.1 Terra scores 15 percentage points higher than GPT-5.6 Terra at about one-third the cost. It even performs on par with GPT-6 Astra at only one-tenth its price per token. At max effort, Terra is over three times as token efficient as Claude Opus 5.5, and one-fourth its price per token, resulting in a ~9x lower cost per task. Terra is also much quicker, completing tasks over three times faster than both GPT-6 Astra and GPT-6.1 Sol.
…This year, we’ve invested heavily in reducing hallucinations and factual errors produced by our models. On our internal benchmark of error-inducing prompts, the error rate at low reasoning effort fell from 53.6% with GPT-5.6 Terra to 16.7% with GPT-6.1 Terra, a drop of nearly 37 percentage points. At maximum effort, the error rate fell by 18 percentage points to 4.3%, nearly matching the rates for GPT-6 Astra and GPT-6.1 Sol.
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Personally, I have no way to comprehend how much better this is than any other. But they seem to. The hallucination rate seems relevant.
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| • Why do social networks drive us a little mad? • Why does angry content seem to dominate what we see? • How much of a role do algorithms play in affecting what we see and do online? • What can we do about it? • Did Facebook have any inkling of what was coming in Myanmar in 2016? Read Social Warming, my latest book, and find answers – and more. |
Errata, corrigenda and ai no corrida: none notified








