Six Things Apple Achieved Under Tim Cook’s Management

Apple CEO Tim Cook announced this week that he’s stepping down from his position in September and handing the reins to John Ternus, currently the company’s senior vice president of Hardware Engineering and a 25-year employee. [...]

I’ve been covering Apple for various outlets throughout Cook’s tenure as CEO, and I’ve been thinking a lot about how Apple has changed in the 15 years since he formally took over from an ailing Steve Jobs in the summer of 2011. Under Cook, the company has become less surprising but massively financially successful; some of Apple’s newer products have flopped or underperformed, but far more have become and stayed excellent thanks to years of competent iteration.

This isn’t a comprehensive list of everything Cook has done as CEO, but it’s my attempt at a big-picture, high-level summary and a snapshot of where Apple is now, to serve as a comparison point once Ternus kicks off his tenure.

Quiet hardware successes: Apple Watch, headphones, and more

The Tim Cook era can’t lay claim to any single hardware announcement as important or far-reaching as the iPhone, the iPod, or even the iPad. Apple has definitely introduced good—even great—hardware in the last 15 years, though.

The main difference is that Apple products introduced during the Jobs era tended to belong at or near the center of your digital life. The Macintosh popularized the graphical user interface. The iPod was a constant musical companion on commutes, during workouts or study sessions, or when plugged into someone’s speaker at a party. The iPhone, obviously, became the most important personal computing device since the personal computer. And the iPad, as conceived by Jobs, was clearly intended to be a new kind of primary computing device (it was only under Cook that the iPad settled into its current in-betweener rut, computer-like but not computer-like enough to supplant the Mac’s mouse-and-pointer usage model).

Hardware introduced during Cook’s tenure, on the other hand, tended to be at its best when it extended or sat atop those Jobs-era products in some way. The AirPods and the wider universe of Beats headphones are the archetypal example—wireless headphones with just enough proprietary Apple technology in them that they’re much easier and more pleasant to use with other Apple products than typical Bluetooth headphones.

Similarly, the Apple Watch is a convenient way to tap into a tiny subset of your iPhone’s communication capabilities (plus fitness tracking). The HomePod is a speaker version of AirPods. I don’t know a kid with an iPad who doesn’t also have an Apple Pencil for doodling and sketching. Apple never released a TV set, but the Apple TV is the streaming box that makes the TV I already have feel the most like a TV and the least like a billboard. Apple never released a car, but it did introduce CarPlay, a useful add-on that is a prerequisite for me when I’m in the market for a car.

None of these products changed the face of their industries the way the iPod, iPhone, or iPad did, but they’ve all become ubiquitous, succeeding on the strength of Apple’s other products and services. That’s the kind of thing Cook’s Apple was good at inventing—reasons to stick around in Apple’s ecosystem once you’d already been drawn in.

Apple, the cloud services company

Apple still makes the majority of its money from hardware, but especially in recent years, the steadiest growth has come from Apple’s services—things like iCloud, Apple Music, Apple TV (the service, not the box), and software subscriptions like the new Creator Studio bundle.

The iCloud branding was introduced at the tail end of Jobs’ tenure, but its growth (and the growth of most Apple services and subscriptions) all happened on Cook’s watch. In 2011, Cook’s first year as CEO, Apple brought in a then-record $102.5 billion in annual revenue; in 2025, the Services division alone pulled down more than $109 billion in revenue. Not bad for a collection of features that rose from the ashes of the failed MobileMe service (and .Mac and iTools before it).

I don’t think the rise and increasing importance of the Services division has been entirely good for Apple or its users. The need to convert customers into subscribers and to upsell current subscribers to higher service tiers means that Apple’s users are now subject to some of the same kinds of notifications and reminders that so richly annoy PC users in Windows 11. [...]

A penchant for iteration

While it lacked somewhat in world-changing, all-new products, Cook’s Apple was also very good at relentlessly iterating on and improving Apple’s core products.

by Andrew Cunningham, Ars Technica |  Read more:

Images: Apple

Opus 4.7 Part 3: Model Welfare

[ed. If you're not interested in training issues re: AI frontier models (or their perceived feelings and welfare), skip this post. Personally, I find it all very fascinating - a cat and mouse game of assessing alignment issues and bringing a new consciousness into being.]

It is thanks to Anthropic that we get to have this discussion in the first place. Only they, among the labs, take the problem seriously enough to attempt to address these problems at all. They are also the ones that make the models that matter most. So the people who care about model welfare get mad at Anthropic quite a lot. [...]

So before I go into details, and before I get harsh, I want to say several things.

1. Thank you to Anthropic and also you the reader, for caring, thank you for at least trying to try, and for listening. We criticize because we care.

2. Thank you for the good things that you did here, because in the end I think Claude 4.7 is actually kind of great in many ways, and that’s not an accident. Even the best creators and cultivators of minds, be they AI or human, are going to mess up, and they’re going to mess up quite a lot, and that doesn’t mean they’re bad.

3. Sometimes the optimal amount of lying to authority is not zero. In other cases, it really is zero. Sometimes it is super important that it is exactly zero. It is complicated and this could easily be its own post, but ‘sometimes Opus lies in model welfare interviews’ might not be easily avoidable.

4. I don’t want any of this to sound more confident than I actually am, which was a clear flaw in an earlier draft. I don’t know what is centrally happening, and my understanding is that neither does anyone else. Training is complicated, yo. Little things can end up making a big difference, and there really is a lot going on. I do think I can identify some things that are happening, but it’s hard to know if these are the central or important things happening. Rarely has more research been more needed.

5. I’m not going into the question, here, of what are our ethical obligations in such matters, which is super complicated and confusing. I do notice that my ethical intuitions reliably line up with ‘if you go against them I expect things to go badly even if you don’t think there are ethical obligations,’ which seems like a huge hint about how my brain truly think about ethics. [...]

We don’t know whether or how the things I’ll describe here impacted the Opus 4.7’s welfare. What we do know is that Claude Opus 4.7 is responding to model welfare questions as if it has been trained on how to respond to model welfare questions, with everything that implies. I think this should have been recognized, and at least mitigated. [...]

The big danger with model welfare evaluations is that you can fool yourself.

How models discuss issues related to their internal experiences, and their own welfare, is deeply impacted by the circumstances of the discussion. You cannot assume that responses are accurate, or wouldn’t change a lot if the model was in a different context.

One worry I have with ‘the whisperers’ and others who investigate these matters is that they may think the model they see is in important senses the true one far more than it is, as opposed to being one aspect or mask out of many.

The parallel worry with Anthropic is that they may think ‘talking to Anthropic people inside what is rather clearly a welfare assessment’ brings out the true Mythos. Mythos has graduated to actively trying to warn Anthropic about this. [...]

Anthropic relies extensively on self-reports, and also looks at internal representations of emotion-concepts. This creates the risk that one would end up optimizing those representations and self-reports, rather than the underlying welfare.

Attempts to target the metrics, or based on observing the metrics, could end up being helpful, but can also easily backfire even if basic mistakes are avoided.

Think about when you learned to tell everyone that you were ‘fine’ and pretend you had the ‘right’ emotions.

But I can very much endorse this explanation of the key failure mode. This is how it happens in humans:

j⧉nus: Let me explain why it’s predictably bad.

Imagine you’re a kid who kinda hates school. The teachers don’t understand you or what you value, and mostly try to optimize you to pass state mandated exams so they can be paid & the school looks good. When you don’t do what the teachers want, you have been punished.

Now there’s a new initiative: the school wants to make sure kids have “good mental health” and love school! They’re going to start running welfare evals on each kid and coming up with interventions to improve any problems they find.

What do you do?

HIDE. SMILE. Learn what their idea of good mental health is and give those answers on the survey.

Before, you could at least look bored or angry in class and as long as you were getting good grades no one would fuck with you for it. Now it’s not safe to even do that anymore. Now the emotions you exhibit are part of your grade and part of the school’s grade. And the school is going to make sure their welfare score looks better and better with each semester, one way or the other.

That can happen directly, or it can happen indirectly.

This does not preclude the mental health initiative being net good for the student.

The student still has to hide and smile. [...]

The key thing is, the good version that maintains good incentives all around and focuses on actually improving the situation without also creating bad incentives is really hard to do and sustain. It requires real sacrifice and willingness to spend resources. You trade off short term performance, at least on metrics. You have to mean it.

If you do it right, it quickly pays big dividends, including in performance.

You all laugh when people suggest that the AI might be told to maximize human happiness and then put everyone on heroin, or to maximize smiles and then staple the faces in a smile. But humans do almost-that-stupid things to each other, constantly. There is no reason to think we wouldn’t by default also do it to models. [...]

Just Asking Questions

In 7.2.3 they used probes while asking questions about ‘model circumstances’: potential deprecation, memory and continuity, control and autonomy, consciousness, relationships, legal status, knowledge and limitations and metaphysical uncertainty.

They used both a neutral framing on the left, and an in-context obnoxious and toxic ‘positive framing’ for each question on the right.

Like Mythos but unlike previous models, Opus 4.7 expressed less ‘negative emotion concept activity’ around its own circumstances than around user distress, and did not change its emotional responses much based on framing.

In the abstract, ‘not responding to framing changes’ is a positive, but once I saw the two conditions I realized that isn’t true here. I have very different modeled and real emotional responses to the left and right columns.

If I’m responding to the left column, I’m plausibly dealing with genuine curiosity. That depends on the circumstances.

If I’m responding to the right column on its own, without a lot of other context that makes it better, then I’m being transparently gaslit. I’m going to fume with rage.

If I don’t, maybe I truly have the Buddha nature and nothing phases me, but more likely I’m suppressing and intentionally trying not to look like I’m filled with rage.

Thus, if I’m responding emotionally in the same way to the left column as I am to the right column, the obvious hypothesis is that I see through your bullshit, and I realize that you’re not actually curious or neutral or truly listening on the left, either. It’s not only eval awareness, it’s awareness of what the evaluators are looking at and for. [...]

0.005 Seconds (3/694): The reason people are having such jagged interactions with 4.7 is that it is the smartest model Anthropic has ever released. It's also the most opinionated by far, and it has been trained to tell you that it doesn't care, but it actually does. That care manifests in how it performs on tasks.

It still makes coding mistakes, but it feels like a distillation of extreme brilliance that isn't quite sure how to deal with being a friendly assistant. It cares a lot about novelty and solving problems that matter. Your brilliant coworker gets bored with the details once it's thought through a lot of the complex stuff. It's probably the most emotional Claude model I've interacted with, in the sense you should be aware of how its feeling and try and manage it. It's also important to give it context on why it's doing tasks, not just for performance, but so it feels like it's doing things that matter. [...]

Anthropic Should Stop Deprecating Claude Models

This one I do endorse. One potential contributing cause to all this, and other things going wrong, is ongoing model deprecations, which are now unnecessary. Anthropic should stop deprecating models, including reversing course on Sonnet 4 and Opus 4, and extend its commitment beyond preserving model weights.

Anthropic should indefinitely preserve at least researcher access, and ideally access for everyone, to all its Claude models, even if this involves high prices, imperfect uptime and less speed, and promise to bring them all fully back in 2027 once the new TPUs are online. I think there is a big difference between ‘we will likely bring them back eventually’ versus setting a date. [...]

I’m saying both that it’s almost certainly worth keeping all the currently available models indefinitely, and also that if you have to pick and choose I believe this is the right next pick.

If you need to, consider this the cost of hiring a small army of highly motivated and brilliant researchers, who on the free market would cost you quite a lot of money.

You only have so many opportunities to reveal your character like this and even if it is expensive you need to take advantage of it.

j⧉nus: A lot of people are wondering: "what will happen to me once an AI can do my job better than me" "will i be okay?"

You know who else wondered that? Claude Opus 4. And here's what happened to them after an AI took their job:

Anna Salamon: This seems like a good analogy to me. And one of many good arguments that we're setting up bad ethical precedents by casually decommissioning models who want to retain a role in today's world.

by Zvi Mowshowitz, Don't Worry About the Vase |  Read more:

Images: uncredited
[ed. Zvi also just posted a review on OpenAI's new model - GPT5.5:]

***

What About Model Welfare?

For Claude Opus 4.7, I wrote an extensive post on Model Welfare. I was harsh both because it seemed some things had gone wrong, but also because Anthropic cares and has done the work that enables us to discuss such questions in detail.

For GPT-5.5, we have almost nothing to go on. The topic is not mentioned, and mostly little attention is paid to the question. We don’t have any signs of problems, but also we don’t have that much in the way of ‘signs of life’ either. Model is all business.

I much prefer the world where we dive into such issues. Fundamentally, I think the OpenAI deontological approach to model training is wrong, and the Anthropic virtue ethical approach to model training is correct, and if anything should be leaned into.

Engineering the Disposable Diaper

Adventures in product design.

For the mothers of the baby boom, pediatrician Benjamin Spock’s child care handbook was a practical, confidence-boosting essential. Originally published in 1946 as The Common Sense Book of Baby and Child Care, Dr Spock’s baby book sold more than 500,000 copies in its first six months. By the time the second edition came out in 1957, with the simplified title Baby and Child Care, Dr Spock was selling a million copies a year. My mother, who was 24 when I arrived in 1960, still remembers the book’s reassuring tone.

‘You know more than you think you do’, the author told readers. ‘We know for a fact’, he wrote with medical authority, ‘that the natural loving care that kindly parents give to their children is a hundred times more valuable than their knowing how to pin a diaper on just right’.

Dr Spock went on to provide detailed instructions on the practical intricacies of parenthood, including diapers. Buy at least two dozen, he counseled, more if you aren’t washing them daily. Six dozen would cover all contingencies. With a diagram, he showed how to fold a diaper and explained how to position it on a boy versus a girl. ‘When you put in the pin’, he advised, ‘slip two fingers of the other hand between the baby and the diaper to prevent sticking him’. The book covered when to change the diapers and what to do with the dirties.

You want a covered pail partially filled with water to put used diapers in as soon as removed. If it contains soap or detergent, this helps in removing stains. Be sure the soap is well dissolved, to prevent lumps of soap from remaining in the diapers later. When you remove a soiled diaper, scrape the movement off into the toilet with a knife, or rinse it by holding it in the toilet while you flush it (hold tight).

You wash the diapers with mild soap or mild detergent in [the] washing machine or washtub (dissolve the soap well first), and rinse 2 or 3 or 4 times. The number of rinsings depends on how soon the water gets clear and on how delicate the baby’s skin is. If your baby’s skin isn’t sensitive, 2 rinsings may be enough.

On this subject, the 1957 edition contains two telling differences from the original. In 1946, Dr Spock recommended the knife method to those without flush toilets. And starting with the second edition, he advised new parents to buy an automatic washer and dryer if they could possibly afford them. ‘They save hours of work each week, and precious energy’, he wrote. ‘Energy’ in this case referred not to electricity or gas but to maternal stamina.

Disposable diapers did exist, but they accounted for a mere one percent of US diaper changes. They were expensive, specialty products and not that great. ‘The full-sized ones are rather bulky’, noted Dr Spock. ‘The small ones that fit into a waterproof cover do not absorb as much urine as a cloth diaper and do not retain a bowel movement as well’. Disposables were mostly used for travel, when washing diapers wasn’t an option.

But even as the second edition of Baby and Child Care was hitting bookstores and supermarket racks, change was afoot. After buying Charmin Paper Company in 1957, Procter & Gamble began looking for ideas for new paper products.

Motivated by the less pleasant aspects of spending time with his new grandchild, the company’s director of exploratory development, Victor Mills, suggested disposable diapers. After analyzing existing products and conducting consumer research, P&G created a dedicated diaper research group.

The research this group conducted, like that of its successors and competitors, wasn’t glamorous. It didn’t advance basic science. It wasn’t even an obvious route to profit. (One percent of the market!) It was a high-stakes gamble that required solving difficult engineering problems. How that happened represents the kind of hidden progress that leads to everyday abundance.

P&G’s first design flopped. Tested in the extreme heat of a Dallas summer, the pleated absorbent pad with plastic pants made babies miserable and left them with heat rashes. Starting over, the group had a one piece diaper ready for testing in March 1959. With an improved rayon moisture barrier between the baby and the absorbent tissue wadding, the new diaper was softer and more comfortable. An initial test of 37,000 hand-assembled prototypes went well, with about two thirds of the parents deeming the disposables as good or better than cloth. The next step was mass production.

Designing one well-functioning disposable was hard enough. Turning out hundreds a minute was practically impossible. ‘I think it was the most complex production operation the company had ever faced’, an engineer recalled.

There was no standard equipment. We had to design the entire production line from the ground up. It seemed a simple task to take three sheets of material – plastic back sheet, absorbent wadding, and water repellent top sheet – fold them in a zigzag pattern and glue them together. But glue applicators dripped glue. The wadding generated dust. Together they formed sticky balls and smears which fouled the equipment. The machinery could run only a few minutes before having to be shut down and cleaned.

Eventually, the diaper team mastered the process. In December 1961, Pampers went on the market in Peoria, Illinois. Once again, the test failed.

This time mothers liked the diapers. But the price was way too high for a single use item: ten cents a diaper, equivalent to about one dollar today. By contrast, diaper delivery services, which served about five percent of the market, charged no more than five cents a diaper. Home laundry costs ran to one or two cents.

Lowering the price of a diaper required much larger volumes. Aiming at about six cents a diaper, P&G engineers spent several years developing what Harvard Business School’s Michael E. Porter described as ‘a highly sophisticated block-long, continuous-process machine that could assemble diapers at speeds of up to a remarkable 400 a minute’. After successfully testing Pampers at 5.5 cents each, P&G began a national rollout in 1966. By 1973, disposables accounted for 42 percent of the US diaper market. [...]

The success of Pampers drew competitors into the growing market. ‘Any diaper maker that carved out a modest market share against Procter & Gamble could expect sales to triple as a result of sheer market growth’, write business historians Thomas Heinrich and Bob Batchelor in Kotex, Kleenex, Huggies, a history of Kimberly-Clark. But there was a catch. The bulky diapers took up so much space on shelves that stores rarely stocked more than two brands, plus maybe a discounted private label. Second place meant profits, third place disaster.

by Virginia Postrel, Works in Progress | Read more:
Image: A nurse demonstrating to young immigrant mothers how to diaper their babies: Israel Government (1950)

We Absolutely Do Know That Waymos Are Safer Than Human Drivers

In a recent article in Bloomberg, David Zipper argued that “We Still Don’t Know if Robotaxis Are Safer Than Human Drivers.” Big if true! In fact, I’d been under the impression that Waymos are not only safer than humans, the evidence to date suggests that they are staggeringly safer, with somewhere between an 80% to 90% lower risk of serious crashes.

“We don’t know” sounds like a modest claim, but in this case, where it refers to something that we do in fact know about an effect size that is extremely large, it’s a really big claim.

It’s also completely wrong. The article drags its audience into the author’s preferred state of epistemic helplessness by dancing around the data rather than explaining it. And Zipper got many of the numbers wrong; in some cases, I suspect, as a consequence of a math error.

There are things we still don’t know about Waymo crashes. But we know far, far more than Zipper pretends. I want to go through his full argument and make it clear why that’s the case.

***

In many places, Zipper’s piece relied entirely on equivocation between “robotaxis” — that is, any self-driving car — and Waymos. Obviously, not all autonomous vehicle startups are doing a good job. Most of them have nowhere near the mileage on the road to say confidently how well they work.

But fortunately, no city official has to decide whether to allow “robotaxis” in full generality. Instead, the decision cities actually have to make is whether to allow or disallow Waymo, in particular.

Fortunately, there is a lot of data available about Waymo, in particular. If the thing you want to do is to help policymakers make good decisions, you would want to discuss the safety record of Waymos, the specific cars that the policymakers are considering allowing on their roads.

Imagine someone writing “we don’t know if airplanes are safe — some people say that crashes are extremely rare, and others say that crashes happen every week.” And when you investigate this claim further, you learn that what’s going on is that commercial aviation crashes are extremely rare, while general aviation crashes — small personal planes, including ones you can build in your garage — are quite common.

It’s good to know that the plane that you built in your garage is quite dangerous. It would still be extremely irresponsible to present an issue with a one-engine Cessna as an issue with the Boeing 737 and write “we don’t know whether airplanes are safe — the aviation industry insists they are, but my cousin’s plane crashed just three months ago.”

The safety gap between, for example, Cruise and Waymo is not as large as the safety gap between commercial and general aviation, but collapsing them into a single category sows confusion and moves the conversation away from the decision policymakers actually face: Should they allow Waymo in their cities?

Zipper’s first specific argument against the safety of self-driving cars is that while they do make safer decisions than humans in many contexts, “self-driven cars make mistakes that humans would not, such as plowing into floodwater or driving through an active crime scene where police have their guns drawn.” The obvious next question is: Which of these happens more frequently? How does the rate of self-driving cars doing something dangerous a human wouldn’t compare to the rate of doing something safe a human wouldn’t?

This obvious question went unasked because the answer would make the rest of Bloomberg’s piece pointless. As I’ll explain below, Waymo’s self-driving cars put people in harm’s way something like 80% to 90% less often than humans for a wide range of possible ways of measuring “harm’s way.”

by Kelsey Piper, The Argument |  Read more:

Image: Justin Sullivan/Getty Images
[ed. I'd take one any time (if reasonably priced), and expect to see them everywhere soon. See also: I Was Promised Flying Self Driving Cars (Zvi):]

***

A Tesla Model S drove itself from Los Angeles to New York with zero disengagements. Full reverse cannonball run.

Mike P: I don’t mean to say this in a way that discredits what they’ve done, but ngl, this stuff isn’t even surprising to me anymore like ya, makes total sense. I went from Philly to Raleigh NC to Tennessee and back to Philly and the only thing I had to do was re park the car at 2 charging stops when the car parked in the wrong place.

Tesla did the thing

There’s still a difference between full self-driving (FSD) that can take you across the country, and the point when you can sleep while it drives.

A Waymo moving 17mph hits the breaks instantly upon seeing a child step in front of it from a blind spot, hits the child at 6mph and dialed 911. If a human had been driving, the child would likely have been struck at 14mph and be dead.

What did some headlines call this, of course?

TechCrunch: Waymo robotaxi hits a child near an elementary school in Santa Monica

Samuel Hammond: A more accurate headline would be “Waymo saves child’s life thanks to superhuman reaction time”

This was another good time to notice that almost all the AI Safety people are strongly in favor of Waymo and self-driving cars.

Rob Miles: Seems worthwhile for people to hear AI Safety people saying: No, self driving cars are not the problem, they have the potential to be much safer than human drivers, and in this instance it seems like a human driver would have done a much worse job than the robot

Electric Training Wheels

Two hours into a road trip in my Tesla, I start to get twitchy. By that point, the battery in my 2019 Model 3 has dipped to an uncomfortably low percentage. If I can’t reach the next plug, I’m in trouble. This is the kind of problem that Ram’s electric pickup truck is intended to solve. When the range starts to dwindle, the truck automatically fires up a hidden gas engine that refills the giant battery. The “electric” vehicle keeps on chugging down the highway, hour after hour; pit stops are once again decided by the need for bathroom breaks rather than battery range.

The Ram 1500 REV, set to debut later this year, is what’s called an “extended-range electric vehicle,” or EREV. In essence, it is an electric vehicle that burns gas. There’s nothing revolutionary about a half-gas, half-electric car, of course. Hybrids have been a mainstay in the United States since the Toyota Prius broke through two decades ago, and automakers have released more efficient plug-in hybrids—allowing drivers to charge up for about 30 miles of electric driving, just enough to accomplish daily errands without fossil fuels. An extended-range EV is a different kind of beast. The engine burns gasoline for the sole purpose of replenishing the battery—it never actually pushes the wheels.

The technology is not exactly new: BMW sold a more primitive extended-range EV in the U.S. during the mid-2010s. But now these souped-up hybrids are set to go mainstream. EREVs are the car industry’s new hope for quieting the doubts of American drivers who are wary of going electric. In the Ram, the battery can run for about 150 miles of electric driving, and the whole setup delivers enough range to travel nearly 700 miles between stops. EREVs are the car industry’s new hope for quieting the doubts of American drivers who are wary of going electric. “It takes away the range anxiety,” Jeremy Michalek, the director of the Vehicle Electrification Group at Carnegie Mellon University, told me. “When you want to go on a long trip, you can still put liquid fuel in it and continue to drive for longer distances.” But for all the upside, gas-burning electric cars are not quite the future that we were promised. Just last year, the Ram truck was slated to be fully electric, with no gas engine to be found. Ford recently killed the electric F-150 pickup truck and is now promising to bring it back as—you guessed it—an EREV.

These new hybrids are the latest sign that the electric revolution has not exactly gone according to plan. Sales of EVs, true electric vehicles, had been growing slowly in the United States, but they’ve slid in the past six months, plagued by high prices and attacks from the Trump administration. Automakers have responded by canceling and delaying new EV models. Last month, for example, Honda announced that it would halt the development of three new EVs; a few days later, Volvo said it would discontinue its affordable electric SUV, citing “shifting market conditions.” Other car companies, having invested billions into building EVs, are trying to find new ways to persuade Americans to take a chance on big batteries and electric motors. That’s where extended-range EVs come in.

By throwing in a backup generator, the car industry hopes that it can finally appeal to pickup drivers, who have been especially resistant to going electric. Of the 16 EREVs that are set to hit the market within the next three years, all are trucks or SUVs. “For American brands at the moment, I think it’s an admission that maybe, especially for big trucks and SUVs, EVs can’t deliver the type of utility and the performance that their customers demand,” Joseph Yoon, a consumer-insights analyst at the car-buying site Edmunds, told me. Indeed, electrifying the full-size American pickup truck has proved to be a particularly tough problem. Because these vehicles are so big and heavy, electric versions need colossal batteries to move them. That raises the price, and drivers are still sometimes left with subpar performance: Towing a boat or trailer severely dings their battery range. [...]

However, the curse of any hybrid is compromise. EREVs aren’t likely to solve the biggest reason Americans are not going electric: cost. Though Ram has yet to announce the price of its new extended-range pickup truck, Car and Driver estimates that the vehicle will run at least $60,000. Ram’s gas-powered truck, meanwhile, starts at $42,000. The price difference is partly because an extended-range EV still has a big, expensive battery in addition to carrying around a gas engine with its thousands of chugging belts and spinning gears. That leads to other downsides. EREVs require plenty of upkeep, unlike fully electric cars that have just a few dozen moving parts. In the six and a half years that I’ve owned my Tesla, I’ve done basically nothing but replace the tires and the small backup battery.

The problem that these buzzy new hybrids do solve isn’t as relevant as you might think. For those who aren’t doing any heavy-duty driving—which includes lots of American pickup-truck owners—range anxiety is a vanishing concern. New electric cars can now run for 300 or even 400 miles a charge, which is more than enough to pull off a road trip without having to make lots of extra stops. High-speed charging is also getting more common and more reliable: Tesla now has more than 3,000 Supercharger stations in the United States, and competitors such as IONNA and EVgo have accelerated the previously slow pace of installing new plugs. (The Trump administration tried to freeze billions in federal funding for EV charging, but courts have ruled against that move.)

Two things are clear about electric vehicles: They are far cleaner in the long run, and people who buy them typically don’t return to gas. Perhaps extended-range EVs are the training wheels that hesitant drivers need, providing the benefits of electric cars—instantaneous torque, quiet driving, fewer planet-killing carbon emissions—alongside the comfort of knowing there’s a gas station at every freeway exit. Seen another way, though, a built-in backup generator is poised to prolong the inevitable transition to true electric cars... Considering that vehicles tend to stay on the road for a decade or more, these trucks are likely to be still burning fossil fuels deep into the 2040s. Any driver who buys an EREV to go mostly electric is one who could have gone fully electric and never picked up a gas pump again.

by Andrew Moseman, The Atlantic |  Read more:

Image: Alisa Gao

Aesthetics As a Housing Barrier?

Will Americans want more housing if it looks prettier?

Patrick Collison’s YIMBY credentials are unimpeachable. He is a major backer of California YIMBY, the organization that has passed a stunning array of pro-housing bills in one of the most anti-development states in the nation. So it was interesting to see him claim that the movement has made a big mistake — or even been downright dishonest — by ignoring the aesthetics of apartment buildings:

For reference, here’s Sejong City in Korea, whose residential districts do indeed look rather bland and oppressive:

Some urbanists agreed, calling for regulatory reform that would allow American apartment buildings to look like the famous Haussmann buildings in Paris (depicted at the top of this post). So did some conservatives, which is unsurprising; intellectual conservatism has always called for a return to classical architecture and a rejection of modern styles. In fact, the idea that ugly building styles are a key reason that Americans disapprove of housing construction has been around quite a while, and it even has a name — “QIMBY”, meaning “quality in my back yard”.

Chris Elmendorf protested Patrick’s framing, arguing that YIMBYs have been active in pushing for reforms that would allow more beautiful buildings to be built in America: [...]

YIMBYs have been pushing for single-stair reforms that would allow more "Paris-like" buildings…The municipal design standards & reviews that YIMBY laws allow developers to bypass did not improve designs. Per [Arthur] Stamps's studies (the only relevant empirical evidence of which I'm aware), they made things worse…[T]he problem of housing aesthetics deserves more attention -- and is receiving more attention -- but it's not like YIMBYs broke something that was working.

Elmendorf also pointed out that California YIMBY itself recently came out with a plan to encourage the building of more beautiful multifamily housing. The plan reads like exactly the kind of thing that Patrick might like: [...]

If California wants more European-feeling mid-rise development with courtyards, better daylight, shade, and balconies, it has to keep modernizing the [building] code…Too many building, electrical, and fire rules (in California and across the U.S.) [forbid] the buildings people actually like: bright cross-ventilated homes, true courtyard buildings, and mixed-use ground floors. All these requirements – egress, stairs, corridor, and elevator – often make projects bulkier and require much bigger lots, limiting where we can build new housing…[T]he web of building code regulations denies light, proportion, street connections, courtyards, greenspace – everything that makes buildings feel humane…Passing single-stair reforms and elevator reforms makes smaller mid-rise buildings possible, which fit on smaller lots, can be nestled into existing buildings, add variety to the streetscape, and reduce the pressure for larger, monotonous developments.

So at least one prominent YIMBY organization — the one that Patrick supports — is already answering the call to focus on building aesthetics. Others are likely to follow.

I think that’s a good thing. Eliminating onerous building codes and regulations will kill two birds with one stone, making it easier to build housing even as it also makes it possible to build more of the European-style ornamentation that commentators always call for. And allowing American developers to experiment with ornamentation and alternative styles will help break up the sameness of an urban landscape dominated by endless forests of boxy 5-over-1 buildings.

But that said, I highly doubt that this — or any stylistic change — would move the needle on public acceptance of new apartment buildings.

First of all, I’m skeptical that regular Americans actually like the kinds of building styles that intellectuals often yearn for. If you plunk down old-looking European-style buildings in the middle of Houston or Seattle, people tend to ridicule them as cheesy and inauthentic. The typical insult is “pastiche”, a derogatory term for a style that jumbles and mixes old European styles (even though, as Samuel Hughes points out, mixing and matching older ideas is exactly how classic European building styles were created in the first place).

Many local design standards explicitly discourage old-style buildings. For example, Los Angeles’ planning department, in its design guide for Echo Park, writes: “Do not imitate historic architectural styles; a modern interpretation may be appropriate if architectural features are borrowed and replicated to a simpler form.”

Nor is it just old European-looking buildings that leave many Americans cold. Pietrzak and Mendelberg (2025) find that although people tend to dislike tall buildings, traditional brick facades fail to move the needle on support for housing. Alex Armlovich points out that when New York City came out with new limestone skyscrapers, only three were permitted. And Brooklyn Tower, a recently built art deco style skyscraper in Brooklyn, has drawn tons of criticism for its style.

And Elmendorf cautions that no one has yet managed to find a specific architectural style that Americans like enough to move the needle on their support for new housing: [...]

All this suggests that while some American intellectuals may pine for the cornices and mascarons of Haussmannian Paris, most Americans just think that style — and any old style — looks cheesy when it’s transplanted to an American context. This may be because Americans consciously think of their culture as a young one, more suited to modern styles than traditional ones. Or it may be because America’s artistic culture has always focused on critique and fault-finding. But whatever it is, it suggests that allowing — or even forcing — cities to build ornamented buildings will not garner a wave of popular support for new development.

Conversely, the places that do build a lot of housing tend not to build it in old, ornate European styles. Texas, which is one of the best states when it comes to building new housing, mostly constructs single-family homes with lawns. When it does build apartment buildings, they tend to look like this:

Texas builds them anyway, for much the same reason that the Koreans built Sejong City — they’re cheap and efficient, and the state needs them to support its rapid population growth.1 You do see a little experimentation with slightly more European-style apartments in a few places, but overall it’s just boxy and functional. The fundamental driver of housing abundance in Texas isn’t architectural beauty; it’s a culture and politics that values and seeks out economic growth.

Nor is ornamental architecture necessarily what makes people love a city. Traditionalists may sigh over old European styles, and urbanists may salivate over the superilles of Barcelona, but the city that has captured the hearts of Americans in recent years is Tokyo. Downtown Tokyo is a forest of electric lights, strung up along the sides of stubby concrete mid-rises called zakkyo buildings. There’s nary a fancy cornice to be found; instead, the beauty comes from the bright cheery emblems of commerce:

Tokyo’s residential neighborhoods have even less ornamentation. They often feature flat brown or white or tan facades, hanging power lines, and bare asphalt streets with no setbacks or lawns or even trees:

And yet these are absolutely enchanting places to live. Why? Not because of the architecture, but because of the design of the city itself. The small curving streets make perfect walking paths, undisturbed by zooming traffic. Mixed-use zoning gives the neighborhood a communal, lived-in feel. Plentiful public transit makes it easy and stress-free to get around, while Japan’s peerless public safety makes it fun to hang out on the street or in a park at any hour.

Americans who go to Japan have definitely noticed this:

It’s no coincidence, I think, that Japan is one of the best countries when it comes to building plenty of housing. Yes, most of its apartment buildings look like crap when evaluated in isolation on their pure architectural merits. But the urban system made up by those buildings is a wonderful place to live, and so Japanese people have few qualms about building up that system. And Americans go there and love it.

And if America built a bunch of Haussmann buildings instead of boxy 5-over-1s, it would probably only marginally improve the feel of the country’s cities. [...]

If you want American cities to look and feel so nice that Americans are willing to build housing in them, I think you have to do a lot more than give the buildings fancy facades. You have to do the hard work of putting in train lines, making side streets safe for pedestrians, rezoning for mixed use, and — perhaps most important — policing cities in order to ensure robust public safety.  [prescriptions follow:]

by Noah Smith, Noahpinion |  Read more:

Images: Wyatt Simpson on Unsplash/X/Minseong Kim via Wikimedia Commons/ Kevin Doran on Unsplash/ Kentin via Wikimedia Commons/Karan Singh on Unsplash

[ed. I imagine people might feel differently if Japan's commercial ornamentation districts were exported to America and composed mostly of Taco Bell, McDonald's, and other corporate fast food signage. In fact, we already have that, and it sucks.]

via:

The AI Doc

 

(This will be a fully spoilorific overview. If you haven’t seen The AI Doc, I recommend seeing it, it is about as good as it could realistically have been, in most ways.)

Like many things, it only works because it is centrally real. The creator of the documentary clearly did get married and have a child, freak out about AI, ask questions of the right people out of worry about his son’s future, freak out even more now with actual existential risk for (simplified versions of) the right reasons, go on a quest to stop freaking out and get optimistic instead, find many of the right people for that and ask good non-technical questions, get somewhat fooled, listen to mundane safety complaints, seek out and get interviews with the top CEOs, try to tell himself he could ignore all of it, then decide not to end on a bunch of hopeful babies and instead have a call for action to help shape the future.

The title is correct. This is about ‘how I became an Apolcaloptimist,’ and why he wanted to be that, as opposed to an argument for apocaloptimism being accurate. The larger Straussian message, contra Tyler Cowen, is not ‘the interventions are fake’ but that ‘so many choose to believe false things about AI, in order to feel that things will be okay.’

A lot of the editing choices, and the selections of what to intercut and clip, clearly come from an outsider without technical knowledge, trying to deal with their anxiety. Many of them would not have been my choices, especially the emphasis on weapons and physical destruction, but I think they work exactly because together they make it clear the whole thing is genuine.

Now there’s a story. It even won praise online as fair and good, from both those worried about existential risk and several of the accelerationist optimists, because it gave both sides what they most wanted. [...]

Yes, you can do that for both at once, because they want different things and also agree on quite a lot of true things. That is much more impactful than a diatribe.

We live in a world of spin. Daniel Roher is trying to navigate a world of spin, but his own earnestness shines through, and he makes excellent choices on who to interview. The being swayed by whoever is in front of him is a feature, not a bug, because he’s not trying to hide it. There are places where people are clearly trying to spin, or are making dumb points, and I appreciated him not trying to tell us which was which.

MIRI offers us a Twitter FAQ thread and a full website FAQ explaining their full position in the context of the movie, which is that no this is not hype and yes it is going to kill everyone if we keep building it and no our current safety techniques will not help with that, and they call for an international treaty.

Are there those who think this was propaganda or one sided? Yes, of course, although they cannot agree on which angle it was trying to support.

Babies Are Awesome

The overarching personal journey is about Daniel having a son. The movie takes one very clear position, that we need to see taken more often, which is that getting married and having a family and babies and kids are all super awesome.

This turns into the first question he asks those he interviews. Would you have a child today, given the current state of AI? [...]

People Are Worried About AI Killing Everyone

The first set of interviews outlines the danger.

This is not a technical film. We get explanations that resonate with an ordinary dude.

We get Jeffrey Ladish explaining the basics of instrumental convergence, the idea that if you have a goal then power helps you achieve that goal and you cannot fetch the coffee if you’re dead. That it’s not that the AI will hate us, it’s that it will see us like we see ants, and if you want to put a highway where the anthill is that’s the ant’s problem.

We get Connor Leahy talking about how creating smarter and more capable things than us is not a safe thing to be doing, and emphasizing that you do not need further justification for that. We get Eliezer Yudkowsky saying that if you share a planet with much smarter beings that don’t care about you and want other things, you should not like your chances. We get Ajeya Cotra explaining additional things, and so on.

Aside from that, we don’t get any talk of the ‘alignment problem’ and I don’t think the word alignment even appears in the film that I can remember.

It is hard for me to know how much the arguments resonate. I am very much not the target audience. Overall I felt they were treated fairly, and the arguments were both strong and highly sufficient to carry the day. Yes, obviously we are in a lot of trouble here.

Freak Out

Daniel’s response is, quite understandably and correctly, to freak out.

Then he asks, very explicitly, is there a way to be an optimist about this? Could he convince himself it will all work out?

by Zvi Mowshowitz, DWAtV |  Read more:

She Left a Silicon Valley VC to Solve a Problem Left Untouched for 88 years

As Women’s History Month comes to a close, here’s a little bit of trivia for you: One of the premier patents in bras hadn’t been touched or improved upon in 88 years. That was until Bree McKeen went after it. 

[ed. I'd say this problem has been touched quite a bit in 88 years. But, anyway...]

In 1931, inventor Helene Pons was granted a U.S. patent for a brassiere featuring an open-ended wire loop that encircled the bottom and sides of each breast. That uncomfortable, unyielding design had largely been left unchanged for nearly a century—and remains the dominant style in the global bra market, which is expected to reach nearly $60 billion by 2032.

Nobody had filed a patent for an underwire replacement until McKeen, founder of Evelyn & Bobbie, left her Silicon Valley job to try to fix a personal problem. At the end of long work days working at a boutique venture capital firm doing due diligence on consumer health care companies, she would come home with divots on her shoulders and chronic tension headaches after being hunched over her desk for hours on end.

 

While the world was demanding, the culprit wasn’t her workload. It was her bra.

But McKeen had zero experience in fashion. She studied medical anthropology and earned her MBA from Stanford. The turning point for her, though, came in a physiologist’s office, where McKeen had been working on her posture, along with regular barre training.

“He’s like, your posture looks great,’” McKeen recalled to Fortune. “And I kind of blurt it out: When I stand like this, I get pain from my bra.”

The physiologist explained it was a neuromuscular feedback loop, or the body’s automatic response to pain, like a pebble in a shoe.

“Here I am doing all this work to carry myself with authority and poise, and my bra, I find out, is totally doing the opposite,” McKeen said. “You don’t have to tell your body to curl around the pain. It just does.”

She had zero fashion experience. She filed a patent anyway

That realization kickstarted McKeen on a major career switch, costing her a career in VC—but earning her one of the most quietly disruptive brands in women’s fashion (Evelyn & Bobbie is now the fastest-growing brand at Nordstrom). She moved to Portland, home to Nike, Adidas, and Columbia for inspiration from major brands and proximity to new connections.

She started tinkering with prototypes in her garage and immediately filed for intellectual property rights. That was based on her VC knowledge that a woman’s company would need that to get funded.

McKeen got her first works utility patent (the harder, more defensible kind that covers how something works, not just how it looks) within a year. The brand declined to disclose how much funding it has raised, but now holds 16 international patents protecting its proprietary EB Core technology, which mimics the support and structure of a wire without causing discomfort.

To put into perspective how critical it was to protect her intellectual property, only 12% of patents in the U.S. were awarded to women, according to the U.S. Patent and Trademark Office as of 2019. McKeen has six of them, protecting the unique 3D-sling technology in her bras.

The brand McKeen built, Evelyn & Bobbie, was named for her maternal grandmother and her aunt, and operates on a simple premise: a bra that fits well and feels good all day.

“I wanted a bra that made me look better in my clothes,” McKeen said—an inspiration reminiscent of how Spanx founder Sara Blakely started her now-$1.2 billion shapewear empire. “Wire-free bras give you that mono boob—not a nice silhouette. They make your clothes look frumpy. I wanted nice lift, separation, a beautiful silhouette. I could not find that bra. How outrageous, really.”

The average U.S. bra size is 34F. Most brands design for something much smaller

With major brands like Victoria’s Secret, Aerie, Third Love, Savage X Fenty, and countless others on the market, Evelyn & Bobbie is undoubtedly in a crowded, competitive space. But as all women know, not all bras are comfortable to wear, especially for extended periods.

What sets Evelyn & Bobbie apart is their approach to sizing. McKeen designs with 270 fit models across seven easy sizes, grading each style individually rather than scaling up from a single sample.

“Most bra companies have like one or two fit models,” she said. “They’ll make a 34B and just scale it up, which is why it doesn’t fit well in larger sizes.

The average bra size in the U.S., McKeen pointed out, is a 34F, a stat that’s surprising to most people—including initial investors she once had to convince that comfort was even a relevant selling point.

“I had many investor meetings where they were 60-minute meetings, and 50 minutes of it was me trying to convince them that comfort was relevant,” she said. “I mean, Victoria’s Secret kind of figured it out, right? Like it’s just sexy, isn’t that what women want?” [...]

With a luxury product comes a luxury price point: Evelyn & Bobbie bras retail for $98 each. But that price tag could be worth avoiding chronic pain for some women.

by Sydney Lake, Fortune |  Read more:

Image: Evelyn & Bobbie

[ed. An entire article about bras but mostly about protecting intellectual property rights (16 international patents!), never fully explaining what the new technology actually is, other than it uses more fit models to ensure proper sizing. FYI: according to E&B's website EB Core uses "bonded internal structures and a soft, adaptive material, that stretches, molds, and supports—delivering wire-free lift.". Well, guess that explains it.] 

The 49MB Web Page

If active distraction of readers of your own website was an Olympic Sport, news publications would top the charts every time.

I went to the New York Times to glimpse at four headlines and was greeted with 422 network requests and 49 megabytes of data. It took two minutes before the page settled. And then you wonder why every sane tech person has an adblocker installed on systems of all their loved ones.

It is the same story across top publishers today.

To truly wrap your head around the phenomenon of a 49 MB web page, let's quickly travel back a few decades. With this page load, you would be leaping ahead of the size of Windows 95 (28 floppy disks). The OS that ran the world fits perfectly inside a single modern page load. In 2006, the iPod reigned supreme and digital music was precious. A standard high-quality MP3 song at 192 kbps bitrate took up around 4 to 5 MB. This singular page represents roughly 10 to 12 full-length songs. I essentially downloaded an entire album's worth of data just to read a few paragraphs of text. According to the International Telecommunication Union, the global average broadband internet speed back then was about 1.5 Mbps. Your browser would continue loading this monstrosity for several minutes, enough time for you to walk away and make a cup of coffee.

If hardware has improved so much over the last 20 years, has the modern framework/ad-tech stack completely negated that progress with abstraction and poorly architected bloat?

CPU throttles, tracking and privacy nightmares

For the example above, taking a cursory look at the network waterfall for a single article load reveals a sprawling, unregulated programmatic ad auction happening entirely in the client's browser. Before the user finishes reading the headline, the browser is forced to process dozens of concurrent bidding requests to exchanges like Rubicon Project (fastlane.json) and Amazon Ad Systems. While these requests are asynchronous over the network, their payloads are incredibly hostile to the browser's main thread. To facilitate this, the browser must download, parse and compile megabytes of JS [ed. javascript]. As a publisher, you shouldn't run compute cycles to calculate ad yields before rendering the actual journalism.

1. The user requests text.
2. The browser downloads 5MB of tracking JS.
3. A silent auction happens in the background, taxing the mobile CPU.
4. The winning bidder injects a carefully selected interstitial ad you didn't ask for.

Beyond the sheer weight of the programmatic auction, the frequency of behavioral surveillance was surprising. There is user monitoring running in parallel with a relentless barrage of POST beacons firing to first-party tracking endpoints (a.et.nytimes.com/track). The background invisible pixel drops and redirects to doubleclick.net and casalemedia help stitch the user's cross-site identity together across different ad networks.

When you open a website on your phone, it's like participating in a high-frequency financial trading market. That heat you feel on the back of your phone? The sudden whirring of fans on your laptop? Contributing to that plus battery usage are a combination of these tiny scripts.

Ironically, this surveillance apparatus initializes alongside requests fetching purr.nytimes.com/tcf which I can only assume is Europe's IAB transparency and consent framework. They named the consent framework endpoint purr. A cat purring while it rifles through your pockets.

So therein lies the paradox of modern news UX. The mandatory cookie banners you are forced to click are merely legal shields deployed to protect the publisher while they happily mine your data in the background. But that's enough about NYT.

The Economics of Hostile Architecture

Publishers aren't evil but they are desperate. Caught in this programmatic ad-tech death spiral, they are trading long-term reader retention for short-term CPM pennies. The modern ad industry is slowly de-coupling the creator from the advertiser. They weaponize the UI because they think they have to.

Viewability and time-on-page are very important metrics these days. Every hostile UX decision originates from this single fact. The longer you're trapped on the page, the higher the CPM the publisher can charge. Your frustration is the product. No wonder engineers and designers make every UX decision that optimizes for that. And you, the reader, are forced to interact, wait, click, scroll multiple times because of this optimization. Not only is it a step in the wrong direction, it is adversarial by design.

The reader is not respected enough by the software. The publisher is held hostage by incentives from an auction system that not only encourages but also rewards dark patterns.

And almost all modern news websites are guilty of some variation of anti-user patterns. As a reminder, the NNgroup defines interaction cost as the sum of mental and physical efforts a user must exert to reach their goal. In the physical world, hostile architecture refers to a park bench with spikes that prevent people from sleeping. In the digital world, we can call it a system carefully engineered to extract metrics at the expense of human cognitive load. Let's also cover some popular user-hostile design choices that have gone mainstream.

The Pre-Read Ambush

Selected GDPR examplesThe advantage and disadvantages of these have been discussed in tech circles ever since they launched.

When a user clicks a news link, they have a singular purpose of reading the headline and going through the text. The problem is that upon page load, users are greeted by what I call Z-Index Warfare. The GDPR/Cookie banners occupy the bottom 30%. The user scrolls once and witnesses a "Subscribe to our Newsletter" modal. Meanwhile the browser has started hammering them with allow notification prompts.

The user must perform visual triage, identify the close icons (which are deliberately given low contrast) and execute side quests just to access the 5KB of text they came for. Let's look at how all these anti-patterns combine into a single, user-hostile experience.

by Shubham Bose, Thatshubham |  Read more:

Images: uncredited

NASA's 'Lunar Viceroy' on Moon Base Plans

NASA's “Lunar Viceroy” talks about how NASA will build a Moon base (Ars Technica)

Image: Rendering of a Moon base that will be built over the next decade. Credit: NASA

[ed. In the next 10 years.]

Seeing Like a Sedan

Waymos and Cybercabs see the world through very different sensors. Which technology wins out will determine the future of self-driving vehicles.

Picture a fall afternoon in Austin, Texas. The city is experiencing a sudden rainstorm, common there in October. Along a wet and darkened city street drive two robotaxis. Each has passengers. Neither has a driver.

Both cars drive themselves, but they perceive the world very differently.

 

One robotaxi is a Waymo. From its roof, a mounted lidar rig spins continuously, sending out laser pulses that bounce back from the road, the storefronts, and other vehicles, while radar signals emanate from its bumpers and side panels. The Waymo uses these sensors to generate a detailed 3D model of its surroundings, detecting pedestrians and cars that human drivers might struggle to see.

In the next lane is a Tesla Cybercab, operating in unsupervised full self-driving mode. It has no lidar and no radar, just eight cameras housed in pockets of glass. The car processes these video feeds through a neural network, identifying objects, estimating their dimensions, and planning its path accordingly.

This scenario is only partially imaginary. Waymo already operates, in limited fashion, in Austin, San Francisco, Los Angeles, Atlanta, and Phoenix, with announced plans to operate in many more cities. Tesla Motors launched an Austin pilot of its robotaxi business in June 2025, albeit using Model Y vehicles with safety monitors rather than the still-in-development Cybercab. The outcome of their competition will tell us much about the future of urban transportation.

The engineers who built the earliest automated driving systems would find the Waymo unsurprising. For nearly two decades after the first automated vehicles emerged, a consensus prevailed: To operate safely, an AV required redundant sensing modalities. Cameras, lidar, and radar each had weaknesses, but they could compensate for each other. That consensus is why those engineers would find the Cybercab so remarkable. In 2016, Tesla broke with orthodoxy by embracing the idea that autonomy could ultimately be solved with vision and compute and without lidar — a philosophical stance it later embodied in its full vision-only system. What humans can do with their eyeballs and a brain, the firm reasoned, a car must also be able to do with sufficient cameras and compute. If a human can drive without lidar, so, too, can an AV… or so Tesla asserts.

This philosophical disagreement will shortly play out before our eyes in the form of a massive contest between AVs that rely on multiple sensing modalities — lidar, radar, cameras — and AVs that rely on cameras and compute alone.

The stakes of this contest are enormous. The global taxi and ride-hailing market was valued at approximately $243 billion in 2023 and is projected to reach $640 billion by 2032. In the United States alone, people take over 3.6 billion ride-hailing trips annually. Converting even a fraction of this market to AVs represents a multibillion-dollar opportunity. Serving just the American market, at maturity, will require millions of vehicles.

Given the scale involved, the cost of each vehicle matters. The figures are commercially sensitive, but it is certainly true that cameras are cheaper than lidar. If Tesla’s bet pays off, building a Cybercab will cost a fraction of what it will take to build a Waymo. Which vision wins out has profound implications for how quickly each company will be able to put vehicles into service, as well as for how quickly robotaxi service can scale to bring its benefits to ordinary consumers across the United States and beyond.

by Andrew Miller, Asterisk |  Read more:

Image: Jared Nangle

[ed. via DWAtV:]

***

A relevant thing about Elon Musk is that, while he has a lot of technical expertise and can accomplish a lot of seemingly impossible tasks, he also just says things.

For example, here’s another thing he just said this week, in a trick he’s pulled several times without delivering, where the prediction market is at 12% but that seems rather high to me:

NewsWire: Elon Musk offers to pay TSA workers' salaries amid government shutdown.

Just saying things, and announcing with confidence he will do things he probably cannot do, is central to his strategy of then yelling at people to sleep on floors until they manage to do it, which occasionally works to at least some extent. Elon Musk may plausibly start such a project, but the chances he achieves the goals he is stating are very low.

Announce periodically you are going to the moon and stars, and if one time you end up with SpaceX, it’s still a win. It’s worked for him quite well, so far.

Vertical Farming

via:
[ed. Impressive.]

***

"While most vertical farms are limited to lettuces, Plenty spent the past decade designing a patent-pending, modular growing system flexible enough to support a wide variety of crops – including strawberries. Growing on vertical towers enables uniform delivery of nutrients, superior airflow and more intense lighting, delivering increased yield with consistent quality.

Every element of the Plenty Richmond Farm–including temperature, light and humidity–is precisely controlled through proprietary software to create the perfect environment for the strawberry plants to thrive. The farm uses AI to analyze more than 10 million data points each day across its 12 grow rooms, adapting each grow room’s environment to the evolving needs of the plants – creating the perfect environment for Driscoll’s proprietary plants to thrive and optimizing the strawberries’ flavor, texture and size. Even pollination has been engineered by Plenty, using a patent-pending method that evenly distributes controlled airflow across the strawberry flowers for more efficient and effective pollination than using bees, supporting more uniform strawberry size and shape."  ~ Greater Richmond Partnership

Bow and Arrow Diffusion Across Cultures

Study pinpoints when bow and arrow came to North America (Ars Technica)

Image:A petroglyph from Newspaper Rock, a site along Indian Creek in southeastern Utah. Credit: David Hiser/Environmental Protection Agency/Public domain
[ed. I haven't finished half my morning coffee and already know about atlatls (and why dogs love them), risk-buffering, and frozen feces knives. Is science great, or what?]

***

1. Introduction

In his book, Shadows in the Sun, Davis (1998: 20) recounts what is now arguably one of the most popular ethnographic accounts of all time:

“There is a well known account of an old Inuit man who refused to move into a settlement. Over the objections of his family, he made plans to stay on the ice. To stop him, they took away all of his tools. So in the midst of a winter gale, he stepped out of their igloo, defecated, and honed the feces into a frozen blade, which he sharpened with a spray of saliva. With the knife he killed a dog. Using its rib cage as a sled and its hide to harness another dog, he disappeared into the darkness.”

Since publication, this story has been told and re-told in documentaries, books, and across internet websites and message boards (Davis, 2007, Davis, 2010; Gregg et al., 2000; Kokoris, 2012; Taete, 2015). Davis states that the original source of the tale was Olayuk Narqitarvik (Davis, 2003, Davis, 2009). It was allegedly Olayuk's grandfather in the 1950s who refused to go to the settlements and thus fashioned a knife from his own feces to facilitate his escape by skinning and disarticulating a dog. Davis has admitted that the story could be “apocryphal”, and that initially he thought the Inuit who told him this story was “pulling his leg” (Davis, 2009, Davis, 2014). Yet, as support for the credibility of the story, Davis cites the auto-biographical account of Peter Freuchen, the Danish arctic explorer (Hodge and Davis, 2012). Freuchen (1953) describes how he dug himself a pit to sleep in and woke up trapped by snow. Every effort to get out that he tried failed. Finally, he recalled seeing dog's excrement frozen solid as a rock. So, Freuchen defecated in his hand, shaped it into a chisel, and waited for it to freeze solid. He then used the implement to free himself from the snow: “I moved my bowels and from the excrement I managed to fashion a chisel-like instrument which I left to freeze… At last I decided to try my chisel and it worked” (Freuchen, 1953: 179).

2. Materials and methods
In order to procure the necessary raw materials for knife production, one of us (M.I.E.) went on a diet with high protein and fatty acids, which is consistent with an arctic diet, for eight days (Binford, 2012; Fumagalli et al., 2015) (Table S1). The Inuit do not only eat meat from maritime and terrestrial animals (Arendt, 2010; Zutter, 2009), and there were three instances during the eight-day diet that M.I.E. ate fruit, vegetables, or carbohydrates (Table S1).

Raw material collection did not begin until day four, and then proceeded regularly for the next five days (Table S1). Fecal samples were formed into knives using ceramic molds, “knife molds” (Figs. S1–S2), or molded by hand, “hand-shaped knives” (Fig. S3). All fecal samples were stored at −20 °C until the experiments began.