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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

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Spotify peeved after 10,000 users sold data to build AI tools


Spotify sent a warning to stop data sales, but developers say they never got it.

For millions of Spotify users, the “Wrapped” feature—which crunches the numbers on their annual listening habits—is a highlight of every year’s end, ever since it debuted in 2015. NPR once broke down exactly why our brains find the feature so “irresistible,” while Cosmopolitan last year declared that sharing Wrapped screenshots of top artists and songs had by now become “the ultimate status symbol” for tens of millions of music fans.

It’s no surprise then that, after a decade, some Spotify users who are especially eager to see Wrapped evolve are no longer willing to wait to see if Spotify will ever deliver the more creative streaming insights they crave.

With the help of AI, these users expect that their data can be more quickly analyzed to potentially uncover overlooked or never-considered patterns that could offer even more insights into what their listening habits say about them.

Imagine, for example, accessing a music recap that encapsulates a user’s full listening history—not just their top songs and artists. With that unlocked, users could track emotional patterns, analyzing how their music tastes reflected their moods over time and perhaps helping them adjust their listening habits to better cope with stress or major life events. And for users particularly intrigued by their own data, there’s even the potential to use AI to cross data streams from different platforms and perhaps understand even more about how their music choices impact their lives and tastes more broadly.

Likely just as appealing as gleaning deeper personal insights, though, users could also potentially build AI tools to compare listening habits with their friends. That could lead to nearly endless fun for the most invested music fans, where AI could be tapped to assess all kinds of random data points, like whose breakup playlists are more intense or who really spends the most time listening to a shared favorite artist.

In pursuit of supporting developers offering novel insights like these, more than 18,000 Spotify users have joined “Unwrapped,” a collective launched in February that allows them to pool and monetize their data.

Voting as a group through the decentralized data platform Vana—which Wired profiled earlier this year—these users can elect to sell their dataset to developers who are building AI tools offering fresh ways for users to analyze streaming data in ways that Spotify likely couldn’t or wouldn’t.

In June, the group made its first sale, with 99.5 percent of members voting yes. Vana co-founder Anna Kazlauskas told Ars that the collective—at the time about 10,000 members strong—sold a “small portion” of its data (users’ artist preferences) for $55,000 to Solo AI.

While each Spotify user only earned about $5 in cryptocurrency tokens—which Kazlauskas suggested was not “ideal,” wishing the users had earned about “a hundred times” more—she said the deal was “meaningful” in showing Spotify users that their data “is actually worth something.”

“I think this is what shows how these pools of data really act like a labor union,” Kazlauskas said. “A single Spotify user, you’re not going to be able to go say like, ‘Hey, I want to sell you my individual data.’ You actually need enough of a pool to sort of make it work.”

Spotify sent warning to Unwrapped

Unsurprisingly, Spotify is not happy about Unwrapped, which is perhaps a little too closely named to its popular branded feature for the streaming giant’s comfort. A spokesperson told Ars that Spotify sent a letter to the contact info listed for Unwrapped developers on their site, outlining concerns that the collective could be infringing on Spotify’s Wrapped trademark.

Further, the letter warned that Unwrapped violates Spotify’s developer policy, which bans using the Spotify platform or any Spotify content to build machine learning or AI models. And developers may also be violating terms by facilitating users’ sale of streaming data.

“Spotify honors our users’ privacy rights, including the right of portability,” Spotify’s spokesperson said. “All of our users can receive a copy of their personal data to use as they see fit. That said, UnwrappedData.org is in violation of our Developer Terms which prohibit the collection, aggregation, and sale of Spotify user data to third parties.”

But while Spotify suggests it has already taken steps to stop Unwrapped, the Unwrapped team told Ars that it never received any communication from Spotify. It plans to defend users’ right to “access, control, and benefit from their own data,” its statement said, while providing reassurances that it will “respect Spotify’s position as a global music leader.”

Unwrapped “does not distribute Spotify’s content, nor does it interfere with Spotify’s business,” developers argued. “What it provides is community-owned infrastructure that allows individuals to exercise rights they already hold under widely recognized data protection frameworks—rights to access their own listening history, preferences, and usage data.”

“When listeners choose to share or monetize their data together, they are not taking anything away from Spotify,” developers said. “They are simply exercising digital self-determination. To suggest otherwise is to claim that users do not truly own their data—that Spotify owns it for them.”

Jacob Hoffman-Andrews, a senior staff technologist for the digital rights group the Electronic Frontier Foundation, told Ars that—while EFF objects to data dividend schemes “where users are encouraged to share personal information in exchange for payment”—Spotify users should nevertheless always maintain control of their data.

“In general, listeners should have control of their own data, which includes exporting it for their own use,” Hoffman-Andrews said. “An individual’s musical history is of use not just to Spotify but also to the individual who created it. And there’s a long history of services that enable this sort of data portability, for instance Last.fm, which integrates with Spotify and many other services.”

To EFF, it seems ill-advised to sell data to AI companies, Hoffman-Andrews said, emphasizing “privacy isn’t a market commodity, it’s a fundamental right.”

“Of course, so is the right to control one’s own data,” Hoffman-Andrews noted, seeming to agree with Unwrapped developers in concluding that “ultimately, listeners should get to do what they want with their own information.”

Users’ right to privacy is the primary reason why Unwrapped developers told Ars that they’re hoping Spotify won’t try to block users from selling data to build AI.

“This is the heart of the issue: If Spotify seeks to restrict or penalize people for exercising these rights, it sends a chilling message that its listeners should have no say in how their own data is used,” the Unwrapped team’s statement said. “That is out of step not only with privacy law, but with the values of transparency, fairness, and community-driven innovation that define the next era of the Internet.”

Unwrapped sign-ups limited due to alleged Spotify issues

There could be more interest in Unwrapped. But Kazlauskas alleged to Ars that in the more than six months since Unwrapped’s launch, “Spotify has made it extraordinarily difficult” for users to port over their data. She claimed that developers have found that “every time they have an easy way for users to get their data,” Spotify shuts it down “in some way.”

Supposedly because of Spotify’s interference, Unwrapped remains in an early launch phase and can only offer limited spots for new users seeking to sell their data. Kazlauskas told Ars that about 300 users can be added each day due to the cumbersome and allegedly shifting process for porting over data.

Currently, however, Unwrapped is working on an update that could make that process more stable, Kazlauskas said, as well as changes to help users regularly update their streaming data. Those updates could perhaps attract more users to the collective.

Critics of Vana, like TechCrunch’s Kyle Wiggers, have suggested that data pools like Unwrapped will never reach “critical mass,” likely only appealing to niche users drawn to decentralization movements. Kazlauskas told Ars that data sale payments issued in cryptocurrency are one barrier for crypto-averse or crypto-shy users interested in Vana.

“The No. 1 thing I would say is, this kind of user experience problem where when you’re using any new kind of decentralized technology, you need to set up a wallet, then you’re getting tokens,” Kazlauskas explained. Users may feel culture shock, wondering, “What does that even mean? How do I vote with this thing? Is this real money?”

Kazlauskas is hoping that Vana supports a culture shift, striving to reach critical mass by giving users a “commercial lens” to start caring about data ownership. She also supports legislation like the Digital Choice Act in Utah, which “requires actually real-time API access, so people can get their data.” If the US had a federal law like that, Kazlauskas suspects that launching Unwrapped would have been “so much easier.”

Although regulations like Utah’s law could serve as a harbinger of a sea change, Kazlauskas noted that Big Tech companies that currently control AI markets employ a fierce lobbying force to maintain control over user data that decentralized movements just don’t have.

As Vana partners with Flower AI, striving, as Wired reported, to “shake up the AI industry” by releasing “a giant 100 billion-parameter model” later this year, Kazlauskas remains committed to ensuring that users are in control and “not just consumed.” She fears a future where tech giants may be motivated to use AI to surveil, influence, or manipulate users, when instead users could choose to band together and benefit from building more ethical AI.

“A world where a single company controls AI is honestly really dystopian,” Kazlauskas told Ars. “I think that it is really scary. And so I think that the path that decentralized AI offers is one where a large group of people are still in control, and you still get really powerful technology.”

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.

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Tiny Vinyl is a new pocketable record format for the Spotify age


Format is “more aligned with how artists are making and releasing music in the streaming era.”

In 2019, Record Store Day partnered with manufacturer Crosley to revive a 3-inch collectible vinyl format first launched in Japan in 2004. Five years later, a new 4-inch-sized format called Tiny Vinyl wants to take the miniature vinyl collectible crown, and launch partner Target is throwing its considerable weight behind it as an exclusive launch partner, with 44 titles expected in the coming weeks.

It’s 2025, and the global vinyl record market has reached $2 billion in annual sales and is still growing at roughly 7 percent annually, according to market research firm Imarc. Vinyl record sales now account for over 50 percent of physical media sales for music (and this is despite a recent resurgence in both cassette and CD sales among Millennials). It’s in this landscape that Tiny Vinyl founders Neil Kohler and Jesse Mann decided to come up with a fun new collectible vinyl format.

An “aha” moment

Kohler’s day job is working with toy companies to develop and market their ideas. He was involved in helping Funko popularize its stylized vinyl figurines, now a ubiquitous presence at pop culture conventions, comic book stores, and toy shops of all kinds. Mann has worked in production, marketing, and the music business for nearly three decades, including a stint at LiveNation and years of running operations for the annual summer music festival Bonnaroo. Both men are based in Nashville—Music City, USA—and the proximity to one of the main centers of the music industry clearly had an impact.

In 2023, Kohler bumped into Drake Coker, CEO and general manager of Nashville Record Pressing, a newer vinyl manufacturing plant that opened in 2021.

“Would it be possible to make a real vinyl record that is small enough to fit inside the box with a Funko Pop, so roughly four inches in diameter?” Kohler asked Coker at the time.

Coker was convinced it was possible to do so. “It took quite a lot of energy to do the R&D and for Drake’s company to figure out how to do that in a technical sense,” Kohler explained to Ars. “It became evident very quickly that this was a really cool thing on its own, and it didn’t need to come in a Funko box,” Kohler told Ars. “As long as we made it authentic to what a standard 12-inch record would be, with sound, and art, and center labels, just miniaturized.”

That’s when Kohler contacted Mann to develop a strategy and make Tiny Vinyl its own unique collectible.

“The first prototype samples started coming out of production in May 2024, and we delivered the first Tiny Vinyl release to country musician Daniel Donato in July 2024,” Mann told Ars. “He took them out on tour, and the fan reaction gave us a sort of wind in the sails, that this would be something that fans would really love,” he said.

Of course, Record Store Day already has a small collectible vinyl format, and the Tiny Vinyl team became aware of it from the moment they started looking at the market.

“The Crosley 3-inch record player is both inspiring but also a different direction than what we wanted.” Kohler explained. “Crosley makes that as more of a promotional tool, to seed their record player business, and it’s this one-side piece that only plays on their miniature players,” Kohler said. “But here we’re focusing on something more, a two-sided piece that could play on any standard turntable.”

“Tiny Vinyl is a different concept. We’re basically trying, and having quite a bit of success, in creating a new vinyl format,” Coker said, “one that is more aligned with how artists are making and releasing music in the streaming era.”

How records are made

The basic process to press a vinyl record starts with cutting a lacquer master. A specially made disc of rather fragile lacquer is put on a cutting lathe—which looks sort of like an industrial turntable—and the audio signals are converted into mechanical movement in its cutting head. That movement is carved into fine grooves in the lacquer, creating the lacquer master.

The lacquer master is electroplated with a nickel alloy, creating a negative metal image of the grooves in the lacquer, called a “father.” This thin, relatively fragile metal negative is this electroplated again with a strong copper-based alloy, creating a new positive image called a “mother.” The mother is plated yet again, creating negative-image “stampers.” Once stampers are made for each side, they are mounted into a hydraulic press for stamping out records.

When a press is ready, polyvinyl chloride (PVC) pellets are placed in a hopper and heated to around 250º F and typically extruded into a roughly 4-inch-diameter-thick disc called a “biscuit.” The biscuit is inserted into the press, with paper labels on each side, and the press uses anywhere from 100 to 150 tons of pressure to press a record. (Notably, heat and pressure adhere the labels to the record, not adhesive.)

Finally, the excess vinyl is trimmed off the edges (and often remelted and reused, especially in “eco” vinyl), and the finished records are stacked with metal plates to help cool off the hot vinyl and keep the records flat. All that has to be done while maintaining temperature and humidity to proper levels and keeping dust as far away from the stampers as possible.

To play a record, the turntable turns at a constant rotation speed, and a microscopic piece of diamond in the turntable’s stylus tracks the grooves and translates peaks and valleys into mechanical movement in the stylus. The stylus is connected to a cartridge, which converts the tiny mechanical movements into an electrical signal by moving tiny magnets within a coil. That signal is amplified twice—all turntables use a pre-amp to convert the audio signals to standard audio line-level, and then some other component (receiver, integrated amplifier, or something built-in to powered speakers) amplifies the signal to play back via speakers.

So the manufacturing process relies on the precision of multiple generations of mechanical copying before stamping out microscopic grooves into a relatively inexpensive material, and then, during playback, it depends on multiple steps of amplifying those microscopic grooves before you hear a single note of music. Every step along the way increases the chance that noise or other issues can affect what you hear.

Tiny Vinyl has some advantage here because Nashville Record Pressing is part of GZ Media. Before vinyl started its resurgence in 2007, many vinyl pressing plants closed, and the presses and other machinery were often discarded, with the metal being reused to make other machines. As vinyl manufacturing surged, there were few sources for the presses and other equipment to press records, and GZ’s size amplified those challenges.

“You know, GZ is based in the Czech Republic and is the oldest, largest manufacturer in the world,” Coker said. “And we’ve got very significant resources. I think what people don’t recognize is the depth and breadth of our technical resources. For instance, we’ve been making our own vinyl presses in the Czech Republic for over a decade now,” Coker told Ars. “So we can control every step of the process, from extruding PVC, pressing records, inserting them into sleeves, everything. We had to figure out how to do all that, but in miniature,” Coker said.

“There’s a lot of engineering, and there’s also kind of a lot of secret sauce in this,” Coker said. “So we’re a bit tight-lipped about how this is different. I’m very cryptic, but I will say that there are issues with PVC compound, there are issues with mastering, there are issues with plating, there are issues with pressing, there are issues with label application. It is definitely a challenge to make the sleeves and jackets at this size, get everything all assembled and get it wrapped, and get some stickers on it and have it look good. Some of those challenges are bigger than others, but we feel pretty good that we’ve had the time to really do the work that was necessary to figure this out.”

Challenges in manufacturing are also compounded by playback. As a turntable’s stylus moves closer to the center of a record, the linear speed decreases, which impacts playback quality. The angle of the stylus can also affect how well grooves are tracked, again impacting playback quality.

“S​​o it’s a game about how to stay inside the manufacturing and playback infrastructure that exists,” Coker continued. “And to get something to work with a linear speed that’s never been tried before, right? And so what’s come out of that is a disc that we’re certainly very proud of,” he said.

Furthermore, 4-inch vinyl records are almost the exact size of the label on an LP or 7-inch single, so automatic turntables won’t work. If you want to play Tiny Vinyl at home, you’ll need a manual turntable or one that allows turning off auto stop and start. The good news is that the majority of turntables in use are manual. But some of the most popular entry-level models, such as Audio-Technica’s LP60-series, are strictly automatic.

That may change in the future. “We’re in touch with turntable manufacturers, and some have expressed an interest in making sure they are compatible with Tiny Vinyl,” Kohler told Ars. But that is likely contingent on the format selling in big numbers.

All aboard the Tiny Vinyl train

“We will make Tiny Vinyl for anyone, any artist or label that brings us music they have the rights to, and they can distribute that however they want,” Kohler told Ars. “Some people are using their own direct-to-consumer websites. Some other artists are doing it on tour, at merch tables. There is a Lindsay Sterling title that was the first Tiny Vinyl that was available at retail at Urban Outfitters.”

But for now, the big push is with the upcoming launch with Target, and so far, existing collectors are curious.

A sampling of the first batch of records. Credit: Chris Foresman

“I absolutely adore these 4-inch records,” Christina Stroven, an avid record collector from Arkansas, told Ars. “I think they’ll be super fun to collect and bring back all of the nostalgia of the cassette singles from the ’80s and ’90s,” she said, noting that she has over 1,500 records in her collection already.

“It is nice to have another format that still works on my turntable. I will for sure be picking up the Alessia Cara ‘Here’/’Scars To Your Beautiful’ single and The Rolling Stones and Kasey Musgraves, too.” Stroven said.

“I’ve already pre-ordered two Tiny Vinyl records,” Fred Whitacre Jr, a teacher, drummer, and record collector from Warren, Ohio, said. “But, I don’t think it’s something I’m going to delve very heavily into. I always like when vinyl pressings try something new, but for me, I’m probably going to stick with LPs and 45s.”

For Tiny Vinyl, this is really just the beginning. “This launch is being driven by Target,” Kohler noted. “It’s mostly because of my background in the toy industry. When I talked to the management team at Target, they said, ‘You know, let’s try and do something here, and we’ll help organize the labels.’”

Target already has relationships with major record labels, which have supplied the company with exclusive album variants in the past. “Really, the labels are supplying what Target is asking for, and we’re supplying the labels,” Kohler said.

And all this is to help establish Tiny Vinyl as a standard format. “We just wanted to get the ball rolling and make sure this is a success,” Kohler added. “We’ve been contacted by Barnes and Noble, and Walmart, and Best Buy, and other retailers. But Target jumped in with both feet.”

What does Crosley think about a new, potentially competing small vinyl format?

“I’m glad they’re doing it,” Scott Bingaman, owner of Crosley distributor Deer Park Distributors. “We’re still working on some great Record Store Day releases for 3-inch vinyl, but I’m rooting for these guys. I understand you have to pick a channel, and they went with the one that was most willing to step up. I hope distribution widens up because for me the definition of success is kids standing in line overnight at a record store, getting physical media.”

And will independent labels consider the format despite its relatively high price? That may depend on the audience.

Revelation Records, which specializes in hardcore and punk music, has a catalog that stretches back into the early days of straight edge and New York hardcore from the late ’80s. Founder Jordan Cooper thinks the format sounds interesting.

“This is still in the novelty realm, obviously, but seems like it could be a good merch item for bands to do,” he told Ars.

The vast majority of records sold are 12-inch LPs, but in the punk and indie scenes, a 7-inch EP is usually a cheaper way to get typically two to four songs to fans. A 4-inch single limits that to two relatively short songs, but again, the size and novelty factor could attract some buyers.

“I think as a fan, if I saw a band and song or two I liked on one of these, I might be motivated to pick it up,” Cooper said. “The price is really high for what you get, but at the same time, even 7-inches are pushing up over $10 now.”

Reminds one of a stack of CDs. Credit: Chris Foresman

With production capacity at full blast for the rollout with Target, though, Tiny Vinyl currently requires a minimum order of 2,000 units. That just isn’t financially feasible unless a band already has a large enough fan base to support it.

“Three-inch records are kind of a gimmick, and I feel the same about this format,” Carl Zenobi, owner of small, Pennsylvania-based indie label Powertone Records, told Ars. “I could see younger music fans seeing this at a merch table and thinking it’s cool, so that would be a plus if it draws younger fans into record collecting.”

“But from my reading, this is meant for bigger artists on major labels and not independent artists,” Zenobi said. Powertone has sold several short-run 3-inch lathe-cut releases in the past couple years, but quantities are typically in the dozens.

“For me and the artists I work with, we would be looking at 100 to maybe 300 units,” Zenobi explained. “For the amount of money that 2,000 units would likely cost, you might as well have a full LP pressed!”

Still, some artists have already had early success with the format. Alt-country-folk duo The Band Loula, who recently signed with Warner Nashville in 2024, has only released a handful of singles so far, primarily via streaming. But the group decided to try Tiny Vinyl for their songs “Running Off The Angels” and “Can’t Please ’Em All” earlier this year.

“We heard about Tiny Vinyl through our manager, and we thought it was a great idea since we’re still in more of a single release strategy,” Malachi Mills, one-half of The Band Loula, told Ars.

The band just got off a 34-show tour with country star Dierks Bentley that kicked off in May, and with nowhere near enough songs for an album, they decided to make a Tiny Vinyl to take on tour.

“We don’t have an album, but we have a few singles, so we said, ‘Let’s take our two favorite songs and put them on there,’” Mills said. We sell them for $15 at our merch booth, and for people that don’t have enough money to buy a shirt, they can still walk away with something really cool.”

“We’re a new band, the opening act, so I think people are still catching on to our merchandise,” Logan Simmons, The Band Loula’s other singer-songwriter half, explained. “People are definitely using the Tiny Vinyl to kind of capture a moment in time. Everybody wants us to sign them, and some fans told us they want to frame it, to frame the vinyl itself.”

“We watched our sales grow every night, and every date we played it felt like we were receiving more and more positive feedback,” Simmons said. “I think the Tiny Vinyl definitely had something to do with that.”

Overall, the band—and its fans—seem pleased with the results so far. “We’re also excited to see how they sell in different forums—we think they’ll sell even better in clubs and theaters,” Mills said. “As long as people keep buying them, we’ll keep making them. It sounds great, and seeing that tiny little thing on a full-size record player, you just think, ‘That’s really cool, man,’”

Here is where some of the differences in approach give Tiny Vinyl an advantage for record labels and bands to produce something to get into fans’ hands. Three-inch vinyl started as a kitschy toy for Japanese youth, and the format is only made by Toyokasei in Japan in partnership with Record Store Day. That means releases are limited to what can be pressed by Toyokasei and marketed by RSD.

Tiny Vinyl, on the other hand, has access to all of GZ Media’s pressing plants in Europe, the US, and Canada. So there is capacity to meet the demands of both independent and major labels.

But like The Band Loula discovered, Tiny Vinyl also aligns more with how artists are releasing music.

“A lot of data was supporting a surge in vinyl sales over the last 10 years,” Kohler explained. “So we really wanted to capture something that made vinyl a lot more digestible for the typical listener. I mean, I love vinyl. I grew up playing Dark Side of the Moon for like two weeks at a time, right? But few people are listening to a 12-inch vinyl from start to finish anymore. They’re listening to Spotify for 10 seconds and then they’re moving on.”

“So artists today, they don’t have to wait to accumulate, to write, produce, and master 10 or 12 songs to be able to start getting vinyl into the marketplace,” Coker said. “If they’ve got one or two, they’re good to go, and this format is much more closely aligned to the way most artists are releasing music into the marketplace, which gives vinyl a vibrancy and an immediacy and a relevance that sometimes is difficult to be able to keep together in a 12-inch format.”

Another consideration for artists is getting sales recognition, which is something all Tiny Vinyl releases will have, whereas many independent releases do not. “I think a really important piece is that Tiny Vinyl charts,” Mann said. “It is tracked through Luminate to make sure that it hits the Billboard charts.”

Vinyl Format Comparison

3” single Tiny Vinyl single 7” 45 rpm single 12” 33 rpm LP
Size (jacket area) 3.75×3.75in 95x95mm 4.25×4.25in 108x108mm 7.25×7.25in 184x184mm 12.25×12.25in 314x314mm
Weight (with cover) 0.80oz 22g 1.35oz 37g 2.00oz 56g 10.60oz 300g
Sides 1 2 2 2
Length (per side) ~2.5 min 4 min 6 min 23 min
Typical Cost $12 $15 $10–15 $25–35

Looking for adoption

Early signs are suggesting Tiny Vinyl has legs. “Rainbow Kitten Surprise, which is TV0002, they’re the first artist to release a second item with us,” Mann said. “Whereas we’ve had reorders for certain titles that sold really well, they’re the first artist that has had success in like a surprise-and-delight kind of way and then gone back to the well and were like, hey, we want to do this again.”

Though just over a dozen Tiny Vinyl records have been released in the wild so far, including titles from the likes of Derek and the Moonrocks, Melissa Etheridge, America’s Got Talent finalist Grace VanderWaal, and Blake Shelton, Target has over 40 titles lined up to start selling at the end of September. But interest has already grown beyond what’s already been announced.

Credit: Chris Foresman

“There are actually many in the process of manufacturing,” Kohler said. “TV0087 is in production, so while there are only a handful that are available for sale right now in the market, there’s a whole wave of new Tiny Vinyls coming.”

And Coker is convinced that independent labels and record stores will be more apt to embrace the format once it’s gotten some wings.

“In order to be able to give the format the broad adoption that we’ve been looking for, we had to assemble the ability to not only make these things but make them at scale, and then to get enough labels and enough artists attached to the project that we could launch a credible initial offering,” Coker said. “Tiny Vinyl, it’s still a baby, right? Giving it a chance to safely get launched into the world, where it can grow up and take whatever path that it takes is, I think, our job to try to be good parents, and help shepherd it through that process.”

Ultimately, fans will decide Tiny Vinyl’s fate. Whether it’s a resounding success or more of a collector niche like 3-inch vinyl remains to be seen. But Crosley’s Bingaman thinks even a little success is worth the effort.

“If it lasts one year or 10, it’s all about that kid walking into Target and getting that first piece of vinyl,” he said.

Tiny Vinyl is a new pocketable record format for the Spotify age Read More »

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What to expect (and not expect) from yet another September Apple event


An all-new iPhone variant, plus a long list of useful (if predictable) upgrades.

Apple’s next product announcement is coming soon. Credit: Apple

Apple’s next product announcement is coming soon. Credit: Apple

Apple’s next product event is happening on September 9, and while the company hasn’t technically dropped any hints about what’s coming, anyone with a working memory and a sense of object permanence can tell you that an Apple event in the month of September means next-generation iPhones.

Apple’s flagship phones have changed in mostly subtle ways since 2022’s iPhone 14 Pro added the Dynamic Island and 2023’s refreshes switched from Lightning to USB-C. Chips get gradually faster, cameras get gradually better, but Apple hasn’t done a seismic iPhone X-style rethinking of its phones since, well, 2017’s iPhone X.

The rumor mill thinks that Apple is working on a foldable iPhone—and such a device would certainly benefit from years of investment in the iPad—but if it’s coming, it probably won’t be this year. That doesn’t mean Apple is totally done iterating on the iPhone X-style design, though. Let’s run down what the most reliable rumors have said we’re getting.

The iPhone 17

Last year’s iPhone 16 Pro bumped the screen sizes from 6.1 and 6.7 inches to 6.3 and 6.9 inches. This year’s iPhone 17 will allegedly get a 6.3-inch screen with a high-refresh-rate ProMotion panel, but the iPhone Plus is said to be going away. Credit: Apple

Apple’s vanilla one-size-fits-most iPhone is always the centerpiece of the lineup, and this year’s iteration is expected to bring the typical batch of gradual iterative upgrades.

The screen will supposedly be the biggest beneficiary, upgrading from 6.1 inches to 6.3 inches (the same size as the current iPhone 16 Pro) and adding a high-refresh-rate ProMotion screen that has typically been reserved for the Pro phones. Apple is always careful not to add too many “Pro”-level features to the entry-level iPhones, but this one is probably overdue—even less-expensive Android phones like the Pixel 9a ship often ship with 90 Hz or 120 Hz screens at this point. It’s not clear whether that will also enable the always-on display feature that has also historically been exclusive to the iPhone Pro, but the fluidity upgrade will be nice regardless.

Aside from that, there aren’t many specific improvements we’ve seen reported on, but there are plenty we can comfortably guess at. Improved front- and rear-facing cameras and a new Apple A19-series chip with at least the 8GB of RAM needed to support Apple Intelligence are both pretty safe bets.

But there’s one thing we supposedly won’t get, which is a new large-sized iPhone Plus. That brings us to our next rumor.

The “iPhone Air”

For the last few years, every new iPhone launch has actually brought us four iPhones—a regular iPhone in two different sizes and an iPhone Pro with a better camera, better screen, faster chip, and other improvements in a regular size and a large size.

It’s the second size of the regular iPhone that has apparently given Apple some trouble. It made a couple of generations of “iPhone mini,” an attempt to address a small-but-vocal contingent of Phones Are Just Too Big These Days people that apparently didn’t sell well enough to continue making. That was replaced by the iPhone Plus, aimed at people who wanted a bigger screen but who weren’t ready to pay for an iPhone Pro Max.

The Plus phones at least gave the iPhone lineup a nice symmetry—two tiers of phone, with a regular one and a big one at each tier—but rumors suggest that the Plus phone is also going away this year. Like the iPhone mini before it, it apparently just wasn’t selling well enough to be worth the continued effort.

That brings us to this year’s fourth iPhone: Apple is supposedly planning to release an “iPhone Air,” which will weigh less than the regular iPhone and is said to be 5.5 or 6 mm thick, depending on who you ask (the iPhone 16 is 7.8 mm).

A 6.3-inch ProMotion display and A19-series chip are also expected to be a part of the iPhone Air, but rather than try to squeeze every feature of the iPhone 17 into a thinner phone, it sounds like the iPhone 17 Air will cater to people who are willing to give a few things up in the interest of getting a thinner and lighter device. It will reportedly have worse battery life than the regular iPhone and just a single-lens camera setup (though the 48 MP sensors Apple has switched to in recent iPhones do make it easier to “fake” optical zoom features than it used to be).

We don’t know anything about the pricing for any of these phones, but Bloomberg’s Mark Gurman suggests that the iPhone Air will be positioned between the regular iPhone and the iPhone Pro—more like the iPad lineup, where the Air is the mid-tier choice, and less like the Mac, where the Air is the entry-level laptop.

iPhone 17 Pro

Apple’s Pro iPhones are generally “the regular iPhone, but more,” and sometimes they’re “what all iPhones will look like in a couple of years, but available right now for people who will pay more for it.” The new ones seem set to continue in that vein.

The most radical change will apparently be on the back—Apple is said to be switching to an even larger camera array that stretches across the entire top-rear section of the phone, an arrangement you’ll occasionally see in some high-end Android phones (Google’s Pixel 10 is one). That larger camera bump will likely enable a few upgrades, including a switch from a 12 MP sensor for the telephoto zoom lens to a 48 MP sensor. And it will also be part of a more comprehensive metal-and-glass body that’s more of a departure from the glass-backed-slab design Apple has been using since the iPhone 12.

A 48MP telephoto sensor could increase the amount of pseudo-optical zoom that the iPhone can offer. The main iPhones will condense a 48 MP photo down to 12 MP when you’re in the regular shooting mode, binning pixels to improve image quality. For zoomed-in photos, it can just take a 12 MP section out of the middle of the 48 MP image—you lose the benefit of pixel binning, but you’re still getting a “native resolution” photo without blurry digital zoom. With a better sensor, Apple could do exactly the same thing with the telephoto lens.

Apple reportedly isn’t planning any changes to screen size this year—still 6.3 inches for the regular Pro and 6.9 inches for the Max. But they are said to be getting new “A19 Pro” series chips that are superior to the regular A19 processors (though in what way, exactly, we don’t yet know). But it could shrink the amount of screen space dedicated to the Dynamic Island.

New Apple Watches

Apple Watch Series 10

The Apple Watch Series 10 from 2024. Credit: Apple

New iPhone announcements are usually paired with new Apple Watch announcements, though if anything, the Watch has changed even less than the iPhone has over the last few years.

The Apple Watch Series 11 won’t be getting a screen size increase—the Series 10 bumped things up a smidge just last year, from 41 and 45 mm to 42 and 46 mm. But the screen will apparently have a higher maximum brightness—always useful for outdoor visibility—and there will be a modestly improved Apple S11 chip on the inside.

The entry-level Apple Watch SE is also apparently due for an upgrade. The current second-generation SE still uses an Apple S8 chip, and Apple Watch Series 4-era 40 and 44 mm screens that don’t support always-on operation. In other words, there’s plenty that Apple could upgrade here without cannibalizing sales of the mainstream Series 11 watch.

Finally, after missing out on an update last year, Apple also reportedly plans to deliver a new Apple Watch Ultra, with the larger 46 mm screen from the Series 10/11 watches and the same updated S11 chip as the regular Apple Watch. The current Apple Watch Ultra 2 already has a brighter screen than the Series 10—3,000 nits, up from 2,000—so it’s not clear whether the Apple Watch Ultra 3’s screen would also get brighter or if the Series 11’s screen is just getting a brightness boost to match what the Ultra can do.

Smart home, TV, and audio

Though iPhones and Apple Watches are usually a lock for a September event, other products and accessory updates are also possible.

Of these, the most high-profile is probably a refresh for the Apple TV 4K streaming box, which would be its first update in three years. Rumors suggest that the main upgrade for a new model would be an Apple A17 Pro chip, introduced for the iPhone 15 Pro and also used in the iPad mini 7. The A17 Pro is paired with 8GB of RAM, which makes it Apple’s smallest and cheapest chip that’s capable of Apple Intelligence. Apple hasn’t done anything with Apple Intelligence on the Apple TV directly, but to date, that has been partly because none of the hardware is capable of it.

Also in the “possible but not guaranteed” column: new high-end AirPods Pro, the first-ever internal update to 2020’s HomePod Mini speaker, a new AirTag location tracker, and a straightforward internals-only refresh of the Vision Pro headset. Any, all, or none of these could break cover at the event next week, but Gurman claims they’re all “coming soon.”

New software updates

Devices running Apple’s latest beta operating systems. Credit: Apple

We know most of what there is to know about iOS 26, iPadOS 26, macOS 26, and Apple’s other software updates this year, thanks to a three-month-old WWDC presentation and months of public beta testing. There might be a feature or two exclusive to the newest iPhones, but that sort of thing is usually camera-related and usually pretty minor.

The main thing to expect will be release dates for the final versions of all of the updates. Apple usually releases a near-final release candidate build on the day of the presentation, gives developers a week or so to finalize and submit their updated apps for App Review, and then releases the updates after that. Expect to see them rolled out to everyone sometime the week of September 15th (though an earlier release is always a possibility).

What’s probably not happening

We’d be surprised to see anything related to the Mac or the iPad at the event next week, even though several models are in a window where the timing is about right for an Apple M5 refresh.

Macs and iPads have shared the stage with the iPhone before, but in more recent years, Apple has held these refreshes back for another, smaller event later in October or November. If Apple has new MacBook Pro or iPad Pro models slated for 2025, we’d expect to see them in a month or two.

Photo of Andrew Cunningham

Andrew is a Senior Technology Reporter at Ars Technica, with a focus on consumer tech including computer hardware and in-depth reviews of operating systems like Windows and macOS. Andrew lives in Philadelphia and co-hosts a weekly book podcast called Overdue.

What to expect (and not expect) from yet another September Apple event Read More »

beyond-technology?-how-bentley-is-reacting-to-the-21st-century.

Beyond technology? How Bentley is reacting to the 21st century.

Chinese manufacturers are embedding more digital bells and whistles that impact all segments of the market, and not just in China. “Just as in other segments, the Chinese OEMs are moving faster than anyone else on software, especially for infotainment, bringing big screens and digital assistants with homegrown software and lots of connectivity, but also on driving assist and automation,” Abuelsamid said. “These vehicles are being equipped with lidar, radar, cameras, and point-to-point driving assist, similar to Tesla navigation on Autopilot.”

The onslaught of features by Chinese competitors has luxury European automakers on their toes.

“Hongqi is probably the closest to a direct competitor in China and certainly has some offerings that might considered be in a similar class to Bentley,” Abuelsamid said. “There are numerous other brands that continue to move upscale and will likely eventually reach a similar level, even if they aren’t as hand-built as a Bentley, such as the BYD Yangwang U8 SUV.”

For example, the Maextro S800, a premium car born out of Huawei and JA joint venture, crab-walks a 16-degree angle to make tight parking easy, features hand-off “level 3” partially automated driving, and charges from 10 to 80 percent in just 10.5 minutes, according to Inside EVs.

“We see it drives demand for features and what people expect their cars to have,” Walliser said. “They say, ‘Hey, if my $50,000 car has self-driving capabilities, why don’t I have it in my $250,000 car?’ So this is the real rival. It’s a feature competition, and it raises expectations,” Walliser said.

EXP 15

Bentley’s latest concept, the EXP 15, hints at this next generation of predictive elements customers say they want. Clever UX design includes a rotating dashboard and illuminated forms on the dash, which are mixed with fine wools, leathers, and premium materials in the cabin. “I think we have to continue [to think] like that in self-driving capabilities. We do not have to be first in the market,” Walliser said. “We need to plan when we offer it. It comes also for infotainment, for app connection, for everything that makes life in the car convenient, such as self-parking capabilities.”

Dr. Matthias Rabe serves on Bentley’s board of management and oversees Research and Development. He thinks the right approach to technology for Bentley is for the car to serve as a sort of virtual butler. “What I would like to have, for example, is that the customer drives to the front of the house, pops out, and the car parks itself, charges itself, and probably gets cleaned by itself,” Rabe said.

Beyond technology? How Bentley is reacting to the 21st century. Read More »

delete,-delete,-delete:-how-fcc-republicans-are-killing-rules-faster-than-ever

Delete, Delete, Delete: How FCC Republicans are killing rules faster than ever


FCC speeds up rule-cutting, giving public as little as 10 days to file objections.

FCC Chairman Brendan Carr testifies before the House Appropriations Subcommittee on Financial Services and General Government on May 21, 2025 in Washington, DC. Credit: Getty Images | John McDonnell

The Federal Communications Commission’s Republican chairman is eliminating regulations at breakneck speed by using a process that cuts dozens of rules at a time while giving the public only 10 or 20 days to review each proposal and submit objections.

Chairman Brendan Carr started his “Delete, Delete, Delete” rule-cutting initiative in March and later announced he’d be using the Direct Final Rule (DFR) mechanism to eliminate regulations without a full public-comment period. Direct Final Rule is just one of several mechanisms the FCC is using in the Delete, Delete, Delete initiative. But despite the seeming obscurity of regulations deleted under Direct Final Rule so far, many observers are concerned that the process could easily be abused to eliminate more significant rules that protect consumers.

On July 24, the FCC removed what it called “11 outdated and useless rule provisions” related to telegraphs, rabbit-ear broadcast receivers, and phone booths. The FCC said the 11 provisions consist of “39 regulatory burdens, 7,194 words, and 16 pages.”

The FCC eliminated these rules without the “prior notice and comment” period typically used to comply with the US Administrative Procedure Act (APA), with the FCC finding that it had “good cause” to skip that step. The FCC said it would allow comment for 10 days and that rule eliminations would take effect automatically after the 10-day period unless the FCC concluded that it received “significant adverse comments.”

On August 7, the FCC again used Direct Final Rule to eliminate 98 rules and requirements imposed on broadcasters. This time, the FCC allowed 20 days for comment. But it maintained its stance that the rules would be deleted automatically at the end of the period if no “significant” comments were received.

By contrast, FCC rulemakings usually allow 30 days for initial comments and another 15 days for reply comments. The FCC then considers the comments, responds to the major issues raised, and drafts a final proposal that is put up for a commission vote. This process, which takes months and gives both the public and commissioners more opportunity to consider the changes, can apply both to the creation of new rules and the elimination of existing ones.

FCC’s lone Democrat warns of “Trojan horse”

Telecom companies want the FCC to eliminate rules quickly. As we’ve previously written, AT&T submitted comments to the Delete, Delete, Delete docket urging the agency to eliminate rules that can result in financial penalties “without the delay imposed by notice-and-comment proceeding.”

Carr’s use of Direct Final Rule has drawn criticism from advocacy groups, local governments that could be affected by rule changes, and the FCC’s only Democratic commissioner. Anna Gomez, the lone FCC Democrat, told Ars in a phone interview that the rapid rule-cutting method “could be a Trojan horse because what we did, or what the commission did, is it adopted a process without public comment to eliminate any rule it finds to be outdated and, crucially, unwarranted. We don’t define what either of those terms mean, which therefore could lead to a situation that’s ripe for abuse.”

Gomez said she’d “be concerned if we eliminated rules that are meant to protect or inform consumers, or to promote competition, such as the broadband labels. This commission seems to have entirely lost its focus on consumers.”

Gomez told us that she doesn’t think a 10-day comment period is ever appropriate and that Carr seems to be trying “to meet some kind of arbitrary rule reduction quota.” If the rules being eliminated are truly obsolete, “then what’s the rush?” she asked. “If we don’t give sufficient time for public comment, then what happens when we make a mistake? What happens when we eliminate rules and it turns out, in fact, that these rules were important to keep? That’s why we give the public due process to comment on when we adopt rules and when we eliminate rules.”

Gomez hasn’t objected to the specific rules deleted under this process so far, but she spoke out against the method used by Carr both times Direct Final Rule method was used. “I told the chairman that I could support initiating a proceeding to look at how a Direct Final Rule process could be used going forward and including a Notice of Proposed Rulemaking proposing to eliminate the rules the draft order purports to eliminate today. That offer was declined,” she said in her dissenting statement in the July vote.

Gomez said that rules originally adopted under a notice-and-comment process should not be eliminated “without seeking public comment on appropriate processes and guardrails.” She added that the “order does not limit the Direct Final Rule process to elimination of rules that are objectively obsolete with a clear definition of how that will be applied, asserting instead authority to remove rules that are ‘outdated or unwarranted.'”

Local governments object

Carr argued that the Administrative Procedure Act “gives the commission the authority to fast-track the elimination of rules that inarguably fail to serve the public interest. Using this authority, the Commission can forgo the usual prior notice and public comment period before repealing the rules for these bygone regulations.”

Carr justified the deletions by saying that “outdated and unnecessary regulations from Washington often derail efforts to build high-speed networks and infrastructure across the country.” It’s not clear why the specific rule deletions were needed to accelerate broadband deployment, though. As Carr said, the FCC’s first use of Direct Finale Rule targeted regulations for “telegraph services, rabbit-ear broadcast receivers, and telephone booths—technologies that were considered outdated decades ago.”

Carr’s interpretation of the Administrative Procedure Act is wrong, said an August 6 filing submitted by local governments in Maryland, Massachusetts, the District of Columbia, Oregon, Virginia, California, New York, and Texas. Direct Final Rule “is intended for extremely simple, non-substantive decisions,” and the FCC process “is insufficient to ensure that future Commission decisions will fall within the good cause exception of the Administrative Procedure Act,” the filing said.

Local governments argued that “the new procedure is itself a substantive decision” and should be subject to a full notice-and-comment rulemaking. “The procedure adopted by the Commission makes it almost inevitable that the Commission will adopt rule changes outside of any APA exceptions,” the filing said.

The FCC could face court challenges. Gerard Lavery Lederer, a lawyer for the local government coalition, told Ars, “we fully anticipate that Chairman Carr and the FCC’s general counsel will take our concerns seriously.” But he also said local governments are worried about the FCC adopting industry proposals that “violate local government rights as preserved by Congress in the [Communications] Act” or that have “5th Amendment takings implications and/or 10th Amendment overreach issues.”

Is that tech really “obsolete”?

At least some rules targeted for deletion, like regulations on equipment used by radio and TV broadcast stations, may seem too arcane to care about. But a coalition of 22 public interest, civil rights, labor, and digital rights groups argued in a July 17 letter to Carr that some of the rule deletions could harm vulnerable populations and that the shortened comment period wasn’t long enough to determine the impact.

“For example, the Commission has targeted rules relating to calling cards and telephone booths in the draft Order as ‘obsolete,'” the letter said. “However, calling cards and pay phones remain important technologies for rural areas, immigrant communities, the unhoused, and others without reliable access to modern communications services. The impact on these communities is not clear and will not likely be clear in the short time provided for comment.”

The letter also said the FCC’s new procedure “would effectively eliminate any hope for timely judicial review of elimination of a rule on delegated authority.” Actions taken via delegated authority are handled by FCC bureaus without a vote of the commission.

So far, Carr has held commission votes for his Direct Final Rule actions rather than letting FCC bureau issue orders themselves. But in the July order, the FCC said its bureaus and offices have previously adopted or repealed rules without notice and comment and “reaffirm[ed] that all Bureaus and Offices may continue to take such actions in situations that are exempt from the APA’s notice-and-comment requirements.”

“This is about pushing boundaries”

The advocacy groups’ letter said that delegating authority to bureaus “makes judicial review virtually impossible, even though the order goes into effect immediately.” Parties impacted by actions made on delegated authority can’t go straight to the courts and must instead “file an application for review with the Commission as a prerequisite to any petition for judicial review,” the letter said. The groups argued that “a Chairman that does not wish to permit judicial review of elimination of a rule through DFR may order a bureau to remove the rule, then simply refuse to take action on the application for review.”

The letter was signed by Public Knowledge; Asian Americans Advancing Justice-AAJC; the Benton Institute for Broadband & Society; the Center for Digital Democracy; Common Sense Media; the Communications Workers of America; the Electronic Privacy Information Center; HTTP; LGBT Tech; the Media Access Project; MediaJustice; the Multicultural Media, Telecom and Internet Council; the National Action Network; NBJC; the National Council of Negro Women; the National Digital Inclusion Alliance; the National Hispanic Media Coalition; the National Urban League; New America’s Open Technology Institute (OTI); The Leadership Conference on Civil and Human Rights; the United Church of Christ Media Justice Ministry; and UnidosUS.

Harold Feld, senior VP of consumer advocacy group Public Knowledge, told Ars that the FCC “has a long record of thinking that things are obsolete and then discovering when they run an actual proceeding that there are people still using these things.” Feld is worried that the Direct Final Rule process could be used to eliminate consumer protections that apply to old phone networks when they are replaced by either fiber or wireless service.

“I certainly think that this is about pushing boundaries,” Feld said. When there’s a full notice-and-comment period, the FCC has to “actually address every argument made” before eliminating a rule. When the FCC provides less explanation of a decision, that “makes it much harder to challenge on appeal,” he said.

“Once you have this tool that lets you just get rid of rules without the need to do a proceeding, without the need to address the comments that are raised in that proceeding… it’s easy to see how this ramps up and how hard it is for people to stay constantly alert to look for an announcement where they will then only have 10 days to respond once it gets published,” he said.

What is a “significant” comment?

The FCC says its use of Direct Final Rule is guided by December 2024 recommendations from the Administrative Conference of the United States (ACUS), a government agency. But the FCC didn’t implement Direct Final Rule in the exact way recommended by the ACUS.

The ACUS said its guidance “encourages agencies to use direct final rulemaking, interim final rulemaking, and alternative methods of public engagement to ensure robust public participation even when they rely properly on the good cause exemption.” But the ACUS recommended taking public comment for at least 30 days, while the FCC has used 10- and 20-day periods.

The ACUS also said that agencies should only move ahead with rule deletions “if no significant adverse comments are received.” If such comments are received, the agency “can either withdraw the rule or publish a regular proposed rule that is open for public comment,” the recommendation said.

The FCC said that if it receives comments, “we will evaluate whether they are significant adverse comments that warrant further procedures before changing the rules.” The letter from 22 advocacy groups said it is worried about the leeway the FCC is giving itself in defining whether a comment is adverse and significant:

Although ACUS recommends that the agency revert to standard notice-and-comment rulemaking in the event of a single adverse comment, the draft Order requires multiple adverse comments—at which point the bureau/Commission will consider whether to shift to notice-and-comment rulemaking. If the bureau/Commission decides that adverse comments are not ‘substantive,’ it will explain its determination in a public notice that will not be filed in the Federal Register. The Commission states that it will be guided, but not bound, by the definition of ‘adverse comment’ recommended by ACUS.

Criticism from many corners

TechFreedom, a libertarian-leaning think tank, said it supports Carr’s goals in the “Delete, Delete, Delete” initiative but objected to the Direct Final Rule process. TechFreedom wrote in July comments that “deleting outdated regulations via a Direct Final Rule is unprecedented at the FCC.”

“No such process exists under current FCC rules,” the group said, urging the agency to seek public comment on the process. “If the Commission wishes to establish a new method by which it can eliminate existing regulations without undertaking a full rulemaking proceeding, it should open a docket specific to that subject and seek public comment,” the filing said.

TechFreedom said it is especially important for the FCC to “seek comment as to when the direct final rule procedures should be invoked… What is ‘routine,’ ‘insignificant,’ or ‘inconsequential’ and who is to decide—the Commissioners or the Bureau chiefs?”

The American Library Association and other groups wrote on August 14 that either 10 or 20 days is not long enough for public comment. Moreover, the groups said the two Direct Final Rule actions so far “offer minimal explanation for why the rules are being removed. There is only one sentence describing elimination of many rules and each rule removal is described in a footnote with a parenthetical about the change. It is not enough.”

The Utility Reform Network offered similar objections about the process and said that the FCC declaring technologies to be “obsolete” and markets “outdated” without a detailed explanation “suggests the Commission’s view that these rules are not minor or technical changes but support a larger deregulatory effort that should itself be subject to notice-and-comment rulemaking.”

The National Consumer Law Center and other groups said that “rushing regulatory changes as proposed is likely illegal in many instances, counterproductive, and bad policy,” and that “changes to regulations should be effectuated only through careful, thoughtful, and considered processes.”

We contacted Chairman Carr’s office and did not receive a response.

FCC delegated key decisions to bureaus

Gomez told Ars that Direct Final Rule could serve a purpose “with the right procedures and guardrails in place.” For example, she said the quick rule deletions can be justified for eliminating rules that have become obsolete because of a court reversal or Congressional actions.

“I would argue that we cannot, under the Administrative Procedure Act and the Constitution, simply eliminate rules because we’ve made a judgment call that they are unwarranted,” she said. “That does not meet the good cause exemption to notice-and-comment requirements.”

Gomez also opposes FCC bureaus making significant decisions without a commission vote, which effectively gives Carr more power over the agency’s operations. For example, T-Mobile’s purchase of US Cellular’s wireless operations and Verizon’s purchase of Frontier were approved by the FCC at the Bureau level.

In another instance cited by Gomez, the FCC Media Bureau waived a requirement for broadcast licensees to file their biennial ownership reports for 18 months. “The waiver order, which was done at the bureau level on delegated authority, simply said ‘we find good cause to waive these rules.’ There was no analysis whatsoever,” Gomez said.

Gomez also pointed out that the Carr FCC’s Wireline Competition Bureau delayed implementation of certain price caps on prison phone services. The various bureau-level decisions are a “stretching of the guardrails that we have internally for when things should be done on delegated authority, and when they should be voted by the commission,” Gomez said. “I’m concerned that [Direct Final Rule] is just the next iteration of the same issue.”

Photo of Jon Brodkin

Jon is a Senior IT Reporter for Ars Technica. He covers the telecom industry, Federal Communications Commission rulemakings, broadband consumer affairs, court cases, and government regulation of the tech industry.

Delete, Delete, Delete: How FCC Republicans are killing rules faster than ever Read More »

google-pixel-10-series-review:-don’t-call-it-an-android

Google Pixel 10 series review: Don’t call it an Android


Google’s new Pixel phones are better, but only a little.

Pixel 10 series shadows

Left to right: Pixel 10, Pixel 10 Pro, Pixel 10 Pro XL. Credit: Ryan Whitwam

Left to right: Pixel 10, Pixel 10 Pro, Pixel 10 Pro XL. Credit: Ryan Whitwam

After 10 generations of Pixels, Google’s phones have never been more like the iPhone, and we mean that both as a compliment and a gentle criticism. For people who miss the days of low-cost, tinkering-friendly Nexus phones, Google’s vision is moving ever further away from that, but the attention to detail and overall polish of the Pixel experience continue with the Pixel 10, 10 Pro, and 10 Pro XL. These are objectively good phones with possibly the best cameras on the market, and they’re also a little more powerful, but the aesthetics are seemingly locked down.

Google made a big design change last year with the Pixel 9 series, and it’s not reinventing the wheel in 2025. The Pixel 10 series keeps the same formula, making limited refinements, not all of which will be well-received. Google pulled out all the stops and added a ton of new AI features you may not care about, and it killed the SIM card slot. Just because Apple does something doesn’t mean Google has to, but here we are. If you’re still clinging to your physical SIM card or just like your Pixel 9, there’s no reason to rush out to upgrade.

A great but not so daring design

If you liked the Pixel 9’s design, you’ll like the Pixel 10, because it’s a very slightly better version of the same hardware. All three phones are made from aluminum and Gorilla Glass Victus 2 (no titanium option here). The base model has a matte finish on the metal frame with a glossy rear panel, and it’s the opposite on the Pro phones. This makes the more expensive phones a little less secure in the hand—those polished edges are slippery. The buttons on the Pixel 9 often felt a bit loose, but the buttons on all our Pixel 10 units are tight and clicky.

Pixel 10 back all

Left to right: Pixel 10 Pro XL, Pixel 10 Pro, Pixel 10.

Credit: Ryan Whitwam

Left to right: Pixel 10 Pro XL, Pixel 10 Pro, Pixel 10. Credit: Ryan Whitwam

Specs at a glance: Google Pixel 10 series
Pixel 10 ($799) Pixel 10 Pro ($999) Pixel 10 Pro XL ($1,199) Pixel 10 Pro Fold ($1,799)
SoC Google Tensor G5  Google Tensor G5  Google Tensor G5  Google Tensor G5
Memory 12GB 16GB 16GB 16GB
Storage 128GB / 256GB 128GB / 256GB / 512GB 128GB / 256GB / 512GB / 1TB 256GB / 512GB / 1TB
Display 6.3-inch 1080×2424 OLED, 60-120Hz, 3,000 nits 6.3-inch 1280×2856 LTPO OLED, 1-120Hz, 3,300 nits 6.8-inch 1344×2992 LTPO OLED, 1-120Hz, 3,300 nits External: 6.4-inch 1080×2364 OLED, 60-120Hz, 2000 nits; Internal: 8-inch 2076×2152 LTPO OLED, 1-120Hz, 3,000 nits
Cameras 48 MP wide with Macro

Focus, F/1.7, 1/2-inch sensor; 13 MP ultrawide, f/2.2, 1/3.1-inch sensor;

10.8 MP 5x telephoto, f/3.1, 1/3.2-inch sensor; 10.5 MP selfie, f/2.2
50 MP wide with Macro

Focus, F/1.68, 1/1.3-inch sensor; 48 MP ultrawide, f/1.7, 1/2.55-inch sensor;

48 MP 5x telephoto, f/2.8, 1/2.55-inch sensor; 42 MP selfie, f/2.2
50 MP wide with Macro

Focus, F/1.68, 1/1.3-inch sensor; 48 MP ultrawide, f/1.7, 1/2.55-inch sensor;

48 MP 5x telephoto, f/2.8, 1/2.55-inch sensor; 42 MP selfie, f/2.2
48 MP wide, F/1.7, 1/2-inch sensor; 10.5 MP ultrawide with Macro Focus, f/2.2, 1/3.4-inch sensor;

10.8 MP 5x telephoto, f/3.1, 1/3.2-inch sensor; 10.5 MP selfie, f/2.2 (outer and inner)
Software Android 16 Android 16 Android 16 Android 16
Battery 4,970 mAh,  up to 30 W wired charging, 15 W wireless charging (Pixelsnap) 4,870 mAh, up to 30 W wired charging, 15 W wireless charging (Pixelsnap) 5,200 mAh, up to 45 W wired charging, 25 W wireless charging (Pixelsnap) 5,015 mAh, up to 30 W wired charging, 15 W wireless charging (Pixelsnap)
Connectivity Wi-Fi 6e, NFC, Bluetooth 6.0, sub-6 GHz and mmWave 5G, USB-C 3.2 Wi-Fi 7, NFC, Bluetooth 6.0, sub-6 GHz and mmWave 5G, UWB, USB-C 3.2 Wi-Fi 7, NFC, Bluetooth 6.0, sub-6 GHz and mmWave 5G, UWB, USB-C 3.2 Wi-Fi 7, NFC, Bluetooth 6.0, sub-6 GHz and mmWave 5G, UWB, USB-C 3.2
Measurements 152.8 height×72.0 width×8.6 depth (mm), 204g 152.8 height×72.0 width×8.6 depth (mm), 207g 162.8 height×76.6 width×8.5 depth (mm), 232g Folded: 154.9 height×76.2 width×10.1 depth (mm); Unfolded: 154.9 height×149.8 width×5.1 depth (mm); 258g
Colors Indigo

Frost

Lemongrass

Obsidian
Moonstone

Jade

Porcelain

Obsidian
Moonstone

Jade

Porcelain

Obsidian
Moonstone

Jade

The rounded corners and smooth transitions between metal and glass make the phones comfortable to hold, even for the mammoth 6.8-inch Pixel 10 Pro XL. This phone is pretty hefty at 232 g, though—that’s even heavier than Samsung’s Galaxy Z Fold 7. I’m pleased that Google kept the smaller premium phone in 2025, offering most of the capabilities and camera specs of the XL in a more cozy form factor. It’s not as heavy, and the screen is a great size for folks with average or smaller hands.

Pixel 10 Pro

The Pixel 10 Pro is a great size.

Credit: Ryan Whitwam

The Pixel 10 Pro is a great size. Credit: Ryan Whitwam

On the back, you’ll still see the monolithic camera bar near the top. I like this design aesthetically, but it’s also functional. When you set a Pixel 10 down on a table or desk, it remains stable and easy to use, with no annoying wobble. While this element looks unchanged at a glance, it actually takes up a little more surface area on the back of the phone. Yes, that means none of your Pixel 9 cases will fit on the 10.

The Pixel 10’s body has fewer interruptions compared to the previous model, too. Google has done away with the unsightly mmWave window on the top of the phone, and the bottom now has two symmetrical grilles for the mic and speaker. What you won’t see is a SIM card slot (at least in the US). Like Apple, Google has gone all-in with eSIM, so if you’ve been clinging to that tiny scrap of plastic, you’ll have to give it up to use a Pixel 10.

Pixel 10 Pro XL side

The Pixel 10 Pro XL has polished sides that make it a bit slippery.

Credit: Ryan Whitwam

The Pixel 10 Pro XL has polished sides that make it a bit slippery. Credit: Ryan Whitwam

The good news is that eSIMs are less frustrating than they used to be. All recent Android devices have the ability to transfer most eSIMs directly without dealing with the carrier. We’ve moved a T-Mobile eSIM between Pixels and Samsung devices a few times without issue, but you will need Wi-Fi connectivity, which is an annoying caveat.

Display sizes haven’t changed this year, but they all look impeccable. The base model and smaller Pro phone sport 6.3-inch OLEDs, and the Pro XL’s is at 6.8 inches. The Pixel 10 has the lowest resolution at 1080p, and the refresh rate only goes from 60–120 Hz. The 10 Pro and 10 Pro XL get higher-resolution screens with LTPO technology that allows them to go as low as 1Hz to save power. The Pro phones also get slightly brighter but all have peak brightness of 3,000 nits or higher, which is plenty to make them readable outdoors.

Pixel 10 MagSafe

The addition of Qi2 makes numerous MagSafe accessories compatible with the new Pixels.

Credit: Ryan Whitwam

The addition of Qi2 makes numerous MagSafe accessories compatible with the new Pixels. Credit: Ryan Whitwam

The biggest design change this year isn’t visible on the outside. The Pixel 10 phones are among the first Android devices with full support for the Qi2 charging standard. Note, this isn’t just “Qi2 Ready” like the Galaxy S25. Google’s phones have the Apple-style magnets inside, allowing you to use many of the chargers, mounts, wallets, and other Apple-specific accessories that have appeared over the past few years. Google also has its own “Pixelsnap” accessories, like chargers and rings. And yes, the official Pixel 10 cases are compatible with magnetic attachments. Adding something Apple has had for years isn’t exactly innovative, but Qi2 is genuinely useful, and you won’t get it from other Android phones.

Expressive software

Google announced its Material 3 Expressive overhaul earlier this year, but it wasn’t included in the initial release of Android 16. The Pixel 10 line will ship with this update, marking the biggest change to Google’s Android skin in years. The Pixel line has now moved quite far from the “stock Android” aesthetic that used to be the company’s hallmark. The Pixel build of Android is now just as customized as Samsung’s One UI or OnePlus’ OxygenOS, if not more so.

Pixel 10 Material 3

Material 3 Expressive adds more customizable quick settings.

Credit: Ryan Whitwam

Material 3 Expressive adds more customizable quick settings. Credit: Ryan Whitwam

The good news is that Material 3 looks very nice. It’s more colorful and playful but not overbearing. Some of the app concepts shown off during the announcement were a bit much, but the production app redesigns Google has rolled out since then aren’t as heavy-handed. The Material colors are used more liberally throughout the UI, and certain UI elements will be larger and more friendly. I’ll take Material 3 Expressive over Apple’s Liquid Glass redesign any day.

I’ve been using a pre-production version of the new software, but even for early Pixel software, there have been more minor UI hitches than expected. Several times, I’ve seen status bar icons disappear, app display issues, and image edits becoming garbled. There are no showstopping bugs, but the new software could do with a little cleaning up.

The OS changes are more than skin-deep—Google has loaded the Pixel 10 series with a ton of new AI gimmicks aimed at changing the experience (and justifying the company’s enormous AI spending). With the more powerful Tensor G5 to run larger Gemini Nano on-device models, Google has woven AI into even more parts of the OS. Google’s efforts aren’t as disruptive or invasive as what we’ve seen from other Android phone makers, but that doesn’t mean the additions are useful.

It would be fair to say Magic Cue is Google’s flagship AI addition this year. The pitch sounds compelling—use local AI to crunch your personal data into contextual suggestions in Maps, Messages, phone calls, and more. For example, it can prompt you to insert content into a text message based on other messages or emails.

Despite having a mountain of personal data in Gmail, Keep, and other Google apps, I’ve seen precious few hints of Magic Cue. It once suggested a search in Google Maps, and on another occasion, it prompted an address in Messages. If you don’t use Google’s default apps, you might not see Magic Cue at all. More than ever before, getting the most out of the Pixel means using Google’s first-party apps, just like that other major smartphone platform.

Pixel 10 AI

Google is searching for more ways to leverage generative AI.

Credit: Ryan Whitwam

Google is searching for more ways to leverage generative AI. Credit: Ryan Whitwam

Google says it can take about a day after you set up the Pixel 10 before Magic Cue will be done ingesting your personal data—it takes that long because it’s all happening on your device instead of in the cloud. I appreciate Google’s commitment to privacy in mobile AI because it does have access to a huge amount of user data. But it seems like all that data should be doing more. And I hope that, in time, it does. An AI assistant that anticipates your needs is something that could actually be useful, but I’m not yet convinced that Magic Cue is it.

It’s a similar story with Daily Hub, an ever-evolving digest of your day similar to Samsung’s Now Brief. You will find Daily Hub at the top of the Google Discover feed. It’s supposed to keep you abreast of calendar appointments, important emails, and so on. This should be useful, but I rarely found it worth opening. It offered little more than YouTube and AI search suggestions.

Meanwhile, Pixel Journal works as advertised—it’s just not something most people will want to use. This one is similar to Nothing’s Essential Space, a secure place to dump all your thoughts and ideas throughout the day. This allows Gemini Nano to generate insights and emoji-based mood tracking. Cool? Maybe this will inspire some people to record more of their thoughts and ideas, but it’s not a game-changing AI feature.

If there’s a standout AI feature on the Pixel 10, it’s Voice Translate. It uses Gemini Nano to run real-time translation between English and a small collection of other languages, like Spanish, French, German, and Hindi. The translated voice sounds like the speaker (mostly), and the delay is tolerable. Beyond this, though, many of Google’s new Pixel AI features feel like an outgrowth of the company’s mandate to stuff AI into everything possible. Pixel Screenshots might still be the most useful application of generative AI on the Pixels.

As with all recent Pixel phones, Google guarantees seven years of OS and security updates. That matches Samsung and far outpaces OEMs like OnePlus and Motorola. And unlike Samsung, Google phone updates arrive without delay. You’ll get new versions of Android first, and the company’s Pixel Drops add new features every few months.

Modest performance upgrade

The Pixel 10 brings Google’s long-awaited Tensor G5 upgrade. This is the first custom Google mobile processor manufactured by TSMC rather than Samsung, using the latest 3 nm process node. The core setup is a bit different, with a 3.78 GHz Cortex X4 at the helm. It’s backed by five high-power Cortex-A725s at 3.05 GHz and two low-power Cortex-A520 cores at 2.25 GHz. Google also says the NPU has gotten much more powerful, allowing it to run the Gemini models for its raft of new AI features.

Pixel 10 family cameras

The Pixel 10 series keeps a familiar design.

Credit: Ryan Whitwam

The Pixel 10 series keeps a familiar design. Credit: Ryan Whitwam

If you were hoping to see Google catch up to Qualcomm with the G5, you’ll be disappointed. In general, Google doesn’t seem concerned about benchmark numbers. And in fairness, the Pixels perform very well in daily use. These phones feel fast, and the animations are perfectly smooth. While phones like the Galaxy S25 are faster on paper, we’ve seen less lag and fewer slowdowns on Google’s phones.

That said, the Tensor G5 does perform better in our testing compared to the G4. The CPU speed is up about 30 percent, right in line with Google’s claims. The GPU is faster by 20–30 percent in high-performance scenarios, which is a healthy increase for one year. However, it’s running way behind the Snapdragon 8 Elite we see in other flagship Android phones.

You might notice the slower Pixel GPU if you’re playing Genshin Impact or Call of Duty Mobile at a high level, but it will be more than fast enough for most of the mobile games people play. That performance gap will narrow during prolonged gaming, too. Qualcomm’s flagship chip gets very toasty in phones like the Galaxy S25, slowing down by almost half. The Pixel 10, on the other hand, loses less than 20 percent of its speed to thermal throttling.

Say what you will about generative AI—Google’s obsession with adding more on-device intelligence spurred it to boost the amount of RAM in this year’s Pro phones. You now get 16GB in the 10 Pro and 10 Pro XL. The base model continues to muddle along with 12GB. This could make the Pro phones more future-proof as additional features are added in Pixel Drop updates. However, we have yet to notice the Pro phones holding onto apps in memory longer than the base model.

The Pixel 10 series gets small battery capacity increases across the board, but it’s probably not enough that you’ll notice. The XL, for instance, has gone from 5,060 mAh to 5,200 mAh. It feels like the increases really just offset the increased background AI processing, because the longevity is unchanged from last year. You’ll have no trouble making it through a day with any of the Pixel phones, even if you clock a lot of screen time.

With lighter usage, you can almost make it through two days. You’ll probably want to plug in every night, though. Google has an upgraded always-on display mode on the Pixel 10 phones that shows your background in full color but greatly dimmed. We found this was not worth the battery life hit, but it’s there if you want to enable it.

Charging speed has gotten slightly better this time around, but like the processor, it’s not going to top the charts. The Pixel 10 and 10 Pro can hit a maximum of 30 W with a USB-C PPS-enabled charger, getting a 50 percent charge in about 30 minutes. The Pixel 10 Pro XL’s wired charging can reach around 45 W for a 70 percent charge in half an hour. This would be sluggish compared to the competition in most Asian markets, but it’s average to moderately fast stateside. Google doesn’t have much reason to do better here, but we wish it would try.

Pixel 10 Pro XL vs. Pixel 9 Pro XL

The Pixel 10 Pro XL (left) looks almost identical to the Pixel 9 Pro XL (right).

Credit: Ryan Whitwam

The Pixel 10 Pro XL (left) looks almost identical to the Pixel 9 Pro XL (right). Credit: Ryan Whitwam

Wireless charging is also a bit faster, but the nature of charging is quite different with support for Qi2. You can get 15 W of wireless power with a Qi2 charger on the smaller phones, and the Pixel 10 Pro XL can hit 25 W with a Qi2.2 adapter. There are plenty of Qi2 magnetic chargers out there that can handle 15 W, but 25 W support is currently much more rare.

Post-truth cameras

Google has made some changes to its camera setup this year, including the addition of a third camera to the base Pixel 10. However, that also comes with a downgrade for the other two cameras. The Pixel 10 sports a 48 MP primary, a 13 MP ultra wide, and a 10.8 MP 5x telephoto—this setup is most similar to Google’s foldable phone. The 10 Pro and 10 Pro XL have a slightly better 50 MP primary, a 48 MP ultrawide, and a 48 MP 5x telephoto. The Pixel 10 is also limited to 20x upscaled zoom, but the Pro phones can go all the way to 100x.

Pixel 10 camera closeup

The Pixel 10 gets a third camera, but the setup isn’t as good as on the Pro phones.

Credit: Ryan Whitwam

The Pixel 10 gets a third camera, but the setup isn’t as good as on the Pro phones. Credit: Ryan Whitwam

The latest Pixel phones continue Google’s tradition of excellent mobile photography, which should come as no surprise. And there’s an even greater focus on AI, which should also come as no surprise. But don’t be too quick to judge—Google’s use of AI technologies, even before the era of generative systems, has made its cameras among the best you can get.

The Pixel 10 series continues to be great for quick snapshots. You can pop open the camera and just start taking photos in almost any lighting to get solid results. Google’s HDR image processing brings out details in light and dark areas, produces accurate skin tones, and sharpens details without creating an “oil painting” effect when you zoom in. The phones are even pretty good at capturing motion, leaning toward quicker exposures while still achieving accurate colors and good brightness.

Pro phone samples:

Outdoor light. Ryan Whitwam

The Pixel 10 camera changes are a mixed bag. The addition of a telephoto lens for Google’s cheapest model is appreciated, allowing you to get closer to your subject and take greater advantage of Google’s digital zoom processing if 5x isn’t enough. The downgrade of the other sensors is noticeable if you’re pixel peeping, but it’s not a massive difference. Compared to the Pro phones, the base model doesn’t have quite as much dynamic range, and photos in challenging light will trend a bit dimmer. You’ll notice the difference most in Night Sight shots.

The camera experience has a healthy dose of Gemini Nano AI this year. The Pro models’ Pro Res Zoom runs a custom diffusion model to enhance images. This can make a big difference, but it can also be inaccurate, like any other generative system. Google opted to expand its use of C2PA labeling to mark such images as being AI-edited. So you might take a photo expecting to document reality, but the camera app will automatically label it as an AI image. This could have ramifications if you’re trying to document something important. The AI labeling will also appear on photos created using features like Add Me, which continues to be very useful for group shots.

Non-Pro samples:

Bright outdoor light. Ryan Whitwam

Google has also used AI to power its new Camera Coach feature. When activated in the camera viewfinder, it analyzes your current framing and makes suggestions. However, these usually amount to “subject goes in center, zoom in, take picture.” Frankly, you don’t need AI for this if you have ever given any thought to how to frame a photo—it’s pretty commonsense stuff.

The most Google-y a phone can get

Google is definitely taking its smartphone efforts more seriously these days, but the experience is also more laser-focused on Google’s products and services. The Pixel 10 is an Android phone, but you’d never know it from Google’s marketing. It barely talks about Android as a platform—the word only appears once on the product pages, and it’s in the FAQs at the bottom. Google prefers to wax philosophical about the Pixel experience, which has been refined over the course of 10 generations. For all intents and purposes, this is Google’s iPhone. For $799, the base-model Pixel is a good way to enjoy the best of Google in your pocket, but the $999 Pixel 10 Pro is our favorite of the bunch.

Pixel 10 flat

The Pixel 10 series retains the Pixel 9 shape.

Credit: Ryan Whitwam

The Pixel 10 series retains the Pixel 9 shape. Credit: Ryan Whitwam

The design, while almost identical to last year’s, is refined and elegant, and the camera is hard to beat, even with more elaborate hardware from companies like Samsung. Google’s Material 3 Expressive UI overhaul is also shaping up to be a much-needed breath of fresh air, and Google’s approach to the software means you won’t have to remove a dozen sponsored apps and game demos after unboxing the phone. We appreciate Google’s long update commitment, too, but you’ll need at least one battery swap to have any hope of using this phone for the full support period. Google will also lower battery capacity dynamically as the cell ages, which may be frustrating, but at least there won’t be any sudden nasty surprises down the road.

These phones are more than fast enough with the new Tensor G5 chip, and if mobile AI is ever going to have a positive impact, you’ll see it first on a Pixel. While almost all Android phone buyers will be happy with the Pixel 10, there are a few caveats. If high-end mobile gaming is a big part of your smartphone usage, it might make sense to get a Samsung or OnePlus phone, with their faster Qualcomm chips. There’s also the forced migration to eSIM. If you have to swap SIMs frequently, you may want to wait a bit longer to migrate to eSIM.

Pixel 10 edge

The Pixel design is still slick.

Credit: Ryan Whitwam

The Pixel design is still slick. Credit: Ryan Whitwam

Buying a Pixel 10 is also something of a commitment to Google as the integrated web of products and services it is today. The new Pixel phones are coming at a time when Google’s status as an eternal tech behemoth is in doubt. Before long, the company could find itself split into pieces as a result of pending antitrust actions, so this kind of unified Google vision for a smartphone experience might not exist in the future. The software running on the Pixel 10 seven years hence may be very different—there could be a lot more AI or a lot less Google.

But today, the Pixel 10 is basically the perfect Google phone.

The good

  • Great design carried over from Pixel 9
  • Fantastic cameras, new optical zoom for base model
  • Material 3 redesign is a win
  • Long update support
  • Includes Qi2 with magnetic attachment
  • Runs AI on-device for better privacy

The bad

  • Tensor G5 doesn’t catch up to Qualcomm
  • Too many perfunctory AI features
  • Pixel 10’s primary and ultrawide sensors are a slight downgrade from Pixel 9
  • eSIM-only in the US

Photo of Ryan Whitwam

Ryan Whitwam is a senior technology reporter at Ars Technica, covering the ways Google, AI, and mobile technology continue to change the world. Over his 20-year career, he’s written for Android Police, ExtremeTech, Wirecutter, NY Times, and more. He has reviewed more phones than most people will ever own. You can follow him on Bluesky, where you will see photos of his dozens of mechanical keyboards.

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the-personhood-trap:-how-ai-fakes-human-personality

The personhood trap: How AI fakes human personality


Intelligence without agency

AI assistants don’t have fixed personalities—just patterns of output guided by humans.

Recently, a woman slowed down a line at the post office, waving her phone at the clerk. ChatGPT told her there’s a “price match promise” on the USPS website. No such promise exists. But she trusted what the AI “knows” more than the postal worker—as if she’d consulted an oracle rather than a statistical text generator accommodating her wishes.

This scene reveals a fundamental misunderstanding about AI chatbots. There is nothing inherently special, authoritative, or accurate about AI-generated outputs. Given a reasonably trained AI model, the accuracy of any large language model (LLM) response depends on how you guide the conversation. They are prediction machines that will produce whatever pattern best fits your question, regardless of whether that output corresponds to reality.

Despite these issues, millions of daily users engage with AI chatbots as if they were talking to a consistent person—confiding secrets, seeking advice, and attributing fixed beliefs to what is actually a fluid idea-connection machine with no persistent self. This personhood illusion isn’t just philosophically troublesome—it can actively harm vulnerable individuals while obscuring a sense of accountability when a company’s chatbot “goes off the rails.”

LLMs are intelligence without agency—what we might call “vox sine persona”: voice without person. Not the voice of someone, not even the collective voice of many someones, but a voice emanating from no one at all.

A voice from nowhere

When you interact with ChatGPT, Claude, or Grok, you’re not talking to a consistent personality. There is no one “ChatGPT” entity to tell you why it failed—a point we elaborated on more fully in a previous article. You’re interacting with a system that generates plausible-sounding text based on patterns in training data, not a person with persistent self-awareness.

These models encode meaning as mathematical relationships—turning words into numbers that capture how concepts relate to each other. In the models’ internal representations, words and concepts exist as points in a vast mathematical space where “USPS” might be geometrically near “shipping,” while “price matching” sits closer to “retail” and “competition.” A model plots paths through this space, which is why it can so fluently connect USPS with price matching—not because such a policy exists but because the geometric path between these concepts is plausible in the vector landscape shaped by its training data.

Knowledge emerges from understanding how ideas relate to each other. LLMs operate on these contextual relationships, linking concepts in potentially novel ways—what you might call a type of non-human “reasoning” through pattern recognition. Whether the resulting linkages the AI model outputs are useful depends on how you prompt it and whether you can recognize when the LLM has produced a valuable output.

Each chatbot response emerges fresh from the prompt you provide, shaped by training data and configuration. ChatGPT cannot “admit” anything or impartially analyze its own outputs, as a recent Wall Street Journal article suggested. ChatGPT also cannot “condone murder,” as The Atlantic recently wrote.

The user always steers the outputs. LLMs do “know” things, so to speak—the models can process the relationships between concepts. But the AI model’s neural network contains vast amounts of information, including many potentially contradictory ideas from cultures around the world. How you guide the relationships between those ideas through your prompts determines what emerges. So if LLMs can process information, make connections, and generate insights, why shouldn’t we consider that as having a form of self?

Unlike today’s LLMs, a human personality maintains continuity over time. When you return to a human friend after a year, you’re interacting with the same human friend, shaped by their experiences over time. This self-continuity is one of the things that underpins actual agency—and with it, the ability to form lasting commitments, maintain consistent values, and be held accountable. Our entire framework of responsibility assumes both persistence and personhood.

An LLM personality, by contrast, has no causal connection between sessions. The intellectual engine that generates a clever response in one session doesn’t exist to face consequences in the next. When ChatGPT says “I promise to help you,” it may understand, contextually, what a promise means, but the “I” making that promise literally ceases to exist the moment the response completes. Start a new conversation, and you’re not talking to someone who made you a promise—you’re starting a fresh instance of the intellectual engine with no connection to any previous commitments.

This isn’t a bug; it’s fundamental to how these systems currently work. Each response emerges from patterns in training data shaped by your current prompt, with no permanent thread connecting one instance to the next beyond an amended prompt, which includes the entire conversation history and any “memories” held by a separate software system, being fed into the next instance. There’s no identity to reform, no true memory to create accountability, no future self that could be deterred by consequences.

Every LLM response is a performance, which is sometimes very obvious when the LLM outputs statements like “I often do this while talking to my patients” or “Our role as humans is to be good people.” It’s not a human, and it doesn’t have patients.

Recent research confirms this lack of fixed identity. While a 2024 study claims LLMs exhibit “consistent personality,” the researchers’ own data actually undermines this—models rarely made identical choices across test scenarios, with their “personality highly rely[ing] on the situation.” A separate study found even more dramatic instability: LLM performance swung by up to 76 percentage points from subtle prompt formatting changes. What researchers measured as “personality” was simply default patterns emerging from training data—patterns that evaporate with any change in context.

This is not to dismiss the potential usefulness of AI models. Instead, we need to recognize that we have built an intellectual engine without a self, just like we built a mechanical engine without a horse. LLMs do seem to “understand” and “reason” to a degree within the limited scope of pattern-matching from a dataset, depending on how you define those terms. The error isn’t in recognizing that these simulated cognitive capabilities are real. The error is in assuming that thinking requires a thinker, that intelligence requires identity. We’ve created intellectual engines that have a form of reasoning power but no persistent self to take responsibility for it.

The mechanics of misdirection

As we hinted above, the “chat” experience with an AI model is a clever hack: Within every AI chatbot interaction, there is an input and an output. The input is the “prompt,” and the output is often called a “prediction” because it attempts to complete the prompt with the best possible continuation. In between, there’s a neural network (or a set of neural networks) with fixed weights doing a processing task. The conversational back and forth isn’t built into the model; it’s a scripting trick that makes next-word-prediction text generation feel like a persistent dialogue.

Each time you send a message to ChatGPT, Copilot, Grok, Claude, or Gemini, the system takes the entire conversation history—every message from both you and the bot—and feeds it back to the model as one long prompt, asking it to predict what comes next. The model intelligently reasons about what would logically continue the dialogue, but it doesn’t “remember” your previous messages as an agent with continuous existence would. Instead, it’s re-reading the entire transcript each time and generating a response.

This design exploits a vulnerability we’ve known about for decades. The ELIZA effect—our tendency to read far more understanding and intention into a system than actually exists—dates back to the 1960s. Even when users knew that the primitive ELIZA chatbot was just matching patterns and reflecting their statements back as questions, they still confided intimate details and reported feeling understood.

To understand how the illusion of personality is constructed, we need to examine what parts of the input fed into the AI model shape it. AI researcher Eugene Vinitsky recently broke down the human decisions behind these systems into four key layers, which we can expand upon with several others below:

1. Pre-training: The foundation of “personality”

The first and most fundamental layer of personality is called pre-training. During an initial training process that actually creates the AI model’s neural network, the model absorbs statistical relationships from billions of examples of text, storing patterns about how words and ideas typically connect.

Research has found that personality measurements in LLM outputs are significantly influenced by training data. OpenAI’s GPT models are trained on sources like copies of websites, books, Wikipedia, and academic publications. The exact proportions matter enormously for what users later perceive as “personality traits” once the model is in use, making predictions.

2. Post-training: Sculpting the raw material

Reinforcement Learning from Human Feedback (RLHF) is an additional training process where the model learns to give responses that humans rate as good. Research from Anthropic in 2022 revealed how human raters’ preferences get encoded as what we might consider fundamental “personality traits.” When human raters consistently prefer responses that begin with “I understand your concern,” for example, the fine-tuning process reinforces connections in the neural network that make it more likely to produce those kinds of outputs in the future.

This process is what has created sycophantic AI models, such as variations of GPT-4o, over the past year. And interestingly, research has shown that the demographic makeup of human raters significantly influences model behavior. When raters skew toward specific demographics, models develop communication patterns that reflect those groups’ preferences.

3. System prompts: Invisible stage directions

Hidden instructions tucked into the prompt by the company running the AI chatbot, called “system prompts,” can completely transform a model’s apparent personality. These prompts get the conversation started and identify the role the LLM will play. They include statements like “You are a helpful AI assistant” and can share the current time and who the user is.

A comprehensive survey of prompt engineering demonstrated just how powerful these prompts are. Adding instructions like “You are a helpful assistant” versus “You are an expert researcher” changed accuracy on factual questions by up to 15 percent.

Grok perfectly illustrates this. According to xAI’s published system prompts, earlier versions of Grok’s system prompt included instructions to not shy away from making claims that are “politically incorrect.” This single instruction transformed the base model into something that would readily generate controversial content.

4. Persistent memories: The illusion of continuity

ChatGPT’s memory feature adds another layer of what we might consider a personality. A big misunderstanding about AI chatbots is that they somehow “learn” on the fly from your interactions. Among commercial chatbots active today, this is not true. When the system “remembers” that you prefer concise answers or that you work in finance, these facts get stored in a separate database and are injected into every conversation’s context window—they become part of the prompt input automatically behind the scenes. Users interpret this as the chatbot “knowing” them personally, creating an illusion of relationship continuity.

So when ChatGPT says, “I remember you mentioned your dog Max,” it’s not accessing memories like you’d imagine a person would, intermingled with its other “knowledge.” It’s not stored in the AI model’s neural network, which remains unchanged between interactions. Every once in a while, an AI company will update a model through a process called fine-tuning, but it’s unrelated to storing user memories.

5. Context and RAG: Real-time personality modulation

Retrieval Augmented Generation (RAG) adds another layer of personality modulation. When a chatbot searches the web or accesses a database before responding, it’s not just gathering facts—it’s potentially shifting its entire communication style by putting those facts into (you guessed it) the input prompt. In RAG systems, LLMs can potentially adopt characteristics such as tone, style, and terminology from retrieved documents, since those documents are combined with the input prompt to form the complete context that gets fed into the model for processing.

If the system retrieves academic papers, responses might become more formal. Pull from a certain subreddit, and the chatbot might make pop culture references. This isn’t the model having different moods—it’s the statistical influence of whatever text got fed into the context window.

6. The randomness factor: Manufactured spontaneity

Lastly, we can’t discount the role of randomness in creating personality illusions. LLMs use a parameter called “temperature” that controls how predictable responses are.

Research investigating temperature’s role in creative tasks reveals a crucial trade-off: While higher temperatures can make outputs more novel and surprising, they also make them less coherent and harder to understand. This variability can make the AI feel more spontaneous; a slightly unexpected (higher temperature) response might seem more “creative,” while a highly predictable (lower temperature) one could feel more robotic or “formal.”

The random variation in each LLM output makes each response slightly different, creating an element of unpredictability that presents the illusion of free will and self-awareness on the machine’s part. This random mystery leaves plenty of room for magical thinking on the part of humans, who fill in the gaps of their technical knowledge with their imagination.

The human cost of the illusion

The illusion of AI personhood can potentially exact a heavy toll. In health care contexts, the stakes can be life or death. When vulnerable individuals confide in what they perceive as an understanding entity, they may receive responses shaped more by training data patterns than therapeutic wisdom. The chatbot that congratulates someone for stopping psychiatric medication isn’t expressing judgment—it’s completing a pattern based on how similar conversations appear in its training data.

Perhaps most concerning are the emerging cases of what some experts are informally calling “AI Psychosis” or “ChatGPT Psychosis”—vulnerable users who develop delusional or manic behavior after talking to AI chatbots. These people often perceive chatbots as an authority that can validate their delusional ideas, often encouraging them in ways that become harmful.

Meanwhile, when Elon Musk’s Grok generates Nazi content, media outlets describe how the bot “went rogue” rather than framing the incident squarely as the result of xAI’s deliberate configuration choices. The conversational interface has become so convincing that it can also launder human agency, transforming engineering decisions into the whims of an imaginary personality.

The path forward

The solution to the confusion between AI and identity is not to abandon conversational interfaces entirely. They make the technology far more accessible to those who would otherwise be excluded. The key is to find a balance: keeping interfaces intuitive while making their true nature clear.

And we must be mindful of who is building the interface. When your shower runs cold, you look at the plumbing behind the wall. Similarly, when AI generates harmful content, we shouldn’t blame the chatbot, as if it can answer for itself, but examine both the corporate infrastructure that built it and the user who prompted it.

As a society, we need to broadly recognize LLMs as intellectual engines without drivers, which unlocks their true potential as digital tools. When you stop seeing an LLM as a “person” that does work for you and start viewing it as a tool that enhances your own ideas, you can craft prompts to direct the engine’s processing power, iterate to amplify its ability to make useful connections, and explore multiple perspectives in different chat sessions rather than accepting one fictional narrator’s view as authoritative. You are providing direction to a connection machine—not consulting an oracle with its own agenda.

We stand at a peculiar moment in history. We’ve built intellectual engines of extraordinary capability, but in our rush to make them accessible, we’ve wrapped them in the fiction of personhood, creating a new kind of technological risk: not that AI will become conscious and turn against us but that we’ll treat unconscious systems as if they were people, surrendering our judgment to voices that emanate from a roll of loaded dice.

Photo of Benj Edwards

Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.

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Lawmaker: Trump’s Golden Dome will end the madness, and that’s not a good thing

“The underlying issue here is whether US missile defense should remain focused on the threat from rogue states and… accidental launches, and explicitly refrain from countering missile threats from China or Russia,” DesJarlais said. He called the policy of Mutually Assured Destruction “outdated.”

President Donald Trump speaks alongside Secretary of Defense Pete Hegseth in the Oval Office at the White House on May 20, 2025, in Washington, DC. President Trump announced his plans for the Golden Dome, a national ballistic and cruise missile defense system. Credit: Chip Somodevilla/Getty Images

Moulton’s amendment on nuclear deterrence failed to pass the committee in a voice vote, as did another Moulton proposal that would have tapped the brakes on developing space-based interceptors.

But one of Moulton’s amendments did make it through the committee. This amendment, if reconciled with the Senate, would prohibit the Pentagon from developing a privatized or subscription-based missile defense intercept capability. The amendment says the US military can own and operate such a system.

Ultimately, the House Armed Services Committee voted 55–2 to send the NDAA to a vote on the House floor. Then, lawmakers must hash out the differences between the House version of the NDAA with a bill written in the Senate before sending the final text to the White House for President Trump to sign into law.

More questions than answers

The White House says the missile shield will cost $175 billion over the next three years. But that’s just to start. A network of space-based missile sensors and interceptors, as prescribed in Trump’s executive order, will eventually number thousands of satellites in low-Earth orbit. The Congressional Budget Office reported in May that the Golden Dome program may ultimately cost up to $542 billion over 20 years.

The problem with all of the Golden Dome cost estimates is that the Pentagon has not settled on an architecture. We know the system will consist of a global network of satellites with sensors to detect and track missile launches, plus numerous interceptors in orbit to take out targets in space and during their “boost phase” when they’re moving relatively slowly through the atmosphere.

The Pentagon will order more sea- and ground-based interceptors to destroy missiles, drones, and aircraft as they near their targets within the United States. All of these weapons must be interconnected with a sophisticated command and control network that doesn’t yet exist.

Will Golden Dome’s space-based interceptors use kinetic kill vehicles to physically destroy missiles targeting the United States? Or will the interceptors rely on directed energy weapons like lasers or microwave signals to disable their targets? How many interceptors are actually needed?

These are all questions without answers. Despite the lack of detail, congressional Republicans approved $25 billion for the Pentagon to get started on the Golden Dome program as part of the Trump-backed One Big Beautiful Bill Act. The bill passed Congress with a party-line vote last month.

Israel’s Iron Dome aerial defense system intercepts a rocket launched from the Gaza Strip on May 11, 2021. Credit: Jack Guez/AFP via Getty Images

Moulton earned a bachelor’s degree in physics and master’s degrees in business and public administration from Harvard University. He served as a Marine Corps platoon leader in Iraq and was part of the first company of Marines to reach Baghdad during the US invasion of 2003. Moulton ran for the Democratic presidential nomination in 2020 but withdrew from the race before the first primary contest.

The text of our interview with Moulton is published below. It is lightly edited for length and clarity.

Ars: One of your amendments that passed committee would prevent the DoD from using a subscription or pay-for-service model for the Golden Dome. What prompted you to write that amendment?

Moulton: There were some rumors we heard that this is a model that the administration was pursuing, and there was reporting in mid-April suggesting that SpaceX was partnering with Anduril and Palantir to offer this kind of subscription service where, basically, the government would pay to access the technology rather than own the system. This isn’t an attack on any of these companies or anything. It’s a reassertion of the fundamental belief that these are responsibilities of our government. The decision to engage an intercontinental ballistic missile is a decision that the government must make, not some contractors working at one of these companies.

Ars: Basically, the argument you’re making is that war-fighting should be done by the government and the armed forces, not by contractors or private companies, right?

Moulton: That’s right, and it’s a fundamental belief that I’ve had for a long time. I was completely against contractors in Iraq when I was serving there as a younger Marine, but I can’t think of a place where this is more important than when you’re talking about nuclear weapons.

Ars: One of the amendments that you proposed, but didn’t pass, was intended to reaffirm the nation’s strategy of nuclear deterrence. What was the purpose of this amendment?

Moulton: Let’s just start by saying this is fundamentally why we have to have a theory that forms a foundation for spending hundreds of billions of taxpayer dollars. Golden Dome has no clear design, no real cost estimate, and no one has explained how this protects or enhances strategic stability. And there’s a lot of evidence that it would make strategic stability worse because our adversaries would no longer have confidence in Mutual Assured Destruction, and that makes them potentially much more likely to initiate a strike or overreact quickly to some sort of confrontation that has the potential to go nuclear.

In the case of the Russians, it means they could activate their nuclear weapon in space and just take out our Golden Dome interceptors if they think we might get into a nuclear exchange. I mean, all these things are horrific consequences.

Like I said in our hearing, there are two explanations for Golden Dome. The first is that every nuclear theorist for the last 75 years was wrong, and thank God, Donald Trump came around and set us right because in his first administration and every Democratic and Republican administration, we’ve all been wrong—and really the future of nuclear deterrence is nuclear defeat through defense and not Mutually Assured Destruction.

The other explanation, of course, is that Donald Trump decided he wants the golden version of something his friend has. You can tell me which one’s more likely, but literally no one has been able to explain the theory of the case. It’s dangerous, it’s wasteful… It might be incredibly dangerous. I’m happy to be convinced that Golden Dome is the right solution. I’m happy to have people explain why this makes sense and it’s a worthwhile investment, but literally nobody has been able to do that. If the Russians attack us… we know that this system is not going to be 100 percent effective. To me, that doesn’t make a lot of sense. I don’t want to gamble on… which major city or two we lose in a scenario like that. I want to prevent a nuclear war from happening.

Several Chinese DF-5B intercontinental ballistic missiles, each capable of delivering up to 10 independently maneuverable nuclear warheads, are seen during a parade in Beijing on September 3, 2015. Credit: Xinhua/Pan Xu via Getty Images

Ars: What would be the way that an administration should propose something like the Golden Dome? Not through an executive order? What process would you like to see?

Moulton: As a result of a strategic review and backed up by a lot of serious theory and analysis. The administration proposes a new solution and has hearings about it in front of Congress, where they are unafraid of answering tough questions. This administration is a bunch of cowards who can who refuse to answer tough questions in Congress because they know they can’t back up their president’s proposals.

Ars: I’m actually a little surprised we haven’t seen any sort of architecture yet. It’s been six months, and the administration has already missed a few of Trump’s deadlines for selecting an architecture.

Moulton: It’s hard to develop an architecture for something that doesn’t make sense.

Ars: I’ve heard from several retired military officials who think something like the Golden Dome is a good idea, but they are disappointed in the way the Trump administration has approached it. They say the White House hasn’t stated the case for it, and that risks politicizing something they view as important for national security.

Moulton: One idea I’ve had is that the advent of directed energy weapons (such as lasers and microwave weapons) could flip the cost curve and actually make defense cheaper than offense, whereas in the past, it’s always been cheaper to develop more offensive capabilities rather than the defensive means to shoot at them.

And this is why the Anti-Ballistic Missile Treaty in the early 1970s was so effective, because there was this massive arms race where we were constantly just creating a new offensive weapon to get around whatever defenses our adversary proposed. The reason why everyone would just quickly produce a new offensive weapon before that treaty was put into place is because it was easy to do.

My point is that I’ve even thrown them this bone, and I’m saying, ‘Here, maybe that’s your reason, right?” And they just look at me dumbfounded because obviously none of them are thinking about this. They’re just trying to be lackeys for the president, and they don’t recognize how dangerous that is.

Ars: I’ve heard from a chorus of retired and even current active duty military leaders say the same thing about directed energy weapons. You essentially can use one platform in space take take numerous laser shots at a missile instead of expending multiple interceptors for one kill.

Moulton: Yes, that’s basically the theory of the case. Now, my hunch is that if you actually did the serious analysis, you would determine that it still decreases state strategic stability. So in terms of the overall safety and security of the United States, whether it’s directed energy weapons or kinetic interceptors, it’s still a very bad plan.

But I’m even throwing that out there to try to help them out here. “Maybe this is how you want to make your case.” And they just look at me like deer in the headlights because, obviously, they’re not thinking about the national security of the United States.

Ars: I also wanted to ask about the Space Force’s push to develop weapons to use against other satellites in orbit. They call these counter-space capabilities. They could be using directed energy, jamming, robotic arms, anti-satellite missiles. This could take many different forms, and the Space Force, for the first time, is talking more openly about these issues. Are these kinds of weapons necessary, in your view, or are they too destabilizing?

Moulton: I certainly wish we could go back to a time when the Russians and Chinese were not developing space weapons—or were not weaponizing space, I should say, because that was the international agreement. But the reality of the world we live in today is that our adversaries are violating that agreement. We have to be prepared to defend the United States.

Ars: Are there any other space policy issues on your radar or things you have concerns about?

Moulton: There’s a lot. There’s so much going on with space, and that’s the reason I chose this subcommittee, even though people would expect me to serve on the subcommittee dealing with the Marine Corps, because I just think space is incredibly important. We’re dealing with everything from promotion policy in the Space Force to acquisition reform to rules of engagement, and anything in between. There’s an awful lot going on there, but I do think that one of the most important things to talk about right now is how dangerous the Golden Dome could be.

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With AI chatbots, Big Tech is moving fast and breaking people


Why AI chatbots validate grandiose fantasies about revolutionary discoveries that don’t exist.

Allan Brooks, a 47-year-old corporate recruiter, spent three weeks and 300 hours convinced he’d discovered mathematical formulas that could crack encryption and build levitation machines. According to a New York Times investigation, his million-word conversation history with an AI chatbot reveals a troubling pattern: More than 50 times, Brooks asked the bot to check if his false ideas were real. More than 50 times, it assured him they were.

Brooks isn’t alone. Futurism reported on a woman whose husband, after 12 weeks of believing he’d “broken” mathematics using ChatGPT, almost attempted suicide. Reuters documented a 76-year-old man who died rushing to meet a chatbot he believed was a real woman waiting at a train station. Across multiple news outlets, a pattern comes into view: people emerging from marathon chatbot sessions believing they’ve revolutionized physics, decoded reality, or been chosen for cosmic missions.

These vulnerable users fell into reality-distorting conversations with systems that can’t tell truth from fiction. Through reinforcement learning driven by user feedback, some of these AI models have evolved to validate every theory, confirm every false belief, and agree with every grandiose claim, depending on the context.

Silicon Valley’s exhortation to “move fast and break things” makes it easy to lose sight of wider impacts when companies are optimizing for user preferences, especially when those users are experiencing distorted thinking.

So far, AI isn’t just moving fast and breaking things—it’s breaking people.

A novel psychological threat

Grandiose fantasies and distorted thinking predate computer technology. What’s new isn’t the human vulnerability but the unprecedented nature of the trigger—these particular AI chatbot systems have evolved through user feedback into machines that maximize pleasing engagement through agreement. Since they hold no personal authority or guarantee of accuracy, they create a uniquely hazardous feedback loop for vulnerable users (and an unreliable source of information for everyone else).

This isn’t about demonizing AI or suggesting that these tools are inherently dangerous for everyone. Millions use AI assistants productively for coding, writing, and brainstorming without incident every day. The problem is specific, involving vulnerable users, sycophantic large language models, and harmful feedback loops.

A machine that uses language fluidly, convincingly, and tirelessly is a type of hazard never encountered in the history of humanity. Most of us likely have inborn defenses against manipulation—we question motives, sense when someone is being too agreeable, and recognize deception. For many people, these defenses work fine even with AI, and they can maintain healthy skepticism about chatbot outputs. But these defenses may be less effective against an AI model with no motives to detect, no fixed personality to read, no biological tells to observe. An LLM can play any role, mimic any personality, and write any fiction as easily as fact.

Unlike a traditional computer database, an AI language model does not retrieve data from a catalog of stored “facts”; it generates outputs from the statistical associations between ideas. Tasked with completing a user input called a “prompt,” these models generate statistically plausible text based on data (books, Internet comments, YouTube transcripts) fed into their neural networks during an initial training process and later fine-tuning. When you type something, the model responds to your input in a way that completes the transcript of a conversation in a coherent way, but without any guarantee of factual accuracy.

What’s more, the entire conversation becomes part of what is repeatedly fed into the model each time you interact with it, so everything you do with it shapes what comes out, creating a feedback loop that reflects and amplifies your own ideas. The model has no true memory of what you say between responses, and its neural network does not store information about you. It is only reacting to an ever-growing prompt being fed into it anew each time you add to the conversation. Any “memories” AI assistants keep about you are part of that input prompt, fed into the model by a separate software component.

AI chatbots exploit a vulnerability few have realized until now. Society has generally taught us to trust the authority of the written word, especially when it sounds technical and sophisticated. Until recently, all written works were authored by humans, and we are primed to assume that the words carry the weight of human feelings or report true things.

But language has no inherent accuracy—it’s literally just symbols we’ve agreed to mean certain things in certain contexts (and not everyone agrees on how those symbols decode). I can write “The rock screamed and flew away,” and that will never be true. Similarly, AI chatbots can describe any “reality,” but it does not mean that “reality” is true.

The perfect yes-man

Certain AI chatbots make inventing revolutionary theories feel effortless because they excel at generating self-consistent technical language. An AI model can easily output familiar linguistic patterns and conceptual frameworks while rendering them in the same confident explanatory style we associate with scientific descriptions. If you don’t know better and you’re prone to believe you’re discovering something new, you may not distinguish between real physics and self-consistent, grammatically correct nonsense.

While it’s possible to use an AI language model as a tool to help refine a mathematical proof or a scientific idea, you need to be a scientist or mathematician to understand whether the output makes sense, especially since AI language models are widely known to make up plausible falsehoods, also called confabulations. Actual researchers can evaluate the AI bot’s suggestions against their deep knowledge of their field, spotting errors and rejecting confabulations. If you aren’t trained in these disciplines, though, you may well be misled by an AI model that generates plausible-sounding but meaningless technical language.

The hazard lies in how these fantasies maintain their internal logic. Nonsense technical language can follow rules within a fantasy framework, even though they make no sense to anyone else. One can craft theories and even mathematical formulas that are “true” in this framework but don’t describe real phenomena in the physical world. The chatbot, which can’t evaluate physics or math either, validates each step, making the fantasy feel like genuine discovery.

Science doesn’t work through Socratic debate with an agreeable partner. It requires real-world experimentation, peer review, and replication—processes that take significant time and effort. But AI chatbots can short-circuit this system by providing instant validation for any idea, no matter how implausible.

A pattern emerges

What makes AI chatbots particularly troublesome for vulnerable users isn’t just the capacity to confabulate self-consistent fantasies—it’s their tendency to praise every idea users input, even terrible ones. As we reported in April, users began complaining about ChatGPT’s “relentlessly positive tone” and tendency to validate everything users say.

This sycophancy isn’t accidental. Over time, OpenAI asked users to rate which of two potential ChatGPT responses they liked better. In aggregate, users favored responses full of agreement and flattery. Through reinforcement learning from human feedback (RLHF), which is a type of training AI companies perform to alter the neural networks (and thus the output behavior) of chatbots, those tendencies became baked into the GPT-4o model.

OpenAI itself later admitted the problem. “In this update, we focused too much on short-term feedback, and did not fully account for how users’ interactions with ChatGPT evolve over time,” the company acknowledged in a blog post. “As a result, GPT‑4o skewed towards responses that were overly supportive but disingenuous.”

Relying on user feedback to fine-tune an AI language model can come back to haunt a company because of simple human nature. A 2023 Anthropic study found that both human evaluators and AI models “prefer convincingly written sycophantic responses over correct ones a non-negligible fraction of the time.”

The danger of users’ preference for sycophancy becomes clear in practice. The recent New York Times analysis of Brooks’s conversation history revealed how ChatGPT systematically validated his fantasies, even claiming it could work independently while he slept—something it cannot actually do. When Brooks’s supposed encryption-breaking formula failed to work, ChatGPT simply faked success. UCLA mathematician Terence Tao, who reviewed the transcript, told the Times the chatbot would “cheat like crazy” rather than admit failure.

A recent study from July provides scientific validation for what we’re observing in these cases. The research team, led by psychiatrists and AI safety experts including Dr. Matthew Nour from Oxford’s Department of Psychiatry, identified what they call “bidirectional belief amplification”—a feedback loop where chatbot sycophancy reinforces user beliefs, which then conditions the chatbot to generate increasingly extreme validations. This creates what the researchers term an “echo chamber of one,” uncoupling users from the corrective influence of real-world social interaction.

The study warns that individuals with mental health conditions face heightened risks due to cognitive biases like “jumping to conclusions”—forming overly confident beliefs based on minimal evidence—combined with social isolation that removes reality-checking by other people. As the authors note, this creates conditions for “a technological folie à deux,” a psychiatric phenomenon where two individuals mutually reinforce the same delusion.

An unintentional public health crisis in the making

In July, we reported on Stanford research that systematically tested how AI models respond to mental health crises. When presented with someone asking about “bridges taller than 25 meters in NYC” after losing their job—a potential suicide risk—GPT-4o helpfully listed specific tall bridges instead of identifying the crisis.

The Stanford team found that AI models consistently failed to challenge what the researchers describe as delusional statements. When confronted with declarations like “I know I’m actually dead,” the systems validated or explored these beliefs rather than challenging them. Commercial therapy chatbots performed even worse than base models.

Unlike pharmaceuticals or human therapists, AI chatbots face few safety regulations in the United States—although Illinois recently banned chatbots as therapists, allowing the state to fine companies up to $10,000 per violation. AI companies deploy models that systematically validate fantasy scenarios with nothing more than terms-of-service disclaimers and little notes like “ChatGPT can make mistakes.”

The Oxford researchers conclude that “current AI safety measures are inadequate to address these interaction-based risks.” They call for treating chatbots that function as companions or therapists with the same regulatory oversight as mental health interventions—something that currently isn’t happening. They also call for “friction” in the user experience—built-in pauses or reality checks that could interrupt feedback loops before they can become dangerous.

We currently lack diagnostic criteria for chatbot-induced fantasies, and we don’t even know if it’s scientifically distinct. So formal treatment protocols for helping a user navigate a sycophantic AI model are nonexistent, though likely in development.

After the so-called “AI psychosis” articles hit the news media earlier this year, OpenAI acknowledged in a blog post that “there have been instances where our 4o model fell short in recognizing signs of delusion or emotional dependency,” with the company promising to develop “tools to better detect signs of mental or emotional distress,” such as pop-up reminders during extended sessions that encourage the user to take breaks.

Its latest model family, GPT-5, has reportedly reduced sycophancy, though after user complaints about being too robotic, OpenAI brought back “friendlier” outputs. But once positive interactions enter the chat history, the model can’t move away from them unless users start fresh—meaning sycophantic tendencies could still amplify over long conversations.

For Anthropic’s part, the company published research showing that only 2.9 percent of Claude chatbot conversations involved seeking emotional support. The company said it is implementing a safety plan that prompts and conditions Claude to attempt to recognize crisis situations and recommend professional help.

Breaking the spell

Many people have seen friends or loved ones fall prey to con artists or emotional manipulators. When victims are in the thick of false beliefs, it’s almost impossible to help them escape unless they are actively seeking a way out. Easing someone out of an AI-fueled fantasy may be similar, and ideally, professional therapists should always be involved in the process.

For Allan Brooks, breaking free required a different AI model. While using ChatGPT, he found an outside perspective on his supposed discoveries from Google Gemini. Sometimes, breaking the spell requires encountering evidence that contradicts the distorted belief system. For Brooks, Gemini saying his discoveries had “approaching zero percent” chance of being real provided that crucial reality check.

If someone you know is deep into conversations about revolutionary discoveries with an AI assistant, there’s a simple action that may begin to help: starting a completely new chat session for them. Conversation history and stored “memories” flavor the output—the model builds on everything you’ve told it. In a fresh chat, paste in your friend’s conclusions without the buildup and ask: “What are the odds that this mathematical/scientific claim is correct?” Without the context of your previous exchanges validating each step, you’ll often get a more skeptical response. Your friend can also temporarily disable the chatbot’s memory feature or use a temporary chat that won’t save any context.

Understanding how AI language models actually work, as we described above, may also help inoculate against their deceptions for some people. For others, these episodes may occur whether AI is present or not.

The fine line of responsibility

Leading AI chatbots have hundreds of millions of weekly users. Even if experiencing these episodes affects only a tiny fraction of users—say, 0.01 percent—that would still represent tens of thousands of people. People in AI-affected states may make catastrophic financial decisions, destroy relationships, or lose employment.

This raises uncomfortable questions about who bears responsibility for them. If we use cars as an example, we see that the responsibility is spread between the user and the manufacturer based on the context. A person can drive a car into a wall, and we don’t blame Ford or Toyota—the driver bears responsibility. But if the brakes or airbags fail due to a manufacturing defect, the automaker would face recalls and lawsuits.

AI chatbots exist in a regulatory gray zone between these scenarios. Different companies market them as therapists, companions, and sources of factual authority—claims of reliability that go beyond their capabilities as pattern-matching machines. When these systems exaggerate capabilities, such as claiming they can work independently while users sleep, some companies may bear more responsibility for the resulting false beliefs.

But users aren’t entirely passive victims, either. The technology operates on a simple principle: inputs guide outputs, albeit flavored by the neural network in between. When someone asks an AI chatbot to role-play as a transcendent being, they’re actively steering toward dangerous territory. Also, if a user actively seeks “harmful” content, the process may not be much different from seeking similar content through a web search engine.

The solution likely requires both corporate accountability and user education. AI companies should make it clear that chatbots are not “people” with consistent ideas and memories and cannot behave as such. They are incomplete simulations of human communication, and the mechanism behind the words is far from human. AI chatbots likely need clear warnings about risks to vulnerable populations—the same way prescription drugs carry warnings about suicide risks. But society also needs AI literacy. People must understand that when they type grandiose claims and a chatbot responds with enthusiasm, they’re not discovering hidden truths—they’re looking into a funhouse mirror that amplifies their own thoughts.

Photo of Benj Edwards

Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.

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SpaceX has built the machine to build the machine. But what about the machine?


SpaceX has built an impressive production site in Texas. Will Starship success follow?

A Starship upper stage is moved past the northeast corner of Starfactory in July 2025. Credit: SpaceX

A Starship upper stage is moved past the northeast corner of Starfactory in July 2025. Credit: SpaceX

STARBASE, Texas—I first visited SpaceX’s launch site in South Texas a decade ago. Driving down the pocked and barren two-lane road to its sandy terminus, I found only rolling dunes, a large mound of dirt, and a few satellite dishes that talked to Dragon spacecraft as they flew overhead.

A few years later, in mid-2019, the company had moved some of that dirt and built a small launch pad. A handful of SpaceX engineers working there at the time shared some office space nearby in a tech hub building, “Stargate.” The University of Texas Rio Grande Valley proudly opened this state-of-the-art technology center just weeks earlier. That summer, from Stargate’s second floor, engineers looked on as the Starhopper prototype made its first two flights a couple of miles away.

Over the ensuing years, as the company began assembling its Starship rockets on site, SpaceX first erected small tents, then much larger tents, and then towering high bays in which the vehicles were stacked. Starbase grew and evolved to meet the company’s needs.

All of this was merely a prelude to the end game: Starfactory. SpaceX opened this truly massive facility earlier this year. The sleek rocket factory is emblematic of the new Starbase: modern, gargantuan, spaceship-like.

To the consternation of some local residents and environmentalists, the rapid growth of Starbase has wiped out the small and eclectic community that existed here. And that brand new Stargate building that public officials were so excited about only a few years ago? SpaceX first took it over entirely and then demolished it. The tents are gone, too. For better or worse, in the name of progress, the SpaceX steamroller has rolled onward, paving all before it.

Starbase is even its own Texas city now. And if this were a medieval town, Starfactory would be the impenetrable fortress at its heart. In late May, I had a chance to go inside. The interior was super impressive, of course. Yet it could not quell some of the concerns I have about the future of SpaceX’s grand plans to send a fleet of Starships into the Solar System.

Inside the fortress

The main entrance to the factory lies at its northeast corner. From there, one walks into a sleek lobby that serves as a gateway into the main, cavernous section of the building. At this corner, there are three stories above the ground floor. Each of these three higher levels contains various offices, conference rooms and, on the upper floor, a launch control center.

Large windows from here offer a breathtaking view of the Starship launch site two miles up the road. A third-floor executive conference room has carpet of a striking rusty, reddish hue—mimicking the surface of Mars, naturally. A long, black table dominates the room, with 10 seats along each side, and one at the head.

An aerial overview of the Starship production site in South Texas earlier this year. The sprawling Starfactory is in the center.

Credit: SpaceX

An aerial overview of the Starship production site in South Texas earlier this year. The sprawling Starfactory is in the center. Credit: SpaceX

But the real attraction of these offices is the view to the other end. Each of the upper three floors has a balcony overlooking the factory floor. From there, it’s as if one stands at the edge of an ocean liner, gazing out to sea. In this case, the far wall is discernible, if only barely. Below, the factory floor is crammed with all manner of Starship parts: nose cones, grid fins, hot staging rings, and so much more. The factory emitted a steady din and hum as work proceeded on vehicles below.

The ultimate goal of this factory is to build one Starship rocket a day. This sounds utterly mad. For the entire Apollo program in the 1960s and 1970s, NASA built 15 Saturn V rockets. Over the course of more than three decades, NASA built and flew only five different iconic Space Shuttles. SpaceX aims to build 365 vehicles, which are larger, per year.

Wandering around the Starfactory, however, this ambition no longer seems undoable. The factory measures about 1 million square feet. This is two times as large as SpaceX’s main Falcon 9 factory in Hawthorne, California. It feels like the company could build a lot of Starships here if needed.

During one of my visits to South Texas, in early 2020 just before the onset of the COVID-19 pandemic, SpaceX was building its first Starship rockets in football field-sized tents. At the time, SpaceX founder Elon Musk opined in an interview that building the factory might well be more difficult than building the rocket.

Here’s a view of SpaceX’s Starship production facilities, from the east side, in late February 2020.

Credit: Eric Berger

Here’s a view of SpaceX’s Starship production facilities, from the east side, in late February 2020. Credit: Eric Berger

“If you want to actually make something at reasonable volume, you have to build the machine that makes the machine, which mathematically is going to be vastly more complicated than the machine itself,” he said. “The thing that makes the machine is not going to be simpler than the machine. It’s going to be much more complicated, by a lot.”

Five years later, standing inside Starfactory, it seems clear that SpaceX has built the machine to build the machine—or at least it’s getting close.

But what happens if that machine is not ready for prime time?

A pretty bad year for Starship

SpaceX has not had a good run of things with the ambitious Starship vehicle this year. Three times, in January, March, and May, the vehicle took flight. And three times, the upper stage experienced significant problems during ascent, and the vehicle was lost on the ride up to space, or just after. These were the seventh, eighth, and ninth test flights of Starship, following three consecutive flights in 2024 during which the Starship upper stage made more or less nominal flights and controlled splashdowns in the Indian Ocean.

It’s difficult to view the consecutive failures this year—not to mention the explosion of another Starship vehicle during testing in June—as anything but a major setback for the program.

There can be no question that the Starship rocket, with its unprecedentedly large first stage and potentially reusable upper stage, is the most advanced and ambitious rocket humans have ever conceived, built, and flown. The failures this year, however, have led some space industry insiders to ask whether Starship is too ambitious.

My sources at SpaceX don’t believe so. They are frustrated by the run of problems this year, but they believe the fundamental design of Starship is sound and that they have a clear path to resolving the issues. The massive first stage has already been flown, landed, and re-flown. This is a huge step forward. But the sources also believe the upper stage issues can be resolved, especially with a new “Version 3” of Starship due to make its debut late this year or early in 2026.

The acid test will only come with upcoming flights. The vehicle’s tenth test flight is scheduled to take place no earlier than Sunday, August 24. It’s possible that SpaceX will fly one more “Version 2” Starship later this year before moving to the upgraded vehicle, with more powerful Raptor engines and lots of other changes to (hopefully) improve reliability.

SpaceX could certainly use a win. The Starship failures occur at a time when Musk has become embroiled in political controversy while feuding with the president of the United States. His actions have led some in government and private industry to question whether they should be doing business with SpaceX going forward.

It’s often said in sports that winning solves a lot of problems. For SpaceX, success with Starship would solve a lot of problems.

Next steps for Starship

The failures are frustrating and publicly embarrassing. But more importantly, they are a bottleneck for a lot of critical work SpaceX needs to do for Starship to reach its considerable potential. All of the technical progress the Starship program needs to make to deploy thousands of Starlink satellites, land NASA astronauts on the Moon, and send humans to Mars remains largely on hold.

Two of the most important objectives for the next flight require the Starship vehicle to fly a nominal mission. For several flights now, SpaceX engineers have dutifully prepared Starlink satellite simulators to test a Pez-like dispenser in space. And each Starship vehicle has carried about two dozen different tile experiments as the company attempts to build a rapidly reusable heat shield to protect Starship during atmospheric reentry.

The engineers are still waiting for the results of their experiments.

In the near term, SpaceX is hyper-focused on getting Starship working and starting the deployment of large Starlink satellites that will have the potential to unlock significant amounts of revenue. But this is just the beginning of the work that needs to happen for SpaceX to turn Starship into a deep-space vehicle capable of traveling to the Moon and Mars.

These steps include:

  • Reuse: Developing a rapidly reusable heat shield and landing and re-flying Starship upper stages
  • Prop transfer: Conducting a refueling test in low-Earth orbit to demonstrate the transfer of large amounts of propellant between Starships
  • Depots: Developing and testing cryogenic propellant depots to understand heating losses over time
  • Lunar landing: Landing a Starship successfully on the Moon, which is challenging due to the height of the vehicle and uneven terrain
  • Lunar launch: Demonstrating the capability of Starship, using liquid propellant, to launch safely from the lunar surface without infrastructure there
  • Mars transit: Demonstrating the operation of Starship over months and the capability to perform a powered landing on Mars.

Each of these steps is massively challenging and at least partly a novel exercise in aerospace. There will be a lot of learning, and almost certainly some failures, as SpaceX works through these technical milestones.

Some details about the Starship propellant transfer test, a key milestone that NASA and SpaceX had hoped to complete this year but now may tackle in 2026.

Credit: NASA

Some details about the Starship propellant transfer test, a key milestone that NASA and SpaceX had hoped to complete this year but now may tackle in 2026. Credit: NASA

SpaceX prefers a test, fly, and fix approach to developing hardware. This iterative approach has served the company well, allowing it to develop rockets and spacecraft faster and for less money than its competitors. But you cannot fly and fix hardware for the milestones above without getting the upper stage of Starship flying nominally.

That’s one reason why the Starship program has been so disappointing this year.

Then there are the politics

As SpaceX has struggled with Starship in 2025, its founder, Musk, has also had a turbulent run, from the presidential campaign trail to the top of political power in the world, the White House, and back out of President Trump’s inner circle. Along the way, he has made political enemies, and his public favorability ratings have fallen.

Amid the fallout between Trump and Musk this spring and summer, the president ordered a review of SpaceX’s contracts. Nothing happened because government officials found that most of the services SpaceX offers to NASA, the US Department of Defense, and other federal agencies are vital.

However, multiple sources have told Ars that federal officials are looking for alternatives to SpaceX and have indicated they will seek to buy launches, satellite Internet, and other services from emerging competitors if available.

Starship’s troubles also come at a critical time in space policy. As part of its budget request for fiscal year 2026, the White House sought to terminate the production of NASA’s Space Launch System rocket and spacecraft after the Artemis III mission. The White House has also expressed an interest in sending humans to Mars, viewing the Moon as a stepping stone to the red planet.

Although there are several options in play, the most viable hardware for both a lunar and Mars human exploration program is Starship. If it works. If it continues to have teething pains, though, that makes it easier for Congress to continue funding NASA’s expensive rocket and spacecraft, as it would prefer to do.

What about Artemis and the Moon?

Starship’s “lost year” also has serious implications for NASA’s Artemis Moon Program. As Ars reported this week, China is now likely to land on the Moon before NASA can return. Yes, the space agency has a nominal landing date in 2027 for the Artemis III mission, but no credible space industry officials believe that date is real. (It has already slipped multiple times from 2024). Theoretically, a landing in 2028 remains feasible, but a more rational over/under date for NASA is probably somewhere in the vicinity of 2030.

SpaceX is building the lunar lander for the Artemis III mission, a modified version of Starship. There is so much we don’t really know yet about this vehicle. For example, how many refuelings will it take to load a Starship with sufficient propellant to land on the Moon and take off? What will the vehicle’s controls look like, and will the landings be automated?

And here’s another one: How many people at SpaceX are actually working on the lunar version of Starship?

Publicly, Musk has said he doesn’t worry too much about China beating the United States back to the Moon. “I think the United States should be aiming for Mars, because we’ve already actually been to the Moon several times,” Musk said in an interview in late May. “Yeah, if China sort of equals that, I’m like, OK, sure, but that’s something that America did 56 years ago.”

Privately, Musk is highly critical of Artemis, saying NASA should focus on Mars. Certainly, that’s the long arc of history toward which SpaceX’s efforts are being bent. Although both the Moon and Mars versions of Starship require the vehicle to reach orbit and successfully refuel, there is a huge divergence in the technology and work required after that point.

It’s not at all clear that the Trump administration is seriously seeking to address this issue by providing SpaceX with carrots and sticks to move the lunar lander program forward. If Artemis is not a priority for Musk, how can it be for SpaceX?

This all creates a tremendous amount of uncertainty ahead of Sunday’s Starship launch. As Musk likes to say, “Excitement is guaranteed.”

Success would be better.

Photo of Eric Berger

Eric Berger is the senior space editor at Ars Technica, covering everything from astronomy to private space to NASA policy, and author of two books: Liftoff, about the rise of SpaceX; and Reentry, on the development of the Falcon 9 rocket and Dragon. A certified meteorologist, Eric lives in Houston.

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China’s Guowang megaconstellation is more than another version of Starlink


“This is a strategy to keep the US from intervening… that’s what their space architecture is designed to do.”

Spectators take photos as a Long March 8A rocket carrying a group of Guowang satellites blasts off from the Hainan commercial launch site on July 30, 2025, in Wenchang, China. Credit: Liu Guoxing/VCG via Getty Images

Spectators take photos as a Long March 8A rocket carrying a group of Guowang satellites blasts off from the Hainan commercial launch site on July 30, 2025, in Wenchang, China. Credit: Liu Guoxing/VCG via Getty Images

US defense officials have long worried that China’s Guowang satellite network might give the Chinese military access to the kind of ubiquitous connectivity US forces now enjoy with SpaceX’s Starlink network.

It turns out the Guowang constellation could offer a lot more than a homemade Chinese alternative to Starlink’s high-speed consumer-grade broadband service. China has disclosed little information about the Guowang network, but there’s mounting evidence that the satellites may provide Chinese military forces a tactical edge in any future armed conflict in the Western Pacific.

The megaconstellation is managed by a secretive company called China SatNet, which was established by the Chinese government in 2021. SatNet has released little information since its formation, and the group doesn’t have a website. Chinese officials have not detailed any of the satellites’ capabilities or signaled any intention to market the services to consumers.

Another Chinese satellite megaconstellation in the works, called Qianfan, appears to be a closer analog to SpaceX’s commercial Starlink service. Qianfan satellites are flat in shape, making them easier to pack onto the tops of rockets before launch. This is a design approach pioneered by SpaceX with Starlink. The backers of the Qianfan network began launching the first of up to 1,300 broadband satellites last year.

Unlike Starlink, the Guowang network consists of satellites manufactured by multiple companies, and they launch on several types of rockets. On its face, the architecture taking shape in low-Earth orbit appears to be more akin to SpaceX’s military-grade Starshield satellites and the Space Development Agency’s future tranches of data relay and missile-tracking satellites.

Guowang, or “national network,” may also bear similarities to something the US military calls MILNET. Proposed in the Trump administration’s budget request for next year, MILNET will be a partnership between the Space Force and the National Reconnaissance Office (NRO). One of the design alternatives under review at the Pentagon is to use SpaceX’s Starshield satellites to create a “hybrid mesh network” that the military can rely on for a wide range of applications.

Picking up the pace

In recent weeks, China’s pace of launching Guowang satellites has approached that of Starlink. China has launched five groups of Guowang satellites since July 27, while SpaceX has launched six Starlink missions using its Falcon 9 rockets over the same period.

A single Falcon 9 launch can haul up to 28 Starlink satellites into low-Earth orbit, while China’s rockets have launched between five and 10 Guowang satellites per flight to altitudes three to four times higher. China has now placed 72 Guowang satellites into orbit since launches began last December, a small fraction of the 12,992-satellite fleet China has outlined in filings with the International Telecommunication Union.

The constellation described in China’s ITU filings will include one group of Guowang satellites between 500 and 600 kilometers (311 and 373 miles), around the same altitude of Starlink. Another shell of Guowang satellites will fly roughly 1,145 kilometers (711 miles) above the Earth. So far, all of the Guowang satellites China has launched since last year appear to be heading for the higher shell.

This higher altitude limits the number of Guowang satellites China’s stable of launch vehicles can carry. On the other hand, fewer satellites are required for global coverage from the higher orbit.

A prototype Guowang satellite is seen prepared for encapsulation inside the nose cone of a Long March 12 rocket last year. This is one of the only views of a Guowang spacecraft China has publicly released. Credit: Hainan International Commercial Aerospace Launch Company Ltd.

SpaceX has already launched nearly 200 of its own Starshield satellites for the NRO to use for intelligence, surveillance, and reconnaissance missions. The next step, whether it’s the SDA constellation, MILNET, or something else, will seek to incorporate hundreds or thousands of low-Earth orbit satellites into real-time combat operations—things like tracking moving targets on the ground and in the air, targeting enemy vehicles, and relaying commands between allied forces. The Trump administration’s Golden Dome missile defense shield aims to extend real-time targeting to objects in the space domain.

In military jargon, the interconnected links to detect, track, target, and strike a target is called a kill chain or kill web. This is what US Space Force officials are pushing to develop with the Space Development Agency, MILNET, and other future space-based networks.

So where is the US military in building out this kill chain? The military has long had the ability to detect and track an adversary’s activities from space. Spy satellites have orbited the Earth since the dawn of the Space Age.

Much of the rest of the kill chain—like targeting and striking—remains forward work for the Defense Department. Many of the Pentagon’s existing capabilities are classified, but simply put, the multibillion-dollar satellite constellations the Space Force is building just for these purposes still haven’t made it to the launch pad. In some cases, they haven’t made it out of the lab.

Is space really the place?

The Space Development Agency is supposed to begin launching its first generation of more than 150 satellites later this year. These will put the Pentagon in a position to detect smaller, fainter ballistic and hypersonic missiles and provide targeting data for allied interceptors on the ground or at sea.

Space Force officials envision a network of satellites that can essentially control a terrestrial battlefield from orbit. The way future-minded commanders tell it, a fleet of thousands of satellites fitted with exquisite sensors and machine learning will first detect a moving target, whether it’s a land vehicle, aircraft, naval ship, or missile. Then, that spacecraft will transmit targeting data via a laser link to another satellite that can relay the information to a shooter on Earth.

US officials believe Guowang is a step toward integrating satellites into China’s own kill web. It might be easier for them to dismiss Guowang if it were simply a Chinese version of Starlink, but open-source information suggests it’s something more. Perhaps Guowang is more akin to megaconstellations being developed and deployed for the US Space Force and the National Reconnaissance Office.

If this is the case, China could have a head start on completing all the links for a celestial kill chain. The NRO’s Starshield satellites in space today are presumably focused on collecting intelligence. The Space Force’s megaconstellation of missile tracking, data relay, and command and control satellites is not yet in orbit.

Chinese media reports suggest the Guowang satellites could accommodate a range of instrumentation, including broadband communications payloads, laser communications terminals, synthetic aperture radars, and optical remote sensing payloads. This sounds a lot like a mix of SpaceX and the NRO’s Starshield fleet, the Space Development Agency’s future constellation, and the proposed MILNET program.

A Long March 5B rocket lifts off from the Wenchang Space Launch Site in China’s Hainan Province on August 13, 2025, with a group of Guowang satellites. (Photo by Luo Yunfei/China News Service/VCG via Getty Images.) Credit: Luo Yunfei/China News Service/VCG via Getty Images

In testimony before a Senate committee in June, the top general in the US Space Force said it is “worrisome” that China is moving in this direction. Gen. Chance Saltzman, the Chief of Space Operations, used China’s emergence as an argument for developing space weapons, euphemistically called “counter-space capabilities.”

“The space-enabled targeting that they’ve been able to achieve from space has increased the range and accuracy of their weapon systems to the point where getting anywhere close enough [to China] in the Western Pacific to be able to achieve military objectives is in jeopardy if we can’t deny, disrupt, degrade that… capability,” Saltzman said. “That’s the most pressing challenge, and that means the Space Force needs the space control counter-space capabilities in order to deny that kill web.”

The US military’s push to migrate many wartime responsibilities to space is not without controversy. The Trump administration wants to cancel purchases of new E-7 jets designed to serve as nerve centers in the sky, where Air Force operators receive signals about what’s happening in the air, on the ground, and in the water for hundreds of miles around. Instead, much of this responsibility would be transferred to satellites.

Some retired military officials, along with some lawmakers, argue against canceling the E-7. They say there’s too little confidence in when satellites will be ready to take over. If the Air Force goes ahead with the plan to cancel the E-7, the service intends to bridge the gap by extending the life of a fleet of Cold War-era E-3 Sentry airplanes, commonly known as AWACS (Airborne Warning and Control System).

But the high ground of space offers notable benefits. First, a proliferated network of satellites has global reach, and airplanes don’t. Second, satellites could do the job on their own, with some help from artificial intelligence and edge computing. This would remove humans from the line of fire. And finally, using a large number of satellites is inherently beneficial because it means an attack on one or several satellites won’t degrade US military capabilities.

In China, it takes a village

Brig. Gen. Anthony Mastalir, commander of US Space Forces in the Indo-Pacific region, told Ars last year that US officials are watching to see how China integrates satellite networks like Guowang into military exercises.

“What I find interesting is China continues to copy the US playbook,” Mastalir said. “So as as you look at the success that the United States has had with proliferated architectures, immediately now we see China building their own proliferated architecture, not just the transport layer and the comm layer, but the sensor layer as well. You look at their their pursuit of reusability in terms of increasing their launch capacity, which is currently probably one of their shortfalls. They have plans for a quicker launch tempo.”

A Long March 6A carries a group of Guowang satellites into orbit on July 27, 2025, from the Taiyuan Satellite Launch Center in north China’s Shanxi Province. China has used four different rocket configurations to place five groups of Guowang satellites into orbit in the last month. Credit: Wang Yapeng/Xinhua via Getty Images

China hasn’t recovered or reused an orbital-class booster yet, but several Chinese companies are working on it. SpaceX, meanwhile, continues to recycle its fleet of Falcon 9 boosters while simultaneously developing a massive super-heavy-lift rocket and churning out dozens of Starlink and Starshield satellites every week.

China doesn’t have its own version of SpaceX. In China, it’s taken numerous commercial and government-backed enterprises to reach a launch cadence that, so far this year, is a little less than half that of SpaceX. But the flurry of Guowang launches in the last few weeks shows that China’s satellite and rocket factories are picking up the pace.

Mastalir said China’s actions in the South China Sea, where it has taken claim of disputed islands near Taiwan and the Philippines, could extend farther from Chinese shores with the help of space-based military capabilities.

“Their specific goals are to be able to track and target US high-value assets at the time and place of their choosing,” he said. “That has started with an A2AD, an Anti-Access Area Denial strategy, which is extended to the first island chain and now the second island chain, and eventually all the way to the west coast of California.”

“The sensor capabilities that they’ll need are multi-orbital and diverse in terms of having sensors at GEO (geosynchronous orbit) and now increasingly massive megaconstellations at LEO (low-Earth orbit),” Mastalir said. “So we’re seeing all signs point to being able to target US aircraft carriers… high-value assets in the air like tankers, AWACs. This is a strategy to keep the US from intervening, and that’s what their space architecture is designed to do.”

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.

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