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report:-apple-inches-closer-to-releasing-an-oled-touchscreen-macbook-pro

Report: Apple inches closer to releasing an OLED touchscreen MacBook Pro

At multiple points over many years, Apple executives have taken great pains to point out that they think touchscreen Macs are a silly idea. But it remains one of those persistent Mac rumors that crops up over and over again every couple of years, from sources that are reliable enough that they shouldn’t be dismissed out of hand.

Today’s contribution comes from supply chain analyst Ming Chi-Kuo, who usually has some insight into what Apple is testing and manufacturing. Kuo says that touchscreen MacBook Pros are “expected to enter mass production by late 2026,” and that the devices will also shift to using OLED display panels instead of the Mini LED panels on current-generation MacBook Pros.

Kuo says that Apple’s interest in touchscreen Macs comes from “long-term observation of iPad user behavior.” Apple’s tablet hardware launches in the last few years have also included keyboard and touchpad accessories, and this year’s iPadOS 26 update in particular has helped to blur the line between the touch-first iPad and the keyboard-and-pointer-first Mac. In other words, Apple has already acknowledged that both kinds of input can be useful when combined in the same device; taking that same jump on the Mac feels like a natural continuation of work Apple is already doing.

Touchscreens became much more common on Windows PCs starting in 2012 when Windows 8 was released, itself a response to Apple’s introduction of the iPad a couple of years before. Microsoft backed off on almost all of Windows 8’s design decisions in the following years after the dramatic UI shift proved unpopular with traditional mouse-and-keyboard users, but touchscreen PCs like Microsoft’s Surface lineup have persisted even as the software has changed.

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new-amelia-earhart-bio-delves-into-her-unconventional-marriage

New Amelia Earhart bio delves into her unconventional marriage


more than a marriage of convenience

Author Laurie Gwen Shapiro chats with Ars about her latest book, The Aviator and the Showman.

Amelia Earhart. Credit: Public domain

Famed aviator Amelia Earhart has captured our imaginations for nearly a century, particularly her disappearance in 1937 during an attempt to become the first female pilot to circumnavigate the globe. Earhart was a complicated woman, highly skilled as a pilot yet with a tendency toward carelessness. And her marriage to a flamboyant publisher with a flair for marketing may have encouraged that carelessness and contributed to her untimely demise, according to a fascinating new book, The Aviator and the Showman: Amelia Earhart, George Putnam, and the Marriage that Made an American Icon.

Author Laurie Gwen Shapiro is a longtime Earhart fan. A documentary filmmaker and journalist, she first read about Earhart in a short biography distributed by Scholastic Books. “I got a little obsessed with her when I was younger,” Shapiro told Ars. The fascination faded as she got older and launched her own career. But she rediscovered her passion for Earhart while writing her 2018 book, The Stowaway, about a young man who stowed away on Admiral Richard Byrd‘s first voyage to Antarctica. The marketing mastermind behind the boy’s journey and his subsequent (ghost-written) memoir was publisher George Palmer Putnam, Earhart’s eventual husband.

The fact that Earhart started out as Putnam’s mistress contradicted Shapiro’s early squeaky-clean image of Earhart and drove her to delve deeper into the life of this extraordinary woman. “I was less interested in how she died than how she lived,” said Shapiro. “Was she a good pilot? Was she a good, kind person? Was this a real marriage? The mystery of Amelia Earhart is not how she died, but how she lived.”

There have been numerous Earhart biographies, but Shapiro accessed some relatively new source material, most notably a good 200 hours of tapes that had become available via the Smithsonian’s Amelia Earhart Project, including interviews with Earhart’s sister, Muriel. “I took an extra six months on my book just so that I could listen to all of them,” said Shapiro. She also scoured archival material at the University of New Hampshire concerning Putnam’s close associate, Hilton Railey; at Purdue University; and at Harvard’s Radcliffe Institute, along with numerous in-person interviews—including several with authors of prior Earhart biographies.

Shapiro’s breezy account of Earhart’s early life includes a few new details, particularly about the aviator’s relationship with an early benefactor (Shapiro calls him Earhart’s “sugar daddy”) in California: a 63-year-old billboard magnate named Thomas Humphrey Bennett Varney. Varney wanted to marry her, but she ended up accepting the proposal of a young chemical engineer from Boston, Samuel Chapman. “Amelia could have had a very different life,” said Shapiro. “She could have gone to Marblehead, Massachusetts, where [Chapman] had a house, and become part of the yacht set and she still would have had an interesting life. But I don’t think that was the life Amelia Earhart wanted, even if that meant she had a shorter life.”

Shapiro doesn’t neglect Putnam’s story, describing him as the “PT Barnum of publishing.” The family publishing company, G.P. Putnam and Sons, was founded in 1838 by his grandfather, and by the late 1920s, the ambitious young George was among several possible successors jockeying for position to replace his uncle, George Haven Putnam. He had his own ambitions, determined to bring what he viewed as a stodgy company fully into the 20th century.

Putnam published Charles Lindbergh‘s blockbuster memoir, We, in 1927 and followed that early success with a series of rather lurid adventure memoirs chronicling the exploits of “boy explorers.” The boys didn’t always survive their adventures, with one perishing from a snake bite and another drowning in a Bolivian flood. But the books were commercial successes, so Putnam kept cranking them out.

After Lindbergh’s historic crossing, Putnam was eager to tap into the public’s thirst for aviation stories. It wouldn’t be especially newsworthy to have another man make the same flight. But a woman? Putnam liked that idea, and a wealthy benefactor, steel heiress Amy Phipps Guest, provided financial support for the feat—really more of a publicity stunt, since Putnam’s plan, as always, was to publish a scintillating memoir of the journey. During the Jazz Age, newspapers routinely paid for exclusive rights to these kinds of stories in exchange for glowing coverage, per Shapiro. In this case, The New York Times did not initially want to sponsor a woman for a trans-Atlantic flight, but Putnam’s connections won them over.

Love at first sight

Earhart, then a social worker living in Boston, interviewed to be part of the three-person crew making that historic 1928 trans-Atlantic flight, and Putnam quickly spotted her potential to be his new adventure heroine. Railey later recalled that, at least for Putnam—whose marriage to Crayola heiress Dorothy Binney was floundering—it was love at first sight.

At the time, Earhart was still engaged to Chapman, and George was still married to Binney, but nonetheless, he “relentlessly pursued” Earhart. Earhart ended her engagement to Chapman in November 1928. “There’s a tape in the Smithsonian archives that talks about his wife coming in and catching them in sexual relations,” said Shapiro. “But [Binney] was having an affair, too, with a young man named George Weymouth [her son’s tutor]. This is the Jazz Age, anything goes. Amelia wanted to be able to achieve her dreams. Who are we to say a woman can’t marry a man who can give her a path to being wealthy?”

The successful 1928 flight earned Earhart the moniker “Lady Lindy.” Putnam showered his mistress with fur coats, sporty cars, and other luxurious trappings—although as her manager, he still kept 10 percent of her earnings. That life of luxury fell apart in October 1929 with the onset of the Great Depression, and Putnam found himself scrambling financially after being pushed out of the family publishing company.

Earhart and Putnam in 1931. Public domain

After his rather messy divorce from Binney, Putnam married Earhart in 1931. Earhart held decidedly unconventional views on marriage for that era: They held separate bank accounts, and she kept her maiden name, viewing the marriage as a “partnership” with “dual control,” and insisting in a letter to Putnam on their wedding day that she would not require fidelity. “I may have to keep some place where I can go to be myself, now and then, for I cannot guarantee to endure at all times the confinement of even an attractive cage,” she wrote.

Since money was tight, Putnam encouraged Earhart to go on the lecture circuit. Earhart would execute a stunt flight, write a book about it, and then go on a lecture tour. “This is an actual marriage,” said Shapiro. “It might have started out more romantically, but at a certain point, they needed each other in a partnership to survive. We don’t have fairy tale connections. Sometimes we have a hot romance that turns into a partnership and then cycles back into intense closeness and mental separation. I think that was the case with Amelia and George.”

Then came Earhart’s fateful final fight. The night before her scheduled departure, a nervous Earhart wanted to wait, but Putnam already had plans in the works for yet another flight, financed through sponsorship deals. And he wanted to get the resulting book about the current pending flight out in time for Christmas. He convinced her to take off as planned. Her navigator, Fred Noonan, was good at his job, but he was a heavy drinker, so he came cheap. That decision was one of several that would prove costly.

Shapiro describes this flight as being “plagued with mechanical issues from the start, underprepared and over-hyped, a feat of marketing more than a feat of engineering.” And she does not absolve Earhart from blame. “She refused to learn Morse code,” said Shapiro. “She refused to hear that trying to land on Howland Island was almost a suicide mission. It’s almost certain that she ran out of gas. Amelia was a very good person, a decent flyer, and beyond brave. She brought up women and championed feminism when other technically more gifted women pilots were going for solo records and had no time for their peers. She aided the aviation industry during the Great Depression as a likable ambassador of the air.”

However, Shapiro believes that Earhart’s marriage to Putnam amplified her incautious impulses, with tragic consequences on her final flight. “Is it George’s fault, or is it Amelia’s fault? I don’t think that’s fair to say,” she said. In many ways, the two complemented each other. Like Putnam, Earhart had great ambition, and her marriage to Putnam enabled her to achieve her goals.

The flip side is that they also brought out each other’s less positive attributes. “They were both aware of the risks involved in what they were doing,” Shapiro said. “But I also tried to show that there was a pattern of both of them taking extraordinary risks without really worrying about critical details. Yes, there is tremendous bravery in [undertaking] all these flights, but bravery is not always enough when charisma trumps caution—and when the showman insists the show must go on.”

Photo of Jennifer Ouellette

Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban.

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What do people actually use ChatGPT for? OpenAI provides some numbers.


Hey, what are you doing with that?

New study breaks down what 700 million users do across 2.6 billion daily GPT messages.

A live look at how OpenAI gathered its user data. Credit: Getty Images

As someone who writes about the AI industry relatively frequently for this site, there is one question that I find myself constantly asking and being asked in turn, in some form or another: What do you actually use large language models for?

Today, OpenAI’s Economic Research Team went a long way toward answering that question, on a population level, releasing a first-of-its-kind National Bureau of Economic Research working paper (in association with Harvard economist David Denning) detailing how people end up using ChatGPT across time and tasks. While other research has sought to estimate this kind of usage data using self-reported surveys, this is the first such paper with direct access to OpenAI’s internal user data. As such, it gives us an unprecedented direct window into reliable usage stats for what is still the most popular application of LLMs by far.

After digging through the dense 65-page paper, here are seven of the most interesting and/or surprising things we discovered about how people are using OpenAI today.

OpenAI is still growing at a rapid clip

We’ve known for a while that ChatGPT was popular, but this paper gives a direct look at just how big the LLM has been getting in recent months. Just measuring weekly active users on ChatGPT’s consumer plans (i.e. Free, Plus, and Pro tiers), ChatGPT passed 100 million users in early 2024, climbed past 400 million users early this year, and currently can boast over 700 million users, or “nearly 10% of the world’s adult population,” according to the company.

Line goes up… and faster than ever these days.

Line goes up… and faster than ever these days. Credit: OpenAI

OpenAI admits its measurements might be slightly off thanks to double-counting some logged-out users across multiple individual devices, as well as some logged-in users who maintain multiple accounts with different email addresses. And other reporting suggests only a small minority of those users are paying for the privilege of using ChatGPT just yet. Still, the vast number of people who are at least curious about trying OpenAI’s LLM appears to still be on the steep upward part of its growth curve.

All those new users are also leading to significant increases in just how many messages OpenAI processes daily, which has gone up from about 451 million in June 2024 to over 2.6 billion in June 2025 (averaged over a week near the end of the month). To give that number some context, Google announced in March that it averages 14 billion searches per day, and that’s after decades as the undisputed leader in Internet search.

… but usage growth is plateauing among long-term users

Newer users have driven almost all of the overall usage growth in ChatGPT in recent months.

Newer users have driven almost all of the overall usage growth in ChatGPT in recent months. Credit: OpenAI

In addition to measuring overall user and usage growth, OpenAI’s paper also breaks down total usage based on when its logged-in users first signed up for an account. These charts show just how much of ChatGPT’s recent growth is reliant on new user acquisition, rather than older users increasing their daily usage.

In terms of average daily message volume per individual long-term user, ChatGPT seems to have seen two distinct and sharp growth periods. The first runs roughly from September through December 2024, coinciding with the launch of the o1-preview and o1-mini models. Average per-user messaging on ChatGPT then largely plateaued until April, when the launch of the o3 and o4-mini models caused another significant usage increase through June.

Since June, though, per-user message rates for established ChatGPT users (those who signed up in the first quarter of 2025 or before) have been remarkably flat for three full months. The growth in overall usage during that last quarter has been entirely driven by newer users who have signed up since April, many of whom are still getting their feet wet with the LLM.

Average daily usage for long-term users has stopped growing in recent months, even as new users increase their ChatGPT message rates.

Average daily usage for long-term users has stopped growing in recent months, even as new users increase their ChatGPT message rates. Credit: OpenAI

We’ll see if the recent tumultuous launch of the GPT-5 model leads to another significant increase in per-user message volume averages in the coming months. If it doesn’t, then we may be seeing at least a temporary ceiling on how much use established ChatGPT users get out of the service in an average day.

ChatGPT users are younger and were more male than the general population

While young people are generally more likely to embrace new technology, it’s striking just how much of ChatGPT’s user base is made up of our youngest demographic cohort. A full 46 percent of users who revealed their age in OpenAI’s study sample were between the ages of 18 and 25. Add in the doubtless significant number of people under 18 using ChatGPT (who weren’t included in the sample at all), and a decent majority of OpenAI’s users probably aren’t old enough to remember the 20th century firsthand.

What started as mostly a boys’ club has reached close to gender parity among ChatGPT users, based on gendered name analysis.

What started as mostly a boys’ club has reached close to gender parity among ChatGPT users, based on gendered name analysis. Credit: OpenAI

OpenAI also estimated the likely gender split among a large sample of ChatGPT users by using Social Security data and the World Gender Name Registry‘s list of strongly masculine or feminine first names. When ChatGPT launched in late 2022, this analysis found roughly 80 percent of weekly active ChatGPT users were likely male. In late 2025, that ratio has flipped to a slight (52.4 percent) majority for likely female users.

People are using it for more than work

Despite all the talk about LLMs potentially revolutionizing the workplace, a significant majority of all ChatGPT use has nothing to do with business productivity, according to OpenAI. Non-work tasks (as identified by an LLM-based classifier) grew from about 53 percent of all ChatGPT messages in June of 2024 to 72.2 percent as of June 2025, according to the study.

As time goes on, more and more ChatGPT usage is becoming non-work related.

As time goes on, more and more ChatGPT usage is becoming non-work related. Credit: OpenAI

Some of this might have to do with the exclusion of users in the Business, Enterprise, and Education subscription tiers from the data set. Still, the recent rise in non-work uses suggests that a lot of the newest ChatGPT users are doing so more for personal than for productivity reasons.

ChatGPT users need help with their writing

It’s not that surprising that a lot of people use a large language model to help them with generating written words. But it’s still striking the extent to which writing help is a major use of ChatGPT.

Across 1.1 million conversations dating from May 2024 to June 2025, a full 28 percent dealt with writing assistance in some form or another, OpenAI said. That rises to a whopping 42 percent for the subset of conversations tagged as work-related (by far the most popular work-related task), and a majority, 52 percent, of all work-related conversations from users with “management and business occupations.”

A lot of ChatGPT use is people seeking help with their writing in some form.

A lot of ChatGPT use is people seeking help with their writing in some form. Credit: OpenAI

OpenAI is quick to point out, though, that many of these users aren’t just relying on ChatGPT to generate emails or messages from whole cloth. The percent of all conversations studied involves users asking the LLM to “edit or critique” text, at 10.6 percent, vs. just 8 percent that deal with generating “personal writing or communication” from a prompt. Another 4.5 percent of all conversations deal with translating existing text to a new language, versus just 1.4 percent dealing with “writing fiction.”

More people are using ChatGPT as an informational search engine

In June 2024, about 14 percent of all ChatGPT conversations were tagged as relating to “seeking information.” By June 2025, that number had risen to 24.4 percent, slightly edging out writing-based prompts in the sample (which had fallen from roughly 35 percent of the 2024 sample).

A growing number of ChatGPT conversations now deal with “seeking information” as you might do with a more traditional search engine.

A growing number of ChatGPT conversations now deal with “seeking information” as you might do with a more traditional search engine. Credit: OpenAI

While recent GPT models seem to have gotten better about citing relevant sources to back up their information, OpenAI is no closer to solving the widespread confabulation problem that makes LLMs a dodgy tool for retrieving facts. Luckily, fewer people seem interested in using ChatGPT to seek information at work; that use case makes up just 13.5 percent of work-related ChatGPT conversations, well below the 40 percent that are writing-related.

A large number of workers are using ChatGPT to make decisions

Among work-related conversations, “making decisions and solving problems” is a relatively popular use for ChatGPT.

Among work-related conversations, “making decisions and solving problems” is a relatively popular use for ChatGPT. Credit: OpenAI

Getting help editing an email is one thing, but asking ChatGPT to help you make a business decision is another altogether. Across work-related conversations, OpenAI says a significant 14.9 percent dealt with “making decisions and solving problems.” That’s second only to “documenting and recording information” for work-related ChatGPT conversations among the dozens of “generalized work activity” categories classified by O*NET.

This was true across all the different occupation types OpenAI looked at, which the company suggests means people are “using ChatGPT as an advisor or research assistant, not just a technology that performs job tasks directly.”

And the rest…

Some other highly touted use cases for ChatGPT that represented a surprisingly small portion of the sampled conversations across OpenAI’s study:

  • Multimedia (e.g., creating or retrieving an image): 6 percent
  • Computer programming: 4.2 percent (though some of this use might be outsourced to the API)
  • Creative ideation: 3.9 percent
  • Mathematical calculation: 3 percent
  • Relationships and personal reflection: 1.9 percent
  • Game and roleplay: 0.4 percent

Photo of Kyle Orland

Kyle Orland has been the Senior Gaming Editor at Ars Technica since 2012, writing primarily about the business, tech, and culture behind video games. He has journalism and computer science degrees from University of Maryland. He once wrote a whole book about Minesweeper.

What do people actually use ChatGPT for? OpenAI provides some numbers. Read More »

rocket-report:-russia’s-rocket-engine-predicament;-300th-launch-to-the-iss

Rocket Report: Russia’s rocket engine predicament; 300th launch to the ISS


North Korea test-fired a powerful new solid rocket motor for its next-generation ICBM.

A Soyuz-2.1a rocket is propelled by kerosene-fueled RD-107A and RD-108A engines after lifting off Thursday with a resupply ship bound for the International Space Station. Credit: Roscosmos

Welcome to Edition 8.10 of the Rocket Report! Dear readers, if everything goes according to plan, four astronauts are less than six months away from traveling around the far side of the Moon and breaking free of low-Earth orbit for the first time in more than 53 years. Yes, there are good reasons to question NASA’s long-term plans for the Artemis lunar programthe woeful cost of the Space Launch System rocket, the complexity of new commercial landers, and a bleak budget outlook. But many of us who were born after the Apollo Moon landings have been waiting for this moment our whole lives. It is almost upon us.

As always, we welcome reader submissions. If you don’t want to miss an issue, please subscribe using the box below (the form will not appear on AMP-enabled versions of the site). Each report will include information on small-, medium-, and heavy-lift rockets, as well as a quick look ahead at the next three launches on the calendar.

North Korea fires solid rocket motor. North Korea said Tuesday it had conducted the final ground test of a solid-fuel rocket engine for a long-range ballistic missile in its latest advancement toward having an arsenal that could viably threaten the continental United States, the Associated Press reports. The test Monday observed by leader Kim Jong Un was the ninth of the solid rocket motor built with carbon fiber and capable of producing 1,971 kilonewtons (443,000 pounds) of thrust, more powerful than past models, according to the North’s official Korean Central News Agency.

Mobility and flexibility … Solid-fueled intercontinental ballistic missiles, or ICBMs, have advantages over liquid-fueled missiles, which have historically comprised the bulk of North Korea’s inventory. Solid rocket motors can be stored for longer periods of time and are easier to conceal, transport, and launch on demand. The new solid rocket motor will be used on a missile called the Hwasong-20, according to North Korean state media. The AP reports some analysts say North Korea may conduct another ICBM test around the end of the year, showcasing its military strength ahead of a major ruling party congress expected in early 2026.

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Astrobotic eyes Andøya. US-based lunar logistics company Astrobotic and Norwegian spaceport operator Andøya Space have signed a term sheet outlining the framework for a Launch Site Agreement, European Spaceflight reports. The agreement, once finalized, will facilitate flights of Astrobotic’s Xodiac lander testbed from the Andøya Space facilities. The Xodiac vertical takeoff, vertical landing rocket was initially developed by Masten Space Systems to simulate landing on the Moon and Mars. When Masten filed for bankruptcy in 2022, Astrobotic acquired its intellectual property and assets, including the Xodiac vehicle.

Across the pond … So far, the small Xodiac rocket has flown on low-altitude atmospheric hops from Mojave, California, reaching altitudes of up to 500 meters, or 1,640 feet. The agreement between Astrobotic and Andøya paves the way for “several” Xodiac flight campaigns from Andøya Space facilities on the Norwegian coast. “Xodiac’s presence at Andøya represents a meaningful step toward delivering reliable, rapid, and cost-effective testing and demonstration capabilities to the European space market,” said Astrobotic CEO John Thornton.

Ursa Major breaks ground in Colorado. Ursa Major on Wednesday said it has broken ground on a new 400-acre site where it will test and qualify large-scale solid rocket motors for current and future missiles, including the Navy’s Standard Missile fleet, Defense Daily reports. The new site in Weld County, Colorado, north of Denver, will be ready for testing to begin in the fourth quarter of 2025. Ursa Major will be able to conduct full-scale static firings, and drop and temperature storage testing for current and future missile systems.

Seeking SRM options … Ursa Major said the new facility will support national and missile defense programs. The company’s portfolio includes solid rocket motors (SRMs) ranging from 2 inches to 22 inches in diameter for missiles like the Stinger, Javelin, and air-defense interceptors. Ursa Major aims to join industry incumbents Northrop Grumman, L3Harris, and newcomer Anduril as a major supplier of SRMs to the government. “This facility represents a major step forward in our ability to deliver qualified SRMs that are scalable, flexible, and ready to meet the evolving threat environment,” said Dan Jablonsky, CEO of Ursa Major, in a statement. “It’s a clear demonstration of our commitment and ability to rapidly advance and expand the American-made solid rocket motor industrial base that the country needs, ensuring warfighters will have the quality and quantity of SRMs needed to meet mission demands.”

Falcon 9 launches first satellites in a military megaconstellation. The first 21 satellites in a constellation that could become a cornerstone for the Pentagon’s Golden Dome missile-defense shield successfully launched from California Wednesday aboard a SpaceX Falcon 9 rocket, Ars reports. The Falcon 9 took off from Vandenberg Space Force Base, California, and headed south over the Pacific Ocean, reaching an orbit over the poles before releasing the 21 military-owned satellites to begin several weeks of activations and checkouts.

First of many … These 21 satellites will boost themselves to a final orbit at an altitude of roughly 600 miles (1,000 kilometers). The Pentagon plans to launch 133 more satellites over the next nine months to complete the build-out of the Space Development Agency’s first-generation, or Tranche 1, constellation of missile-tracking and data-relay satellites. Military officials have worked for six years to reach this moment. The Space Development Agency (SDA) was established during the first Trump administration, which made plans for an initial set of demonstration satellites that launched a couple of years ago. In 2022, the Pentagon awarded contracts for the first 154 operational spacecraft, including the ones launched Wednesday. “Back in 2019, when the SDA was stood up, it was to do two things. One was to make sure that we can do beyond line of sight targeting, and the other was to pace the threat, the emerging threat, in the missile-warning and missile-tracking domain. That’s what the focus has been,” said Gurpartap “GP” Sandhoo, the SDA’s acting director.

Another Falcon 9 was delayed three times. SpaceX scrubbed launching a communications satellite from an Indonesian company for a third consecutive day Wednesday, Spaceflight Now reports. Possible technical issues got in the way of a launch attempt Wednesday evening after back-to-back days of weather delays at Cape Canaveral Space Force Station, Florida. The Falcon 9 finally launched Thursday evening with the Boeing-built Nusantara Lima communications satellite, targeting a geosynchronous transfer orbit. It’s the latest satellite from the Indonesian company Pasifik Satelit Nusantara.

A declining market … This was just the fifth geosynchronous communications satellite to launch on a commercial rocket this year, all by SpaceX. There were 21 such satellites that launched on commercial vehicles in 2015, including SpaceX’s Falcon 9, Europe’s Ariane 5, Russia’s Proton, ULA’s Atlas V, and Japan’s H-IIA. Much of the world’s launch capacity today is used to deploy smaller communications satellites into low-Earth orbit, primarily for broadband connectivity rather than for the video broadcast market once dominated by higher-altitude geosynchronous satellites.

Putin urges Russia to build more rocket engines. Russian President Vladimir Putin urged aerospace industry leaders on September 5 to press on with efforts to develop booster rocket engines for space launch vehicles and build on Russia’s longstanding reputation as a leader in space technology, Reuters reports. Putin, who spent the preceding days in China and the Russian far eastern port of Vladivostok, flew to the southern Russian city of Samara, where he met industry specialists and toured the Kuznetsov design bureau engine manufacturing plant.

A shell of its former self … “It is important to consistently renew production capacity in terms of engines for booster rockets,” Russian news agencies quoted Putin as saying during the visit. “And in doing so, we must not only meet our own current and future needs but also move actively on world markets and be successful competitors.” The Kuznetsov plant in Samara builds medium-class RD-107 and RD-108 engines for Russia’s Soyuz-2 rockets, which launch Russian military satellites and crew and cargo to the International Space Station. Their designs can be traced to the dawn of the Space Age nearly 70 years ago. Meanwhile, the outlook for heavier-duty Russian rocket engines is murky, at best. Russia’s most-flown large rocket engine in the post-Cold War era, the RD-180, produced by a company called Energomash, is out of production after the end of sales to the United States.

India nabs a noteworthy launch contract. Astroscale, a satellite servicing and space debris mitigation company based in Japan, has selected India’s Polar Satellite Launch Vehicle (PSLV) to deliver a small satellite named ISSA-J1 to orbit in 2027. This is an interesting mission. The ISSA-J1 spacecraft will fly up to two large pieces of satellite debris in orbit to image and inspect them. ISSA-J1, developed in partnership with the Japanese government, is one in a series of Astroscale missions testing different ways of approaching, monitoring, capturing, and refueling other objects in space. The launch agreement was signed between Astroscale and NewSpace India Limited, the commercial arm of India’s space agency.

Rideshare not an option … “We selected NSIL after thorough evaluations of more than 10 launch service providers over the past year, considering technical capabilities, track record, cost, and other elements,” said Eddie Kato, president and managing director of Astroscale Japan. India’s PSLV is right-sized for a mission like this. ISSA-J1 is a rarity in that it must launch on a dedicated rocket because it has to reach a specific orbit to line up with the pieces of space debris it will approach and inspect. Rideshare launches, such as those that routinely fly on SpaceX’s Falcon 9 rocket, are cheaper but go to standard orbits popular for many different types of satellite missions. A dedicated launch on a Falcon 9 would presumably have been more expensive than a flight on India’s smaller PSLV. Rocket Lab’s Electron, another rocket popular for dedicated launches of small satellites, lacks the performance required for Astroscale’s mission.

Russian cargo en route to ISS. Another cargo ship is flying to humanity’s orbital outpost with the successful launch of Russia’s Progress MS-32 supply freighter Thursday from the Baikonur Cosmodrome in Kazakhstan, NASASpaceflight.com reports. The supply ship launched aboard a Soyuz-2.1a rocket and arrived in orbit about nine minutes later, kicking off a two-day pursuit of the International Space Station. This was the 300th launch of an assembly, crew, or cargo mission to the ISS since 1998, including a handful of missions that didn’t reach the complex due to rocket or spacecraft failures.

Important stuff … The Progress MS-32 cargo craft will dock with the aft port of the space station’s Russian Zvezda service module Saturday. The payloads flying on the Progress mission include food, experiments, clothing, water, air, and propellant to be pumped into the space station’s onboard tanks. The spacecraft will also reboost the lab’s orbit.

Metallic tiles? Not so great. It has been two weeks since SpaceX’s last Starship test flight, and engineers have diagnosed issues with its heat shield, identified improvements, and developed a preliminary plan for the next time the ship heads into space, Ars reports. Bill Gerstenmaier, a SpaceX executive in charge of build and flight reliability, presented the findings Monday at the American Astronautical Society’s Glenn Space Technology Symposium in Cleveland. The test flight went “extremely well,” Gerstenmaier said, but he noted some important lessons learned with the ship’s heat shield.

Crunch wrap reigns supreme “We were essentially doing a test to see if we could get by with non-ceramic tiles, so we put three metal tiles on the side of the ship to see if they would provide adequate heat control, because they would be simpler to manufacture and more durable than the ceramic tiles. It turns out they’re not,” Gerstenmaier said. “The metal tiles… didn’t work so well.” One bright spot with the heat shield was the performance of a new experimental material around and under the tiles. “We call it crunch wrap,” Gerstenmaier said. “It’s like a wrapping paper that goes around each tile.” On the next Starship flight, SpaceX will likely cover more parts of the heat shield with this crunch wrap material. Gerstenmaier said the inaugural flight of Starship Version 3, with upgraded engines and more fuel, is now set to occur next year.

An SLS compromise might be afoot in DC. The Trump administration is seeking to cancel NASA’s Space Launch System rocket after two more flights, but key lawmakers in Congress, including Republican Sen. Ted Cruz of Texas, aren’t ready to go along.  So is this an impasse? Possibly not, as sources say the White House and Congress may not be all that far apart on how to handle this. The solution involves canceling part of the SLS rocket now, but not all of it, Ars reports.

Goodbye EUS? … The compromise might be to cancel a large new upper stage for the SLS rocket called the Exploration Upper Stage. This would save NASA billions of dollars, and the agency could instead procure commercial upper stages, such as those built by United Launch Alliance or Blue Origin, to fly on SLS rockets after NASA’s Artemis III mission. It would also eliminate the need for NASA to finish building an expensive new launch tower at Kennedy Space Center, Florida. The upper stage flying on the first three SLS missions is no longer in production. Sources indicated to Ars that Blue Origin has already begun work on a modified version of its New Glenn upper stage that could fit within the shroud of the SLS rocket.

Next three launches

Sept. 13: Soyuz-2.1b | Glonass-K1 No. 18L | Plesetsk Cosmodrome, Russia | 02: 30 UTC

Sept. 13: Falcon 9 | Starlink 17-10 | Vandenberg Space Force Base, California | 15: 41 UTC

Sept. 14: Falcon 9 | Cygnus NG-23 | Cape Canaveral Space Force Station, Florida | 22: 11 UTC

Photo of Stephen Clark

Stephen Clark is a space reporter at Ars Technica, covering private space companies and the world’s space agencies. Stephen writes about the nexus of technology, science, policy, and business on and off the planet.

Rocket Report: Russia’s rocket engine predicament; 300th launch to the ISS Read More »

jef-raskin’s-cul-de-sac-and-the-quest-for-the-humane-computer

Jef Raskin’s cul-de-sac and the quest for the humane computer


“He wanted to make [computers] more usable and friendly to people who weren’t geeks.”

Consider the cul-de-sac. It leads off the main street past buildings of might-have-been to a dead-end disconnected from the beaten path. Computing history, of course, is filled with such terminal diversions, most never to be fully realized, and many for good reason. Particularly when it comes to user interfaces and how humans interact with computers, a lot of wild ideas deserved the obscure burials they got.

But some deserved better. Nearly every aspiring interface designer believed the way we were forced to interact with computers was limiting and frustrating, but one man in particular felt the emphasis on design itself missed the forest for the trees. Rather than drowning in visual metaphors or arcane iconographies doomed to be as complex as the systems they represented, the way we deal and interact with computers should stress functionality first, simultaneously considering both what users need to do and the cognitive limits they have. It was no longer enough that an interface be usable by a human—it must be humane as well.

What might a computer interface based on those principles look like? As it turns out, we already know.

The man was Jef Raskin, and this is his cul-de-sac.

The Apple core of the Macintosh

It’s sometimes forgotten that Raskin was the originator of the Macintosh project in 1979. Raskin had come to Apple with a master’s in computer science from Penn State University, six years as an assistant professor of visual arts at the University of California, San Diego (UCSD), and his own consulting company. Apple co-founder Steve Jobs subsequently hired Raskin’s company to write the Apple II’s BASIC programming manual, and Raskin joined Apple as manager of publications in 1978.

Raskin’s work on documentation and testing, combined with his technical acumen, gave him outsized influence within the young company. As the 40-column uppercase-only Apple II was ill-suited for Raskin’s writing, Apple developed a text editor and an 80-column display card, and Raskin leveraged his UCSD contacts to port UCSD Pascal and the p-System virtual machine to the Apple II when Steve Wozniak developed the Apple II’s floppy disk drives. (Apple sold this as Apple Pascal, and many landmark software programs like the Apple Presents Apple tutorial were written in it.)

But Raskin nevertheless concluded that a complex computer (by the standards of the day) could never exist in quantity, nor be usable by enough people to matter. In his 1979 essay “Computers by the Millions,” he argued against systems like the Apple II and the in-development Apple III that relied on expansion slots and cards for many advanced features. “What was not said was that you then had the rather terrible task of writing software to support these new ‘boards,’” he wrote. “Even the more sophisticated operating systems still required detailed understanding of the add-ons… This creates a software nightmare.”

Instead, he felt that “personal computers will be self-contained, complete, and essentially un-expandable. As we’ll see, this strategy not only makes it possible to write complete software but also makes the hardware much cheaper and producible.” Ultimately, Raskin believed, only a low-priced, low-complexity design could be manufactured in large enough numbers for a future world and be functional there.

The original Macintosh was designed as an embodiment of some of these concepts. Apple chairman Mike Markkula had a $500 (around $2,200 in 2025) game machine concept in mind called “Annie,” named after the Playboy comic character and intended as a low-end system paired with the Apple II—starting at around double that price at the time—and the higher-end Apple III and Lisa, which were then in development. Raskin wasn’t interested in developing a game console, but he did suggest to Markkula that a $500 computer could have more appeal, and he spent several months writing specifications and design documents for the proposed system before it was approved.

“My message,” wrote Raskin in The Book of Macintosh, “is that computers are easy to use, and useful in everyday life, and I want to see them out there, in people’s hands, and being used.” Finding female codenames sexist, he changed Annie to Macintosh after his favorite variety of apple, though using a variant spelling to avoid a lawsuit with the previously existing McIntosh Laboratory. (His attempt was ultimately for naught, as Apple later ended up having to license the trademark from the hi-fi audio manufacturer and then purchase it outright anyway.)

Raskin’s small team developed the hardware at Apple’s repurposed original Cupertino offices separate from the main campus. Initially, he put together a rough all-in-one concept, originally based on an Apple II (reportedly serial number 2) with a “jury-rigged” monitor. This evolved into a prototype chiefly engineered by Burrell Smith, selecting for its CPU the 8-bit Motorola 6809 as an upgrade from the Apple II’s MOS 6502 but still keeping costs low.

Similarly, a color display and a larger amount of RAM would have also added expense, so the prototype had a small 256×256 monochrome CRT driven by the ubiquitous Motorola 6845 CRTC, plus 64K of RAM. A battery and built-in printer were considered early on but ultimately rejected. The interface emphasized text and keyboard: There was no mouse, and the display was character-based instead of graphical.

Raskin was aware of early graphical user interfaces in development, particularly Xerox PARC’s, and he had even contributed to early design work on the Lisa, but he believed the mouse was inferior to trackballs and tablets and felt such pointing devices were more appropriate for graphics than text. Instead, function keys allowed the user to select built-in applications, and the machine could transparently shift between simple text entry or numeric evaluation in a “calculator-based language” depending on what the user was typing.

During the project’s development, Apple management had recurring concerns about its progress, and it was nearly canceled several times. This changed in late 1980 when Jobs was removed from the Lisa project by President Mike Scott, after which Jobs moved to unilaterally take over the Macintosh, which at that time was otherwise considered a largely speculative affair.

Raskin initially believed the change would be positive, as Jobs stated he was only interested in developing the hardware, and his presence and interest quickly won the team new digs and resources. New team member Bud Tribble suggested that it should be able to take advantage of the Lisa’s powerful graphics routines by migrating to its Motorola 68000, and by February 1981, Smith was able to duly redesign the prototype for the more powerful CPU while maintaining its lower-cost 8-bit data bus.

This new prototype expanded graphics to 384×256, allowed the use of more RAM, and ran at 8 MHz, making the prototype noticeably faster than the 5 MHz Lisa yet substantially cheaper. However, by sharing so much of Lisa’s code, the interface practically demanded a pointing device, and the mouse was selected, even though Raskin had so carefully tried to avoid it. (Raskin later said he did prevail with Jobs on the mouse only having one button, which he believed would be easier for novices, though other Apple employees like Larry Tesler have contested his influence on this decision.)

As Jobs started to take over more and more portions of the project, the two men came into more frequent conflict, and Raskin eventually quit Apple for good in March 1982. The extent of Raskin’s residual impact on the Macintosh’s final form is often debated, but the resulting 1984 Macintosh 128K is clearly a different machine from what Raskin originally envisioned. Apple acknowledged Raskin’s contributions in 1987 by presenting him with one of the six “millionth” Macintoshes, which he auctioned off in 1999 along with the Apple II used in the original concept.

A Swyftly tilting project

After Raskin’s departure from Apple, he established Information Appliance, Inc. in Palo Alto to develop his original concept on his own terms. By this time, it was almost a foregone conclusion that microcomputers would sooner or later make their way to everyone; indeed, home computer pioneers like Jack Tramiel’s Commodore were already selling inexpensive “computers by the millions”—literally. With the technology now evolving at a rapid pace, Raskin wanted to concentrate more on the user interface and the concept’s built-in functionality, reviving the ideas he believed had become lost in the Macintosh’s transition. He christened it with a new name: Swyft.

In terms of industrial design, the Swyft owed a fair bit to Raskin’s prior prototype as it was also an all-in-one machine, using a built-in 9” monochrome CRT display. Unlike the Macintosh, however, the screen was set back at an angle and the keyboard was built-in; it also had a small handle at the base of its sloped keyboard making it at least notionally portable.

Disk technology had advanced, so it sported a 3.5-inch floppy drive (also like the Macintosh, albeit hidden behind a door), though initially the prototype used a less-powerful 8-bit MOS 6502 CPU running at 2MHz. The 6502’s 64K addressing limit and the additional memory banking logic it required eventually proved inadequate, and the CPU was changed during development to the Motorola 68008, a cheaper version of the 68000 with an 8-bit data bus and a maximum address space of 1MB. Raskin intended the Swyft to act like an always-on appliance, always ready and always instant, so it had a lower-power mode and absolutely no power switch.

Instead of Pascal or assembly language, Swyft’s ROM operating system was primarily written in Forth. To reduce the size of the compiled code, developer Terry Holmes created a “tokenized” version that embedded smaller tokens instead of execution addresses into Forth word definitions, trading the overhead of an additional lookup step (which was written in hand-coded assembly and made very quick) for a smaller binary size. This modified dialect was called tForth (for “token,” or “Terry”). The operating system supported the hardware and the demands of the on-screen bitmapped display, which could handle true proportional text.

Swyft’s user interface was also radically different and was based on a “document” metaphor. Most computers of that time and today, mobile devices included, divide functionality among separate applications that access files. Raskin believed this approach was excessive and burdensome, writing in 1986 that “[b]y choosing to focus on computers rather than the tasks we wanted done, we inherited much of the baggage that had accumulated around earlier generations of computers. It is more a matter of style and operating systems that need elaborate user interfaces to support huge application programs.”

He expanded on this point in his 2000 book The Humane Interface: “[Y]ou start in the generating application. Your first step is to get to the desktop. You must also know which icons correspond to the desired documents, and you or someone else had to have gone through the steps of naming those documents. You will also have to know in which folder they are stored.”

Raskin thus conceived of a unified workspace in which everything was stored, accessed through one single interface appearing to the user as a text editor editing one single massive document. The editor was intelligent and could handle different types of text according to its context, and the user could subdivide the large document workspace into multiple subdocuments, all kept together. (This even included Forth code, which the user could write and evaluate in place to expand the system as they wished.) Data received from the serial port was automatically “typed” into the same document, and any or all text could be sent over the serial port or to a printer. Instead of function keys, a USE FRONT key acted like an Option or Command key to access special features.

Because everything was kept in one place, when the user saved the system state to a floppy disk, their entire workspace was frozen and stored in its entirety. Swyft additionally tagged the disk with a unique identifier so it knew when a disk was changed. When that disk was reinserted and resumed, the user picked up exactly where they left off, at exactly the same point, with everything they had been working on. Since everything was kept together and loaded en masse, there was no need for a filesystem.

Swyft also lacked a mouse—or indeed any conventional means of moving the cursor around. To navigate through the document, Swyft instead had LEAP keys, which when pressed alone would “creep” forward or backward by single characters. But when held down, you could type a string of characters and release the key, and the system would search forward or backward for that string and highlight it, jumping entire pages and subdocuments if necessary.

If you knew what was in a particular subdocument, you could find it or just LEAP forward to the next document marker to scan through what was there. Additionally, by leaping to one place, leaping again to another, and then pressing both LEAP keys together, you could select text as well. The steps to send, delete, change, or copy anything in the document are the same for everything in the document. “So the apparent simplicity [of other systems] is arrived at only after considerable work has been done and the user has shouldered a number of mental burdens,” wrote Raskin, adding, “the conceptual simplicity of the methods outlined here would be preferable. In most cases, the work required is also far less.”

Get something on sale faster, said Tom Swyftly

While around 60 Swyft prototypes of varying functionality were eventually made, IAI’s backers balked at the several million dollars additionally required to launch the product under the company’s own name. To increase their chances of a successful return on investment, they demanded a licensee for the design instead that would insulate the small company from the costs of manufacturing and sales. They found it in Japanese manufacturer Canon, which had expanded from its core optical and imaging lines into microcomputers but had spent years unsuccessfully trying to crack the market. However, possibly because of its unusual interface, Canon unexpectedly put its electronic typewriter division in charge of the project, and the IAI team began work with Canon’s engineers to refine the hardware for mass production.

SwyftCard advertisement in Byte, October 1985, with Jef Raskin and Steve Wozniak.

In the meantime, IAI investors prevailed upon management to find a way to release some of the Swyft technology early in a less expensive incarnation. This concept eventually turned into an expansion card for the Apple IIe. Raskin’s team was able to adapt some of the code written for the Swyft to the new device, but because the IIe is also a 6502-based system and is itself limited to a 64K address space, it required its own onboard memory banking hardware as well. With the card installed, the IIe booted into a scaled-down Swyft environment using its onboard 16K EPROM, with the option of disabling it temporarily to boot regular Apple software. Unlike the original Swyft, the Apple II SwyftCard does not use the bitmap display and appears strictly in 80-column non-proportional text. The SwyftCard went on sale in 1985 for $89.95, approximately $270 in 2025 dollars.

The initial SwyftCard tutorial page. Credit: Cameron Kaiser

The SwyftCard’s unified workspace can be subdivided into various “subdocuments,” which appear as hard page breaks with equals signs. Although up to 200 pages were supported, in practice, the available workspace limits you to about 15 or 20, “densely typed.” It came with a built-in tutorial which began with orienting you to the LEAP keys (i.e., the two Apple keys) and how to navigate: hold one of them down and type the text to leap to (or equals signs to jump to the next subdocument), or tap them repeatedly to slowly “creep.”

The two-tone cursor. Credit: Cameron Kaiser

Swyft and the SwyftCard implement a two-phased cursor, which the SwyftCard calls either “wide” or “narrow.” By default, the cursor is “narrow,” alternating between a solid and a partially filled block. As you type, the cursor splits into a “wide” form—any text shown in inverse, usually the last character you entered, is what is removed when you press DELETE, with the blinking portion after the inverse text indicating the insertion point. When you creep or leap, the cursor merges back into the “narrow” form. When narrow, DELETE deletes right as a true delete, instead of a backspace. If you selected text by pressing both LEAP keys together, those become highlighted in inverse and can be cut and pasted.

The SwyftCard software defines a USE FRONT key (i.e., the Control key) as well. This was most noticeable as a quick key combination for saving your work to disk, to which the entire workspace was saved in one go with no filenames (i.e., one disk equated one workspace), though it had many other such functions within the program. Since it could be tricky to juggle floppies without overwriting them, the software also took pains to ensure each formatted disk was tagged with a unique identifier to avoid accidental erasure. It also implemented serial communications such that you could dial up a remote system and use USE FRONT-SEND to send it or be dialed into and receive text into the workspace automatically.

SwyftCards didn’t sell in massive numbers, but their users loved them, particularly the speed and flexibility the system afforded. David Thornburg (the designer of the KoalaPad tablet), writing for A+ in November 1985, said it “accomplished something that I never knew was possible. It not only outperforms any Apple II word-processing system, but it lets the Apple IIe outperform the Macintosh… Will Rogers was right: it does take genius to make things simple.”

The Swyft and SwyftCard, however, were as much philosophy as interface; they represented Raskin’s clear desire to “abolish the application.” Rather than starting a potentially different interface to do a particular task, the task should be part of the machine’s standard interface and be launched by direct command. Similarly, even within the single user interface, there should be no “modes” and no switching between different minor behaviors: the interface ought to follow the same rules as much of the time as possible.

“Modes are a significant source of errors, confusion, unnecessary restrictions, and complexity in interfaces,” Raskin wrote in The Humane Interface, illustrating it with the example of “at one moment, tapping Return inserts a return character into the text, whereas at another time, tapping Return cases the text typed immediately prior to that tap to be executed as a command.”

Even a device as simple as a push-button flashlight is modal, argued Raskin, because “[i]f you do not know the present state of the flashlight, you cannot predict what a press of the flashlight’s button will do.” Even if an individual application itself is notionally modeless, Raskin presented the real-world example of Command-N commonly used to open a new document but AOL’s client using Command-M for a new E-mail message; the situation “that gives rise to a mode in this example consists of having a particular application active. The problem occurs when users employ the Command-N command habitually,” he wrote.

Ultimately, wrote Raskin, “[a]n interface is humane if it is responsive to human needs and considerate of human frailties.” In this case, the particular frailty Raskin concentrated on is the natural unconscious human tendency to form habitual behaviors. Because such habits are hard to break, command actions and gestures in an interface should be consistent enough that their becoming habitual makes them more effective, allowing a user to “do the task without having to think about it… We must design interfaces that (1) deliberately take advantage of the human trait of habit development and (2) allow users to develop habits that smooth the flow of their work.” If a task is always accomplished the same way, he asserted, then when the user has acquired the habit of doing so, they will have simultaneously mastered that task.

The Canon Cat’s one and only life

Raskin’s next computer preserved many such ideas from the Swyft, but it only did so in spite of the demands of Canon management, who forced multiple changes during development. Although the original Swyft (though not the SwyftCard) had true proportional text and at least the potential for user-created graphics, Canon’s electric typewriter division was then in charge of the project and insisted on non-proportional fixed-width text and no graphics, because that’s all the official daisywheel printer could generate—even though the system’s bitmapped display remained. (A laser printer option was later added but was nevertheless still limited to text.)

Raskin wanted to use a Mac-like floppy drive that could automatically detect floppy disk insertion, but Canon required the system to use their own floppy drives, which didn’t. Not every change during development was negative. Much of the more complicated Swyft logic board was consolidated into smaller custom gate array chips for mass production, along with the use of a regular 68000 instead of the more limited 68008, which was also cheaper in volume despite only being run at 5MHz.

However, against his repeated demands to the contrary and lengthy explanations of the rationale, Raskin was dismayed to find the device was nevertheless fitted with a power switch; Canon’s engineering staff said they simply thought an error had been made and added it, and by then, it was too late in development to remove it.

Canon management also didn’t understand the new machine’s design philosophy, treating it as an overgrown word processor (dubbed a “WORK Processor [sic]”) instead of the general-purpose computer Raskin intended, and required its programmability in Forth to be removed. This was unpopular with Raskin’s team, so rather than remove it completely, they simply hid it behind an unlikely series of keystrokes and excised it from the manual. On the other hand, because Canon considered it an overgrown word processor, it seemed entirely consistent to keep the Swyft’s primary interface intact otherwise, including its telecommunication features. The new system also got a new name: the Cat.

Canon Cat advertising brochure.

Thus was released the Canon Cat, announced in July 1987, for $1,495 (about $4,150 in 2025 dollars ). The released version came with 256K of RAM, with sockets to add an optional 128K more for 384K total, shared between the video circuitry, Forth dictionary, settings, and document text, all of which could be stored to the 3.5-inch floppy. (Another row of solder pads could potentially hold yet another 128K, but no shipping Cat ever populated it.)

Its 256K of system ROM contained the entirety of the editor and tForth runtime, plus built-in help screens, all immediately available as soon as you turned it on. An additional 128K ROM provided a 90,000-word dictionary to which the user could add words that were also automatically saved to the same disk. The system and dictionary ROMs came in versions for US and UK English, French, and German.

The Canon Cat. Cameron Kaiser

Like the Swyft it was based on, the Cat was an all-in-one system. The 9-inch monochrome CRT was retained, but the floppy drive no longer had a door, and the keyboard was extended with several special keys. In particular, the LEAP keys, as befitting their central importance, were given a row to themselves in an eye-catching shade of pink.

Function key combinations with USE FRONT are printed on the front of the keycaps. The Cat provided both a 1200 baud modem and a 9600bps RS-232 connector for serial data; it could dial out or be dialed into to upload text. Text transmitted to the Cat via the serial port was inserted into the document as if it had been typed in at the console. A Centronics-style printer port connected Canon’s official printer options, though many printers were compatible.

The Cat can be (imperfectly) emulated with MAME; the Internet Archive has a preconfigured Wasm version with Canon ROMs that you can also run in your browser. Note that the current MAME driver, as of this writing, will freeze if the emulated Cat makes a beep, and the ROM’s default keyboard layout assumes you’re using a real Cat, not a PC or Mac. These minor issues can be worked around in the emulated Cat’s setup menu by setting the problem signal to Flash (without a beep) and the keyboard to ASCII. The screenshots here are taken from MAME and adjusted to resemble the Cat’s display aspect ratio.

The Swyft and SwyftCard’s editing paradigm transferred to the Canon Cat nearly exactly. Preserved is the “wide” and “narrow” cursor, showing both the deletion range and the insertion point, as well as the use of the LEAP keys to creep, search, and select text ranges. (In MAME, the emulated LEAP keys are typically mapped to both Alt or Option keys.) SHIFT-LEAP can also be used to scroll the screen line by line, tapping LEAP repeatedly with SHIFT down to continue motion, and the Cat additionally implements a single level of undo with a dedicated UNDO key. The USE FRONT key also persisted, usually mapped in MAME to the Control key(s). Text could be bolded or underlined.

Similarly, the Cat inherits the same “multiple document interface” as the Swyfts: the workspace can be arbitrarily divided into documents, here using the DOCUMENT/PAGE key (mapped usually to Page Down in MAME), and the next or previous document can be LEAPed to by using the DOCUMENT/PAGE key as the target.

However, the Cat has an expanded interface compared to the SwyftCard, with a ruler (in character positions) at the bottom, text and keyboard modes, and open areas for on-screen indicators when disk access or computations are in progress.

Calculating data with the Canon Cat. Credit: Cameron Kaiser

Although Canon had mandated that the Cat’s programmability be suppressed, the IAI team nevertheless maintained the ability to compute expressions, which Canon permitted as an extension of the editor metaphor. Simple arithmetic such as 355/113 could be calculated in place by selecting the text and pressing USE FRONT-CALC (Control-G), which yields the answer with a dotted underline to indicate the result of a computation. (Here, the answer is computed to the default two decimal digits of precision, which is configurable.) Pressing USE FRONT-CALC within that answer reopens the expression to change it.

Computations weren’t merely limited to simple figures, though; the Cat also allowed users to store the result of a computation to a variable and reference that variable in other computations. If the variables underlying a particular computation were changed, its result would automatically update.

A spreadsheet built with expressions on the Cat. Credit: Cameron Kaiser

This capability, along with the Cat’s non-proportional font, made it possible to construct simple spreadsheets right in the editor using nothing more than expressions and the TAB key to create rows and columns. Cells can be referred to by expressions in other cells using a special function use() with relative coordinates. Constant values in “cells” can simply be entered as plain text; if recalculation is necessary, USE FRONT-CALC will figure it out. The Cat could also maintain and sort simple line lists, which, when combined with the LEARN macro facility, could be used to automate common tasks like mail merges.

The Canon Cat’s built-in on-line help facility. Credit: Cameron Kaiser

The Cat also maintained an extensive set of help screens built into ROM that the SwyftCard, for capacity reasons, was forced to load from floppy disk. Almost every built-in function had a documentation screen accessible from USE FRONT-HELP (Control-N): keep USE FRONT down, release the N key, and then press another key to learn about it. When the USE FRONT key is also released, the Cat instantly returns to the editor. Similarly, if the Cat beeped to indicate an error, pressing USE FRONT-HELP could also explain why. Errors didn’t trigger a modal dialogue or lock out system functions; you could always continue.

Internally, the current workspace contained not only the visible text documents but also any custom words the user added to the dictionary and any additional tForth words defined in memory. Ordinarily, there wouldn’t be any, given that Canon didn’t officially permit the user to program their own software, but there were a very small number of software applications Canon itself distributed on floppy disk: CATFORM, which allowed the user to create, fill out, and print form templates, and CATFILE, Canon’s official mailing list application. Dealers were instructed to provide new users with copies, though the Cat here didn’t come with them. Dealers also had special floppies of their own for in-store demos and customization.

The backdoor to Canon Cat tForth. Credit: Cameron Kaiser

Still, IAI’s back door to Forth quietly shipped in every Cat, and the clue was a curious omission in the online help: USE FRONT-ANSWER. This otherwise unexplained and unused key combination was the gateway. If you entered the string Enable Forth Language, highlighted it, and evaluated it with USE FRONT-ANSWER (not CALC; usually Control-Backspace in MAME), you’d get a Forth ok prompt, and the system was now yours. Reset the Cat or type re to return to the editor.

With Forth enabled, you could either enter code at the prompt, or do so within the editor and press USE FRONT-ANSWER to evaluate it, putting any output into the document just like Applesoft BASIC did on the SwyftCard. Through the Forth interface it was possible to define your own words, saved as part of the workspace, or even hack in 68000 machine code and completely take control of the machine. Extensive documentation on the Cat’s internals eventually surfaced, but no third-party software was ever written for the platform during its commercial existence.

As it happened, whatever commercial existence the Cat did have turned out to be brief and unprofitable anyway. It sold badly, blamed in large part on Canon’s poor marketing, which positioned it as an expensive dedicated word processor in an era where general-purpose PCs and, yes, Macintoshes were getting cheaper and could do more.

Various apocryphal stories circulate about why the Cat was killed—one theory cites internal competition between the typewriter and computer divisions; another holds that Jobs demanded the Cat be killed if Canon wanted a piece of his new venture, NeXT (and Owen Linzmeyer reports that Canon did indeed buy a 16 percent stake in 1989)—but regardless of the reason, it lasted barely six months on the market before it was canceled. The 1987 stock market crash was a further blow to the small company and an additional strain on its finances.

Despite the Cat’s demise, Raskin’s team at IAI attempted to move forward with a successor machine, a portable laptop that would have reportedly weighed just four pounds. The new laptop, christened the Swyft III, used a ROM-based operating system based on the Cat’s but with a newer, more sophisticated “leaping” technology called Hyperleap. At $999, it was to include a 640×200 supertwist LCD, a 2400 bps modem and 512K of RAM (a smaller $799 Swyft I would have had less memory and no modem), as well as an external floppy drive and an interchange facility for file transfers with PCs and Macs.

As Raskin had originally intended, the device achieved its claimed six-hour battery life (NiCad or longer with alkaline) primarily by aggressively sleeping when idle but immediately resuming full functionality when a key was pressed. Only two prototypes were ever made before IAI’s investors, considering the company risky after the Cat’s market failure and little money coming in, finally pulled the plug and caused the company to shut down in 1992. Raskin retained patents on the “leaping” method and the Swyft/Cat’s means of saving and restoring from disk, but their subsequent licensees did little with the technology, and the patents in the present day have lapsed.

If you can’t beat ’em, write software

The Cat is probably the best known of Raskin’s designs (notwithstanding the Macintosh, for reasons discussed earlier), especially as Raskin never led the development of another computer again. Nevertheless, his interface ideas remained influential, and after IAI’s closing, he continued as an author and frequent consultant and reviewer for various consumer products. These observations and others were consolidated into his later book The Humane Interface, from which this article has already liberally quoted. On the page before the table of contents, the book observes that “[w]e are oppressed by our electronic servants. This book is dedicated to our liberation.”

In The Humane Interface, Raskin not only discusses concepts such as leaping and habitual command behaviors but means of quantitative assessment as well. One of the more well-known is Fitts’ Law, after psychologist Paul Fitts, Jr., that predicts the time needed to quickly move to a target area is correlated with both the size of the target and its distance from the starting position.

This has been most famously used to justify the greater utility of a global menu bar completely occupying the edge of a screen (such as in macOS) because the mouse pointer stops at the edge, making the menu bar effectively infinitely large and therefore easy to “hit.” Similarly, Hick’s law (or the Hick-Hyman law, named for psychologists William Edmund Hick and Ray Hyman) asserts that increasing the number of choices a user is presented with will increase their decision time logarithmically. Given experimental constants, both laws can predict how long a user will need to hit a target or make a choice.

Notably, none of Raskin’s systems (at least as designed) superficially depended on either law because they had no explicit pointing device and no menus to select from. A more meaningful metric he also considers might be the Card-Moran-Newell GOMS model (“goals, objects, methods and selection rules”) and how it applies to user motion. While the time needed to mentally prepare, press a key, point to a particular position on the display or move from input device to input device (say, mouse to-and-from keyboard) will vary from person to person, most users will have similar times, and general heuristics exist (e.g., nonsense is easier to type than structured data).

However, the length of time the computer takes to respond is within the designer’s control, and its perception can be reduced by giving prompt and accurate feedback, even if the operation’s actual execution time is longer. Similarly, if we reduce keystrokes or reduce having to move from mouse to keyboard for a given task, the total time to perform that task becomes less for any user.

Although these timings can help to determine experimentally which interface is better for a given task, Raskin points out we can use the same principles to also determine the ideal efficiency of such interfaces. An interface that gives the user no choices but still must be interacted with is maximally inefficient because the user must do some non-zero amount of work to communicate absolutely no information.

A classic example might be a modal alert box with only one button—asynchronous or transparent notifications could be better used instead. Likewise, an interface with multiple choices will nevertheless become less efficient if certain choices are harder or more improbable to access, such as buttons or click areas being smaller than others, or a particular choice needing more typing to select than other choices.

Raskin’s book also considers alternative means of navigation, pointing out that “natural” and “intuitive” are not necessarily synonyms for “easy to use.” (A mouse can be easy to use, but it’s not necessarily natural or intuitive. Recall Scotty in Star Trek IV picking up the Macintosh Plus mouse and talking to it instead of trying to move it, and then eventually having to use the keyboard. Raskin cites this very scene, in fact.)

Besides leaping, Raskin also presents the idea of a zooming user interface (ZUI), allowing the user an easier way to not only reach their goal but also see themselves in relationship to that goal and within the entire workspace. If you see what you want, zoom in. If you’ve lost your place, zoom out. One could access a filesystem this way, or a collection of applications or associated websites. Raskin was hardly the first to propose the ZUI—Ivan Sutherland developed a primitive ZUI for graphics in his 1962 Sketchpad, along with the Spatial Dataland at MIT and Xerox PARC’s Smalltalk with “infinite” desktops—but he recognized its unique abilities to keep a user mentally grounded while navigating large structures that would otherwise become unwieldy. This, he asserts, made it more humane.

To crystallize these concepts, rather than create another new computer, Raskin instead started work on a software package with a team that included his son, Aza, initially called The Humane Environment. THE’s HumaneEditorProject was first unveiled to the world on Christmas Eve 2002, though initially only as a SourceForge CVS tree, since it was considered very unfinished. The original early builds of the Humane Editor were open-source and intended to run on classic Mac OS 9, though QEMU, SheepShaver and Classic under Tiger and earlier will also run it.

Default document. Credit: Cameron Kaiser

As before, the Humane Editor uses a large central workspace subdivided into individual documents, here separated by backtick characters. Our familiar two-tone cursor is also maintained. However, although font sizes, boldface, italic, and underlining were supported, colors (and, additionally, font sizes) were still selected by traditional Mac pulldown menus.

Leaping with the SHIFT and angle bracket keys. Credit: Cameron Kaiser

Leaping, here with a trademark, is again front and center in THE. However, instead of dedicated keys, leaping is merely a part of THE’s internal command line, termed the Humane Quasimode, where other commands can be sent. Notice that the prompt is displayed as translucent text over the work area.

The Deletion Document. Credit: Cameron Kaiser

When text was deleted, either by backspacing over it or pressing DELETE with a selected region, it went to an automatically created and maintained “DELETION DOCUMENT” from which it could be rescued. Effectively, this turned the workspace into a yank buffer along with all your documents, and undoing any destructive editing operation thus became merely another cut and paste. (Deleting from the deletion document just deleted.)

Command listing. Credit: Cameron Kaiser

A full list of commands accepted by the Quasimode was available by typing COMMANDS, which in turn emitted them to the document. These are based on precompiled Python files, which the user could edit or add to, and arbitrary Python expressions and code could also be inserted and run from the document workspace directly.

THE was a fully functioning editor, albeit incomplete, but nevertheless capable enough to write its own documentation with. Despite that, the intention was never to make something that was just an editor, and this aspiration became more obvious as development progressed. To make the software available on more platforms, development subsequently changed to wxPython in 2004, and later Python and Pygame to handle the screen display. The main development platform switched at the same time to Windows, and a Windows demo version of this release was made, although Mac OS X and Linux could still theoretically run it if you installed the prerequisites.

With the establishment of the Raskin Center for Humane Interfaces (RCHI), THE’s development continued under a new name, Archy. (This Wayback Machine link is the last version of the site before it was defaced and eventually domain-parked.) The new name was both a pun on “RCHI” and a reference to the Don Marquis characters, Archy and Mehitabel, specifically Archy the typewriting cockroach, whose alleged writings largely lack capital letters or punctuation because he couldn’t hit the SHIFT key at the same time. Archy’s final release shown here was the unfinished build 124, dated December 15, 2005.

The initial Archy window. Credit: Cameron Kaiser

Archy had come a long way from the original Mac THE, finally including the same sort of online help tutorial that the SwyftCard and Cat featured. It continued the use of a dedicated key to enter commands—in this case, CAPS LOCK. Hold it down, type the command, and then release it.

Leaping in Archy. Credit: Cameron Kaiser

Likewise, dedicated LEAP keys returned in Archy, in this case Left and Right Alt, and as before, selection was done by pressing both LEAP keys. A key advancement here is that any text that would be selected, if you chose to select it, is highlighted beforehand in a light shade of yellow so you no longer had to remember where your ranges were.

A list of commands in Archy. Credit: Cameron Kaiser

As before, the COMMANDS verb gave you a list of commands. While THE’s command suite was almost entirely specific to an editor application, Archy’s aspirations as a more complete all-purpose environment were evident. In particular, in addition to many of the same commands we saw on the Mac, there were now special Internet-oriented commands like EMAIL and GOOGLE. These commands were now just small documents containing Python embedded in the same workspace—no more separate files you had to corral. You could even change built-in commands, and even LEAP itself.

As you might expect, besides the deletion document (now just “DELETIONS”), things like your email were also now subdocuments, and your email server settings were a subdocument, too. While this was never said explicitly, a logical extension of the metaphor would have been to subsume webpage contents as in-place parts of the workspace as well—your history, bookmarks, and even the pages themselves could be subdocuments of their own, restored immediately and ready for access when entering Archy. Each time you exited, the entire workspace was saved out into a versioned file, so you could even go back in time to a recent backup if you blew it.

Raskin’s legacy

Raskin was found to have pancreatic cancer in December 2004 and, after transitioning the project to become Archy the following January, died shortly afterward on February 26, 2005. In Raskin’s New York Times obituary, Apple software designer Bill Atkinson lauded his work, saying, “He wanted to make them [computers] more usable and friendly to people who weren’t geeks.” Technology journalist Steven Levy agreed, adding that “[h]e really spent his life urging a degree of simplicity where computers would be not only easy to use but delightful.” He left behind his wife Linda Blum and his three children, Aza, Aviva, and Aenea.

Archy was the last project Raskin was directly involved in, and to date it remains unfinished. Some work continued on the environment after his death—this final release came out in December 2005, nearly 10 months later—but the project was ultimately abandoned, and many planned innovations, such as a ZUI of its own, were never fully developed beyond a separate proof of concept.

Similarly, many of Raskin’s more unique innovations have yet to reappear in modern mainstream interfaces. RCHI closed as well and was succeeded in spirit by the Chicago-based Humanized, co-founded by his son Aza. Humanized reworked ideas from Archy into Enso, which expanded the CAPS LOCK-as-command interface with a variety of verbs such as OPEN (to start applications) and DEFINE (to get the dictionary definition of a word), and the ability to perform direct web searches.

By using a system-wide translucent overlay similar to Archy and THE, the program was intended to minimize the need for switching back and forth between multiple applications to complete a task. In 2008, Enso was made free for download, and Humanized’s staff joined Mozilla, where the concept became a Firefox browser extension called Ubiquity, in which web-specific command verbs could be written in JavaScript and executed in an opaque pop-up window activated by a hotkey combination. However, the project was placed on “indefinite hiatus” in 2009 and was never revisited, and it no longer works with current versions of the browser.

Using Raskin 2 on a MacBook Air to browse images. Credit: Cameron Kaiser

The idea of a single workspace that you “leap through” also never resurfaced. Likewise, although ZUI-like animations have appeared more or less as eye candy in environments such as iOS and GNOME, a pervasive ZUI has yet to appear in (or as) any major modern desktop environment. That said, the idea is visually appealing, and some specific applications have made heavier use of the concept.

Microsoft’s 2007 Deepfish project for Windows Mobile conceived of visually shrunken webpages for mobile devices that users could zoom into, but it was dependent on a central server and had high bandwidth requirements, and Microsoft canceled it in 2008. A Swiss company named Raskin Software LLC (apparently no official relation) offers a macOS ZUI file and media browser called Raskin, which has free and paid tiers; on other platforms, the free open-source Eagle Mode project offers a similar file manager with media previews, but also a chess application, a fractal viewer, and even a Linux kernel configuration tool.

A2 desktop with installer, calendar and clock. Credit: LoganJustice via Wikimedia (CC0)

Perhaps the most complete example of an operating environment built around a ZUI might be A2, a branch of the ETH-Zürich Oberon System. The Oberon System, based around the Oberon programming language descended from Modula-2 and Pascal, was already notable for its unique paneled text user interface, where text is clickable, including text you type; Native Oberon can be booted directly as an operating system by itself.

In 2002, A2 spun off initially as Active Object System, using an updated dialect called Active Oberon supporting improved scheduling, exception handling, and object-oriented programming with processes and threads able to run within an object’s context to make that object “active.” While A2 kept the Oberon System’s clickable text metaphor, windows and gadgets can also be zoomed in or out of on an infinitely scrolling desktop, which is best appreciated in action. It is still being developed, and older live CDs are still available. However, the Oberon System has never achieved general market awareness beyond its small niche, and any forks less so, limiting it to a practical curiosity for most users.

This isn’t to say that Raskin’s quest for a truly humane computer has completely come to naught. Unfortunately, in some respects, we’re truly backsliding, with opaque operating systems that can limit your application choices or your ability to alter or customize them, and despite very public changes in skinning and aesthetics, the key ways that we interact with our computers have not substantially changed since the wide deployment of the Xerox PARC-derived “WIMP” paradigm (windows, icons, menus and pointers)—ironically most visibly promoted by the 1984 post-Raskin Macintosh.

A good interface unavoidably requires work and study, two things that take too long in today’s fast-paced product cycle. Furthermore, Raskin’s emphasis on built-in programmability nevertheless rings a bit quaint in our era, when many home users’ only computer may be a tablet. By his standards, there is little humane about today’s computers, and they may well be less humane than yesterday’s.

Nevertheless, while Raskin’s ideas may have few present-day implementations, that doesn’t mean the spirit in which they were proposed is dead, too. At the very least, some greater consideration is given to the traditional WIMP paradigm’s deficiencies today, particularly with multiple applications and windows, and how it can poorly serve some classes of users, such as those requiring assistive technology. That said, I hold guarded optimism about how much change we’ll see in mainstream systems, and Raskin’s editor-centric, application-less interface becomes more and more alien the more the current app ecosystem reigns dominant.

But as cul-de-sacs go, you can pick far worse places to get lost in than his, and it might even make it out to the main street someday. Until then, at least, you can always still visit—in an upcoming article, we’ll show you how.

Selected bibliography

Folklore.org

CanonCat.net

Linzmeyer, Owen W (2004). Apple Confidential 2.0. No Starch Press, San Francisco, CA.

Raskin, Jef (2000). The humane interface: new directions for designing interactive systems. Addison-Wesley, Boston, MA.

Making the Macintosh: Technology and Culture in Silicon Valley. https://web.stanford.edu/dept/SUL/sites/mac/earlymac.html

Canon’s Cat Computer: The Real Macintosh. https://www.landsnail.com/apple/local/cat/canon.html

Prototype to the Canon Cat: the “Swyft.” https://forum.vcfed.org/index.php?threads/prototype-to-the-canon-cat-the-swyft.12225/

Apple //e and Cat. http://www.regnirps.com/Apple6502stuff/apple_iie_cat.htm

Jef Raskin’s cul-de-sac and the quest for the humane computer Read More »

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OpenAI and Microsoft sign preliminary deal to revise partnership terms

On Thursday, OpenAI and Microsoft announced they have signed a non-binding agreement to revise their partnership, marking the latest development in a relationship that has grown increasingly complex as both companies compete for customers in the AI market and seek new partnerships for growing infrastructure needs.

“Microsoft and OpenAI have signed a non-binding memorandum of understanding (MOU) for the next phase of our partnership,” the companies wrote in a joint statement. “We are actively working to finalize contractual terms in a definitive agreement. Together, we remain focused on delivering the best AI tools for everyone, grounded in our shared commitment to safety.”

The announcement comes as OpenAI seeks to restructure from a nonprofit to a for-profit entity, a transition that requires Microsoft’s approval, as the company is OpenAI’s largest investor, with more than $13 billion committed since 2019.

The partnership has shown increasing strain as OpenAI has grown from a research lab into a company valued at $500 billion. Both companies now compete for customers, and OpenAI seeks more compute capacity than Microsoft can provide. The relationship has also faced complications over contract terms, including provisions that would limit Microsoft’s access to OpenAI technology once the company reaches so-called AGI (artificial general intelligence)—a nebulous milestone both companies now economically define as AI systems capable of generating at least $100 billion in profit.

In May, OpenAI abandoned its original plan to fully convert to a for-profit company after pressure from former employees, regulators, and critics, including Elon Musk. Musk has sued to block the conversion, arguing it betrays OpenAI’s founding mission as a nonprofit dedicated to benefiting humanity.

OpenAI and Microsoft sign preliminary deal to revise partnership terms Read More »

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Ousted CDC director to testify before Senate after RFK Jr. called her a liar

Kennedy is reportedly vetting seven additional members for ACIP, who may be added before the next meeting. They include additional anti-vaccine voices and fringe members of the medical community, such as Kirk Milhoan, who promoted the de-worming drug ivermectin to treat COVID-19, despite several clinical trials finding it is not effective. There is also Joseph Fraiman, who has repeatedly called for COVID-19 vaccines to be pulled from the market.

Also on the list is Catherine Stein, who, The Washington Post noted, has advocated against vaccine mandates and wrote a 2021 article arguing that people should not be afraid of contracting COVID-19 because: “Our Lord has given us a mission to share the gospel. If we live in fear of death, that weakens our testimony. Remember, the Lord Jesus did not fear lepers, and leprosy was (and continues to be) a highly contagious infectious disease.”

Leprosy, or Hansen’s disease, is, in fact, not a highly contagious disease. It does not spread easily from person to person, is not spread through casual contact, and about 95 percent of people are immune to it naturally. COVID-19, meanwhile, is estimated to have caused more than 7 million deaths worldwide since the start of the pandemic.

Regardless of whether these candidates are added to the roster, Cassidy has called for the ACIP meeting scheduled for September 18 and 19 to be postponed.

“Serious allegations have been made about the meeting agenda, membership, and lack of scientific process being followed for the now announced September ACIP meeting,” Cassidy said. “These decisions directly impact children’s health and the meeting should not occur until significant oversight has been conducted. If the meeting proceeds, any recommendations made should be rejected as lacking legitimacy given the seriousness of the allegations and the current turmoil in CDC leadership.”

After Monarez and Houry testify before the HELP committee, Cassidy said that Senators are planning to invite current health officials to respond in a subsequent hearing.

Ousted CDC director to testify before Senate after RFK Jr. called her a liar Read More »

microsoft-ends-openai-exclusivity-in-office,-adds-rival-anthropic

Microsoft ends OpenAI exclusivity in Office, adds rival Anthropic

Microsoft’s Office 365 suite will soon incorporate AI models from Anthropic alongside existing OpenAI technology, The Information reported, ending years of exclusive reliance on OpenAI for generative AI features across Word, Excel, PowerPoint, and Outlook.

The shift reportedly follows internal testing that revealed Anthropic’s Claude Sonnet 4 model excels at specific Office tasks where OpenAI’s models fall short, particularly in visual design and spreadsheet automation, according to sources familiar with the project cited by The Information, who stressed the move is not a negotiating tactic.

Anthropic did not immediately respond to Ars Technica’s request for comment.

In an unusual arrangement showing the tangled alliances of the AI industry, Microsoft will reportedly purchase access to Anthropic’s models through Amazon Web Services—both a cloud computing rival and one of Anthropic’s major investors. The integration is expected to be announced within weeks, with subscription pricing for Office’s AI tools remaining unchanged, the report says.

Microsoft maintains that its OpenAI relationship remains intact. “As we’ve said, OpenAI will continue to be our partner on frontier models and we remain committed to our long-term partnership,” a Microsoft spokesperson told Reuters following the report. The tech giant has poured over $13 billion into OpenAI to date and is currently negotiating terms for continued access to OpenAI’s models amid ongoing negotiations about their partnership terms.

Stretching back to 2019, Microsoft’s tight partnership with OpenAI until recently gave the tech giant a head start in AI assistants based on language models, allowing for a rapid (though bumpy) deployment of OpenAI-technology-based features in Bing search and the rollout of Copilot assistants throughout its software ecosystem. It’s worth noting, however, that a recent report from the UK government found no clear productivity boost from using Copilot AI in daily work tasks among study participants.

Microsoft ends OpenAI exclusivity in Office, adds rival Anthropic Read More »

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Pay-per-output? AI firms blindsided by beefed up robots.txt instructions.


“Really Simple Licensing” makes it easier for creators to get paid for AI scraping.

Logo for the “Really Simply Licensing” (RSL) standard. Credit: via RSL Collective

Leading Internet companies and publishers—including Reddit, Yahoo, Quora, Medium, The Daily Beast, Fastly, and more—think there may finally be a solution to end AI crawlers hammering websites to scrape content without permission or compensation.

Announced Wednesday morning, the “Really Simply Licensing” (RSL) standard evolves robots.txt instructions by adding an automated licensing layer that’s designed to block bots that don’t fairly compensate creators for content.

Free for any publisher to use starting today, the RSL standard is an open, decentralized protocol that makes clear to AI crawlers and agents the terms for licensing, usage, and compensation of any content used to train AI, a press release noted.

The standard was created by the RSL Collective, which was founded by Doug Leeds, former CEO of Ask.com, and Eckart Walther, a former Yahoo vice president of products and co-creator of the RSS standard, which made it easy to syndicate content across the web.

Based on the “Really Simply Syndication” (RSS) standard, RSL terms can be applied to protect any digital content, including webpages, books, videos, and datasets. The new standard supports “a range of licensing, usage, and royalty models, including free, attribution, subscription, pay-per-crawl (publishers get compensated every time an AI application crawls their content), and pay-per-inference (publishers get compensated every time an AI application uses their content to generate a response),” the press release said.

Leeds told Ars that the idea to use the RSS “playbook” to roll out the RSL standard arose after he invited Walther to speak to University of California, Berkeley students at the end of last year. That’s when the longtime friends with search backgrounds began pondering how AI had changed the search industry, as publishers today are forced to compete with AI outputs referencing their own content as search traffic nosedives.

Eckart had watched the RSS standard quickly become adopted by millions of sites, and he realized that RSS had actually always been a licensing standard, Leeds said. Essentially, by adopting the RSS standard, publishers agreed to let search engines license a “bit” of their content in exchange for search traffic, and Eckart realized that it could be just as straightforward to add AI licensing terms in the same way. That way, publishers could strive to recapture lost search revenue by agreeing to license all or some part of their content to train AI in return for payment each time AI outputs link to their content.

Leeds told Ars that the RSL standard doesn’t just benefit publishers, though. It also solves a problem for AI companies, which have complained in litigation over AI scraping that there is no effective way to license content across the web.

“We have listened to them, and what we’ve heard them say is… we need a new protocol,” Leeds said. With the RSL standard, AI firms get a “scalable way to get all the content” they want, while setting an incentive that they’ll only have to pay for the best content that their models actually reference.

“If they’re using it, they pay for it, and if they’re not using it, they don’t pay for it,” Leeds said.

No telling yet how AI firms will react to RSL

At this point, it’s hard to say if AI companies will embrace the RSL standard. Ars reached out to Google, Meta, OpenAI, and xAI—some of the big tech companies whose crawlers have drawn scrutiny—to see if it was technically feasible to pay publishers for every output referencing their content. xAI did not respond, and the other companies declined to comment without further detail about the standard, appearing to have not yet considered how a licensing layer beefing up robots.txt could impact their scraping.

Today will likely be the first chance for AI companies to wrap their heads around the idea of paying publishers per output. Leeds confirmed that the RSL Collective did not consult with AI companies when developing the RSL standard.

But AI companies know that they need a constant stream of fresh content to keep their tools relevant and to continually innovate, Leeds suggested. In that way, the RSL standard “supports what supports them,” Leeds said, “and it creates the appropriate incentive system” to create sustainable royalty streams for creators and ensure that human creativity doesn’t wane as AI evolves.

While we’ll have to wait to see how AI firms react to RSL, early adopters of the standard celebrated the launch today. That included Neil Vogel, CEO of People Inc., who said that “RSL moves the industry forward—evolving from simply blocking unauthorized crawlers, to setting our licensing terms, for all AI use cases, at global web scale.”

Simon Wistow, co-founder of Fastly, suggested the solution “is a timely and necessary response to the shifting economics of the web.”

“By making it easy for publishers to define and enforce licensing terms, RSL lays the foundation for a healthy content ecosystem—one where innovation and investment in original work are rewarded, and where collaboration between publishers and AI companies becomes frictionless and mutually beneficial,” Wistow said.

Leeds noted that a key benefit of the RSL standard is that even small creators will now have an opportunity to generate revenue for helping to train AI. Tony Stubblebine, CEO of Medium, did not mince words when explaining the battle that bloggers face as AI crawlers threaten to divert their traffic without compensating them.

“Right now, AI runs on stolen content,” Stubblebine said. “Adopting this RSL Standard is how we force those AI companies to either pay for what they use, stop using it, or shut down.”

How will the RSL standard be enforced?

On the RSL standard site, publishers can find common terms to add templated or customized text to their robots.txt files to adopt the RSL standard today and start protecting their content from unfettered AI scraping. Here’s an example of how machine-readable licensing terms could look, added directly to robots.txt files:

# NOTICE: all crawlers and bots are strictly prohibited from using this

# content for AI training without complying with the terms of the RSL

# Collective AI royalty license. Any use of this content for AI training

# without a license is a violation of our intellectual property rights.

License: https://rslcollective.org/royalty.xml

Through RSL terms, publishers can automate licensing, with the cloud company Fastly partnering with the collective to provide technical enforcement that Leeds described as tech that acts as a bouncer to keep unapproved bots away from valuable content. It seems likely that Cloudflare, which launched a pay-per-crawl program blocking greedy crawlers in July, could also help enforce the RSL standard.

For publishers, the standard “solves a business problem immediately,” Leeds told Ars, so the collective is hopeful that RSL will be rapidly and widely adopted. As further incentive, publishers can also rely on the RSL standard to “easily encrypt and license non-published, proprietary content to AI companies, including paywalled articles, books, videos, images, and data,” the RSL Collective site said, and that potentially could expand AI firms’ data pool.

On top of technical enforcement, Leeds said that publishers and content creators could legally enforce the terms, noting that the recent $1.5 billion Anthropic settlement suggests “there’s real money at stake” if you don’t train AI “legitimately.”

Should the industry adopt the standard, it could “establish fair market prices and strengthen negotiation leverage for all publishers,” the press release said. And Leeds noted that it’s very common for regulations to follow industry solutions (consider the Digital Millennium Copyright Act). Since the RSL Collective is already in talks with lawmakers, Leeds thinks “there’s good reason to believe” that AI companies will soon “be forced to acknowledge” the standard.

“But even better than that,” Leeds said, “it’s in their interest” to adopt the standard.

With RSL, AI firms can license content at scale “in a way that’s fair [and] preserves the content that they need to make their products continue to innovate.”

Additionally, the RSL standard may solve a problem that risks gutting trust and interest in AI at this early stage.

Leeds noted that currently, AI outputs don’t provide “the best answer” to prompts but instead rely on mashing up answers from different sources to avoid taking too much content from one site. That means that not only do AI companies “spend an enormous amount of money on compute costs to do that,” but AI tools may also be more prone to hallucination in the process of “mashing up” source material “to make something that’s not the best answer because they don’t have the rights to the best answer.”

“The best answer could exist somewhere,” Leeds said. But “they’re spending billions of dollars to create hallucinations, and we’re talking about: Let’s just solve that with a licensing scheme that allows you to use the actual content in a way that solves the user’s query best.”

By transforming the “ecosystem” with a standard that’s “actually sustainable and fair,” Leeds said that AI companies could also ensure that humanity never gets to the point where “humans stop producing” and “turn to AI to reproduce what humans can’t.”

Failing to adopt the RSL standard would be bad for AI innovation, Leeds suggested, perhaps paving the way for AI to replace search with a “sort of self-fulfilling swap of bad content that actually one doesn’t have any current information, doesn’t have any current thinking, because it’s all based on old training information.”

To Leeds, the RSL standard is ultimately “about creating the system that allows the open web to continue. And that happens when we get adoption from everybody,” he said, insisting that “literally the small guys are as important as the big guys” in pushing the entire industry to change and fairly compensate creators.

Photo of Ashley Belanger

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Pay-per-output? AI firms blindsided by beefed up robots.txt instructions. Read More »

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Reddit bug caused lesbian subreddit to be labeled as a place for “straight” women

Explaining further to Ars, Reddit spokesperson Tim Rathschmidt said:

There was a small bug in a test we ran that mistakenly caused the English-to-English translation(s) you saw. That bug has been resolved. Unsurprisingly, English-to-English translations are not part of our strategy, as they aren’t necessary. English-to-English translations were not a desired or expected outcome of the test.

Reddit pulled the test it was running, but its machine learning-powered translations are still functioning, Rathschmidt said. The company plans to fix the bug and run its unspecified “test” again.

Reddit’s explanation differs from user theories floating around beforehand, which were mainly that Reddit was rewriting user-created summaries with generative AI, possibly to boost SEO. Some may still be perturbed by the problem persisting for weeks without explanation and the apparent lack of manual checks for the translation service. However, Redditors can now take comfort in knowing that Reddit is not currently using generative AI to alter user-generated content without notice.

Paige_Railstone, however, maintains frustration and wants to tell Reddit admins, “STOP. Hand off.” The translation bug, they noted, led to people posting on a subreddit for parents with autism that their child might be autistic, “and how terrible that would be for them,” Paige_Railstone recalled.

“These are the kind of unintentionally insulting posts that drive autistics into leaving a community, and it increases the workload of us moderators,” they said.

Paige_Railstone also sees the incident as a reason for moderators to be more cautious.

“This never used to be a concern, but this translation service was rolled out without any notification that I’m aware of, and no option to disable it within the mods’ control. That has the potential to cause problems, as we’ve seen over the past two weeks,” they said.

Disclosure: Advance Publications, which owns Ars Technica parent Condé Nast, is the largest shareholder in Reddit.

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girlsdoporn-owner-michael-pratt-gets-27-years-for-sex-trafficking-conspiracy

GirlsDoPorn owner Michael Pratt gets 27 years for sex trafficking conspiracy

“For almost a decade, the Defendant led the scheme to systematically coerce and defraud women into engaging in filmed sexual activity for profit,” the sentencing recommendation said. “A sentence of 260 months is warranted, given the longevity of the scheme, the amount of profit, and the extent of the damage to the victims.”

Pratt’s plea agreement limited his rights to appeal the sentencing, but said he “may appeal a custodial sentence above 260 months.” The 27-year (324-month) sentence exceeds that. While the government agreed to recommend no more than 260 months, the plea agreement said the government “may support on appeal the sentence or restitution order actually imposed.”

Pratt fled the US in 2019, shortly before being charged with sex trafficking crimes. “He was named to the FBI’s Ten Most Wanted list and lived as an international fugitive for more than three years until his arrest in Spain in December 2022 and extradition to San Diego in March 2024,” the DOJ said.

Pratt tried to minimize his role

Pratt is the fourth person to be sentenced in the GirlsDoPorn case. Pratt’s business partner, Matthew Wolfe, received 14 years. Ruben Andre Garcia was sentenced to 20 years, and Theodore Gyi was sentenced to four years. Defendant Valorie Moser is scheduled to be sentenced on Friday this week.

Pratt’s sentencing memorandum tried to minimize his role in the conspiracy. “Circa 2014, Mr. Pratt’s childhood friend, Matt Wolfe, took over as the cameraman and Mr. Pratt spent more time in the office doing post-production work and other business related activities,” the filing said.

Pratt argued that Garcia exhibited “erratic and unpredictable” behavior and that “much of this conduct occurred outside of Mr. Pratt’s presence.” Pratt’s filing said he should not receive a sentence as long as Garcia’s.

Garcia “was a rapist,” Pratt’s filing said. “Mr. Pratt had no involvement in Garcia’s sexual activities with the models before or after filming, nor did he condone it. When he received some complaints about Garcia’s behavior, Mr. Pratt took precautions to ensure the safety of the models, including setting up nanny video cameras, securing hotel incidental refrigerators, and ensuring everyone left the hotel as a group.”

The government’s sentencing memorandum described Pratt as “the ringleader in a wide-ranging sex-trafficking conspiracy during which many women were defrauded into engaging in sex acts on camera, destroying many of their lives.” The “scheme would never have occurred” if not for Pratt’s actions, “and hundreds of women would not have been victimized,” the government filing said.

GirlsDoPorn owner Michael Pratt gets 27 years for sex trafficking conspiracy Read More »

why-accessibility-might-be-ai’s-biggest-breakthrough

Why accessibility might be AI’s biggest breakthrough

For those with visual impairments, language models can summarize visual content and reformat information. Tools like ChatGPT’s voice mode with video and Be My Eyes allow a machine to describe real-world visual scenes in ways that were impossible just a few years ago.

AI language tools may be providing unofficial stealth accommodations for students—support that doesn’t require formal diagnosis, workplace disclosure, or special equipment. Yet this informal support system comes with its own risks. Language models do confabulate—the UK Department for Business and Trade study found 22 percent of users identified false information in AI outputs—which could be particularly harmful for users relying on them for essential support.

When AI assistance becomes dependence

Beyond the workplace, the drawbacks may have a particular impact on students who use the technology. The authors of a 2025 study on students with disabilities using generative AI cautioned, “Key concerns students with disabilities had included the inaccuracy of AI answers, risks to academic integrity, and subscription cost barriers,” they wrote. Students in that study had ADHD, dyslexia, dyspraxia, and autism, with ChatGPT being the most commonly used tool.

Mistakes in AI outputs are especially pernicious because, due to grandiose visions of near-term AI technology, some people think today’s AI assistants can perform tasks that are actually far outside their scope. As research on blind users’ experiences suggested, people develop complex (sometimes flawed) mental models of how these tools work, showing the need for higher awareness of AI language model drawbacks among the general public.

For the UK government employees who participated in the initial study, these questions moved from theoretical to immediate when the pilot ended in December 2024. After that time, many participants reported difficulty readjusting to work without AI assistance—particularly those with disabilities who had come to rely on the accessibility benefits. The department hasn’t announced the next steps, leaving users in limbo. When participants report difficulty readjusting to work without AI while productivity gains remain marginal, accessibility emerges as potentially the first AI application with irreplaceable value.

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