I plan to continue to leave the Trump administration out of monthly roundups – I will do my best to only cover the administration as it relates to my particular focus areas. That is ‘if I start down this road there is nowhere to stop’ and ‘other sources are left to cover that topic’ and not ‘there are not things worth mentioning.’
I also had forgotten this was originally from Napoleon rather than Bill Watterson.
Dylan O’Sullivan: Napoleon once said that the surprising thing was not that every man has his price, but how low it is, and I can’t help but see that everywhere now.
You destroyed and betrayed yourself for a handful of clicks.
Jasmeet: Dostoevsky wrote, “Your worst sin is that you have destroyed and betrayed yourself for nothing.”
That seems especially appropriate lately, for mostly non-AI reasons.
Disney shuts down 538, Nate Silver offers a few words. You can get all their data off of GitHub. It is a shame that 538 could not be sustained, and I am sad for those who lost their jobs, but as Nate Silver notes their business model was unsustainable inside Disney. Hopefully Silver Bulletin and others can carry the torch in the future.
Restaurant productivity technically rose 15% during the pandemic and sustained that gain, but it turns out it is entirely attributable to the rise of takeout and delivery. That’s not a rise in productivity, that’s delivering a different product that is easier to produce and also in general worse. If anything this change is bad.
Zeynep Tufekci, who has been on top of this from the beginning, reminds us of the massive efforts to mislead us about the fact that Covid-19 could have come from a lab. We don’t know whether Covid-19 came from a lab, but we do know it very much could have, that there was a massive coordinated operation to suppress this fact, and most importantly that this means that we are continuing to do lab research that is likely to cause future pandemics.
Aditya Agarwal models a person’s ambition as something you can unlock and unleash, but not fundamentally change. I think I mostly agree with a soft version of this. There are plenty of people who are ambitious but haven’t been given or felt opportunity, or you can remove something blocking them, but if an adult is at core not so ambitious you should assume you can’t fix that.
Travel advice from The Technium, mostly endorsed by Tyler Cowen. Definitely some good tips in there, even for those who have little desire for the kind of experience this is striving to achieve. The core recommendation is as a baseline to take trips with about 10 days of intense travel, with 12 non-travel days total, and you start with the most challenging content first.
One pattern to notice is the need to focus on absolute marginal cost of things like renting a driver or paying for entry to a museum and what not, rather than looking at relative cost or comparing to what might seem expensive or fair. Only the absolute costs matter.
I continue to not have the desire to do this style of travel that he calls E&E, for engagement and experience, but it does appeal more than the traditional R&R style, for rest and recreation. I can do R&R at home, in many ways far better than I can travelling, at almost no marginal cost. But then, I can do my version of E&E at home too, and often do, although not as often as I should.
A perspective on what does and does not cost you precious Weirdness Points. The particular claim is that being vegan while respecting others preferences costs very little, whereas telling others what to eat costs a lot of points. I agree in relative terms, although I disagree in absolute terms. The general pattern of ‘telling others to do [weird thing] costs vastly more than doing it yourself’ definitely applies, but the [weird thing] can still be expensive.
The Dead Planet Theory, the generalization that most of life is showing up, if showing up includes attempting to Do the Thing at all. As in, yes You Can Just Do Things, and the reason you can is that you almost certainly won’t, which means little competition.
Ashwin Sharma: Basically, Joseph Campbell taught me to ritualize almost everything I considered mundane. Like my morning coffee, my afternoon walk, and my bedtime reading. I learned over time that this is because ritualizing ordinary moments makes them sacred. And when something becomes sacred, when you give it meaning, it gives meaning back to you.
Chris Cordry: Ritualizing everyday actions also means you bring more attention to them. When we give attention to something on a deep level, we can experience it as sacred independent of cognitive meaning-making.
I wrote Bring Back the Sabbath, so I’ve long been a supporter of this, and I agree. The more rituals you can make work for you, the longer you can sustain them, the better. There are of course costs, but consider this a claim that the Ritual Effect matters more than you think it does.
Your periodic reminder that some important people need lately:
Lars Doucet: The counterpart to “move fast and break things” is “don’t be in such a hurry that you waste time.”
This is commonly misunderstood as saying, “please don’t go fast.” It means the opposite! It means, “optimizing for the *feelingof going fast will *MAKE YOU SLOWER*”
The “move fast and break things” vibes, as fun as it is, does pack in a certain tolerance for carelessness and “we’ll figure it out later.”
Sometimes being careful and figuring it out before you leave the house makes you arrive at the destination faster!
The most obvious application in software land is technical debt. You do want rapid prototypes and you do want to avoid premature optimization and over engineering.
But also nothing slows you down like an easily avoided big ball of mud.
Really you just need to very good at asking yourself “am I chasing a goal or am I chasing a vibe?” There are a lot of things that FEEL like going fast that aren’t actually going fast, just being in a hurry, which is a totally different thing.
There’s a similar phenomenon with various cargo-cult symptoms surrounding work culture. It’s very easy to signal that you are very busy, but that’s not the same thing as working hard, which in turn is not the same thing as getting stuff done efficiently and effectively.
I didn’t like The Great Gatsby (the book) either when I was forced to read it, not great at all, do not recommend. I don’t put it in ‘least favorite book’ territory like Tracing Woods does, but I respect that take. My least favorite book, by this criteria, would probably be One Hundred Years of Solitude. Absolutely dreadful. It’s actually amazing how consistently awful were the fiction books schools forced me to read.
Who believes in astrology? Astrology is the Platonic ideal of Obvious Nonsense, so you can use belief in it as a way to measure various group differences. Intelligence is the biggest predictor of non-belief listed in the abstract, followed by education, which makes sense. Religiosity and spirituality are null effects. That speaks poorly of religiosity, since all the major religions are in agreement that astrology is bunk. Whereas it speaks well of spirituality, because it seems like it should be positively correlated to astrology, especially given that right-wing individuals believe in astrology less.
The most interesting one is no impact of ‘scientific trust’ on astrological belief. You would think that belief in science, whether it was real science or Science™, would mean you trusted the scientists who tell you astrology is Obvious Nonsense. This isn’t the case, suggesting that a lot of ‘trust in science’ is actually ‘trust’ in general.
Ryan Peterson: My friend’s startup uses facial recognition to identify employees entering the office and then plays the walk-out theme song of their choice as if they were a WWE superstar.
Would this even be legal in Germany? No wonder Europe is falling behind.
Washington Post will be writing in its op-eds every day in support and defense of two pillars: personal liberties and free markets. They’ll cover other topics too, but the arguments against personal liberties and free markets will be left to others.
As a very strong supporter of both personal liberties and free markets, I love this.
In response to this, there were a bunch of people on the left who got Big Mad and accused Bezos of some sort of betrayal of democracy. To which I say, thank you for letting us know who you are and what you think of free markets and personal liberties. Whereas I saw some on the right, who have not exactly been the biggest free market fans recently, and have a spotty record on personal liberties, cheering this on, so maybe negative polarization can work in our favor for once?
Walks are great. The best walks are aimful walks, where you have an ultimate destination in mind from which you will gain value, but ideally you can proceed there and back at a leisurely pace and wander while doing so. However your amount of physical activity is not fixed, so you can and should also go on aimless walks, which both help you stay active and can help you think better about various things, either alone or with a companion or two.
LessOnline 2will take place at Lighthaven, from May 30 to June 1. I plan on being there. LessOnline 1 was pretty awesome and I’m excited to run it back. Last time I ran a makeshift ‘show the Zvi process’ workshop, haven’t decided what if anything I’ll run this time. Early bid pricing lasts until end of March.
If you are a charity whose goals are compatible with Jaan’s priorities, or especially if you are a good fit for the freedom or fairness tracks, I highly recommend that you apply. The cost is low and the upside is high. And who know, perhaps you will even appear in a future version of The Big Nonprofits Post if I happen to be one of the recommenders for your round.
Calling local Magic gamers: The NYC Invitational Series is coming, starting with the NYC Pauper Open on May 25 at the Upper West Side Hex, building towards an end-of-year invitational. Local game stores are invited to reach out to get in on the fun.
While we’re on that subject, of course, my official trading experience was at Jane Street Capital, which is always hiring. It didn’t work out for me but they’re great people and if you’re going to do that kind of work it’s a pretty great place.
Suzy Weiss argues that comedians should not be hot. I strongly disagree. This is a confusion of the wonderful fact that comedians are allowed to not be hot – which is great – with saying that hotness, or more precisely actually looking good by being not only hot but also well-dressed, shouldn’t be allowed. A central example here (that Suzy uses) is Tina Fey, who is definitely hot, and was hot even when she was playing the intentionally not hot Liz Lemon. Suzy Weiss argues that being ugly, here, is an asset.
To me, that’s exactly the proof that the thesis doesn’t hold water. There’s nothing wrong with hot. The idea that people who are hot, or otherwise advantaged, don’t have problems to use for material, is Obvious Nonsense. What you don’t want is for the hot to crowd out the not hot.
Consider music. In music, the product is fully audio, and yet being hot is increasingly a huge advantage that crowds out the not hot. It’s really tough to be an ugly (or even Hollywood homely) rock star, especially as a woman. That means we’ve missed out on tons of great musicians, and the exceptions that make it anyway prove the rule (but for obvious reasons there will be no examples here).
Alec Stapp: Funny how most people legit believe this.
Philly Gov: Yeah that’s crazy but it also happens to be right specifically in regards to me.
Alec Stapp: Same.
That comes from this paper, but the paper says the peak is around 23.5 years old, whereas the graph here is much earlier.
I am a strange case, in that I didn’t listen to essentially any non-kids non-classical music until college, and I did only a small amount of ‘listening to what is coming out right now.’ So not a representative case, but I very much prefer older music than that, in general. But I do notice that I have a strong preference for the particular relatively new songs I did listen to about that time, including the ones that get reinvented every so often. So there’s that.
I do notice that when I sample new music from recent decades I usually hate it, to the point where I essentially have given up on playlists of hot new music. They are consistently very bad. New (to me!) older music that stood the test of time tends to work better, down to ~1965 or so, which is well before I was born.
My actual music theory is that in micro terms the public has no false positives once songs are at least a few years old. Marketing can make fetch happen for a month or two, but it fades. Your hits that last are your hits for a reason. One hit wonder songs are always bangers and almost always yes it was their best song when I investigate. Artists that break out, break out for a reason (although it can involve looks or dance moves or hard work and so on). The public does offer false negatives – there are gems they don’t appreciate – but that’s largely due to lack of exposure and opportunity.
The public’s macro preferences are of course up for debate. Their genre preferences are wrong, but they are entitled to their opinions on that.
Will Severance stick the landing? Jeff Maurer is skeptical. I agree the prior is to be skeptical, but the vibes tell me to be optimistic this time around. I very much get the sense that they know where things are going and what story they are telling. I’m also at the point where I’m mostly willing to endorse the show even if they only half stick the landing.
Pretty good but growth rate seems to be slowing a bit.
Sunder Pichai: Exciting new @Waymo milestone: Waymo One is now serving 200k+ paid trips each week across LA, Phoenix and SF – that’s 20x growth in less than two years! Up next: Austin, Atlanta and Miami.
New York is alas likely to take a while due to regulatory concerns. But it’s a real shame to see the latest +50k take a full four months. We need to be on an exponential here, people! This now looks kind of linear and I am not here for that, very literally.
It’s so weird that this new area does not yet connect to the existing San Francisco coverage zone, but actual usage patterns are often not what you would think they are.
Kevin Kwok: Waymo is executing a textbook pincer movement against SFO.
Give me Waymo in East Bay and to SFO and I’ll be a lot more tempted to visit.
Well, you can’t have Waymos yet in New York, so can I interest you in armed guards?
Nikita Bier: Over the last few months, I’ve been advising @bookprotectors: a new app for ordering an on-demand security detail. Or more simply: Uber with guns.
Today, they’re debuting in Los Angeles and NYC at No. 3 on the App Store.
If you have a hot date this weekend, pick her up in a Protector.
5 hour minimum booking. All ex-military or ex-law enforcement.
Because our world is bonkers crazy, their top weapon are orange triangles? As in, if a truck stops, within 10 minutes you have to put out orange triangles. But a driverless truck has no way to do that, and so far Aurora has been unable to get a waiver, because they can’t show an alternative that would be at least as safe – never mind that obviously the self-driving trucks will overall be vastly safer. So now they’re in court.
If they don’t get an exception, Aurora won’t have to have a person in every truck. It does mean they have a Snow-Crash-pizza-delivery-style 10-minute countdown to ‘rescue’ any given truck that runs into trouble. So there needs to be someone 10 minutes or less away from every truck at all times. That means you need a lot of trucks to justify the humans who are constantly on call to leap into action with orange triangles.
Evidence on the Hot Hand in Jeopardy. I think the study underestimates the extent to which being hot and each correct answer inform skill differences, and also how much small differences in skill or being hot should impact wagering size. Remember that contestants have very high uncertainty about their skills in terms of knowledge and also ability to execute, and that they can actively improve their skills over the course of the game, and that confidence actually matters.
Also people think extremely poorly about this question. I asked o1-pro and got an answer that was a mix of stating obvious considerations plus complete nonsense. The impact here is only $100-$500 more per wager. That’s not as much as one might think, and the experienced players who don’t vary their wagers probably are mostly just using an established heuristic. Partly this is to keep their focus on other things.
It’s not even clear if being a stronger player should in general make you wager more – if you need variance you should probably risk everything even if you’re under 50%, if you’re sufficiently confident might as well risk it all to win more and more money, it’s in a weird in-between situation (or when you don’t like your chances in this particular category), or especially where you’re in a close 3-way race where polarizing your score is a bad idea until you can break 70%+, where you want to do anything else.
If I was going on Jeopardy for real, I would likely have AI build me a game simulator, because I have actual no idea what the right strategy is here, and it’s important.
This is part of a longstanding tradition where economists analyze people’s decisions, only take into account half the considerations involved, and declare actions irrational.
Sports have an analytics problem, in that teams and players are Solving For the Equilibrium, and that is often resulting in less appealing games. What to do?
As always, don’t hate the player, change the game. The rules have to adjust. The tricky part is that it can be extremely difficult to preserve the things that make the game great, especially while also preserving the game’s traditions and continuity.
MLB largely solved its ‘games take forever’ problem, but has a pitchers being pulled too early problem rapidly getting even worse, and a severe strikeout problem.
The pitchers being pulled issue can be solved via rules change, in particular the double hook, which helps in other ways too.
Strikeouts are trickier, but the solution there is also likely to try and limit pitching changes, combined perhaps with moving the mound back, perhaps in exchange you pull back the fences so home runs are harder and more balls end up in play. I would experiment with aggressive solutions here, even things like ‘make the ball a little bigger,’ or ‘formalize that the strike zone shrinks when you have two strikes and expands when you have three balls.’
The NBA has a 3-point shot problem. An occasional three pointer is fine, but things are very out of hand. The math on 3-point shots is too good, and the weird part is how long it took everyone to notice.
Or at least I think it’s out of hand. Many agree. Others like the current game.
The obvious place to start if you want to change things back, other than ‘move the three point line back,’ is to only award two shots rather than three if you are fouled on a three point shot except in the last two minutes of the game. Another more radical idea is to strengthen two point shots, by treating shooting fouls like a 2-point goaltending if the ball hits the rim, note you can adjust what counts as a foul to taste.
The NFL’s major shift is teams go for it more on fourth down, but that’s good. They warn that there are shifts towards pass-heavy games, but that’s the kind of change that you can fix with rules tweaks, as the NFL has lots of ‘fiddly bits’ in its rules, especially regarding penalties, that are already constantly adjusted.
The directors adopted more of a colorful 1990s aesthetic than the haunting art that originally inspired their film. While some fans of Stålenhag’s work expressed disappointment at this artistic choice, the artist himself had nothing but praise. “When you paint or draw something, you can do anything,” Stålenhag has said. ‘There are no constraints other than the time you spend painting. To see a live action movie make something I painted and to see it so truthfully translated impressed me on all levels.”
Bringing a vision to life
The task of bringing that aesthetic to the screen fell to people like Oscar-winning production designer Dennis Gassner, whose many credits include Barton Fink, Bugsy, The Hudsucker Proxy, The Truman Show, Blade Runner 2049, Skyfall, Quantum of Solace, Spectre, Into the Woods, and Big Fish. (In fact, there’s a carousel featured in the design of the Happyland amusement park that Gassner first used in Big Fish.) He and Richard L. Johnson (Pacific Rim, The Avengers) led a team that not only designed and constructed more than 100 sets for the film, but also created a host of original robot characters to augment the ones featured in Stålenhag’s book.
On set during filming of The Electric State Netflix
All the robots featured in the film have their own stories, “distinct personalities and emotional arcs,” per Anthony Russo. The directors wanted the robots to “feel authentic to the alternate 1990s but still had roots in recognizable designs,” according to Joe Russo—the kinds of things one would see in vintage commercials, shopping malls, corporate branding, and so forth. “Everything is story,” Gassner told Ars. “Story is paramount. What story are you telling? Who are the characters in this story? What are their environments? How do they feel within the environments?”
Gassner’s team designed about 175 robots all told, selecting their favorites to be featured in the final film. “It’s like a great casting call,” Gassner said. “So we played a lot, there was a long time of development in the art department between myself and a vast team of artists. We worked very closely with the visual effects department, but what the characters look like are part of the art department, and our collaboration with Joe and Anthony Russo on the study of characters. That was the fun part, getting the shape right, the character right, the color right, the clothing right.”
Biohybrid robots work by combining biological components like muscles, plant material, and even fungi with non-biological materials. While we are pretty good at making the non-biological parts work, we’ve always had a problem with keeping the organic components alive and well. This is why machines driven by biological muscles have always been rather small and simple—up to a couple centimeters long and typically with only a single actuating joint.
“Scaling up biohybrid robots has been difficult due to the weak contractile force of lab-grown muscles, the risk of necrosis in thick muscle tissues, and the challenge of integrating biological actuators with artificial structures,” says Shoji Takeuchi, a professor at the Tokyo University, Japan. Takeuchi led a research team that built a full-size, 18 centimeter-long biohybrid human-like hand with all five fingers driven by lab-grown human muscles.
Keeping the muscles alive
Out of all the roadblocks that keep us from building large-scale biohybrid robots, necrosis has probably been the most difficult to overcome. Growing muscles in a lab usually means a liquid medium to supply nutrients and oxygen to muscle cells seeded on petri dishes or applied to gel scaffoldings. Since these cultured muscles are small and ideally flat, nutrients and oxygen from the medium can easily reach every cell in the growing culture.
When we try to make the muscles thicker and therefore more powerful, cells buried deeper in those thicker structures are cut off from nutrients and oxygen, so they die, undergoing necrosis. In living organisms, this problem is solved by the vascular network. But building artificial vascular networks in lab-grown muscles is still something we can’t do very well. So, Takeuchi and his team had to find their way around the necrosis problem. Their solution was sushi rolling.
The team started by growing thin, flat muscle fibers arranged side by side on a petri dish. This gave all the cells access to nutrients and oxygen, so the muscles turned out robust and healthy. Once all the fibers were grown, Takeuchi and his colleagues rolled them into tubes called MuMuTAs (multiple muscle tissue actuators) like they were preparing sushi rolls. “MuMuTAs were created by culturing thin muscle sheets and rolling them into cylindrical bundles to optimize contractility while maintaining oxygen diffusion,” Takeuchi explains.
The curious case of the missing Kickstarter spoons.
An attention-grabbing Kickstarter campaign attempting to reinvent the measuring spoon has turned into a mad, mad, mad, mad world for backers after years of broken promises and thousands of missing spoons.
The mind-boggling design for the measuring spoon first wowed the Internet in 2016 after a video promoting the Kickstarter campaign went viral and spawned widespread media coverage fawning over the unique design.
Known as Polygons, the three-in-one origami measuring spoons have a flat design that can be easily folded into common teaspoon and tablespoon measurements. “Regular spoons are so 3000 BC,” a tagline on the project’s website joked.
For gadget geeks, it’s a neat example of thinking outside of the box, and fans found it appealing to potentially replace a drawer full of spoons with a more futuristic-looking compact tool. Most backers signed up for a single set, paying $8–$12 each, while hundreds wanted up to 25 sets, a handful ordered 50, and just one backer signed up for 100. Delivery was initially promised by 2017, supposedly shipping to anywhere in the world.
But it’s been about nine years since more than 30,000 backers flocked to the Kickstarter campaign—raising more than $1 million and eclipsing Polygons’ $10,000 goal. And not only have more than a third of the backers not received their spoons, but now, after years of updates claiming that the spoons had been shipped, some backers began to wonder if the entire campaign might be a fraud. They could see that Polygons are currently being sold on social media and suspected that the maker might be abusing backers’ funds to chase profits, seemingly without ever seriously intending to fulfill their orders.
One Kickstarter backer, Caskey Hunsader, told Ars that he started doubting if the spoon’s designer—an inventor from India, Rahul Agarwal—was even a real person.
Ars reached out to verify Agarwal’s design background. We confirmed that, yes, Agarwal is a real designer, and, yes, he believes there is a method to the madness when it comes to his Kickstarter campaign, which he said was never intended to be a scam or fraud and is currently shipping spoons to backers. He forecasted that 2025 is likely the year that backers’ wait will finally end.
But as thousands of complaints on the Kickstarter attest, backers have heard that one before. It’s been two years since the last official update was posted, which only promised updates that never came and did not confirm that shipments were back on track. The prior update in 2022 promised that “the time has finally arrived when we begin bulk shipping to everyone!”
Hunsader told Ars that people seem mostly upset because of “bullshit,” which is widely referenced in the comments. And that anger is compounded “by the fact that they are producing, and they are selling this product, so they are operating their business using funds that all these people who were their first backers gave them, and we’re the ones who are not getting the product. I think that’s where the anger comes from.”
“It’s been years now, and [I’ve] watched as you promise good people their products and never deliver,” one commenter wrote. “Wherever you try… to sell [your] products, we will be there reminding them of the empty orders you left here.”
“Where is my item? I am beyond angry,” another fumed.
Those who did receive their spoons often comment on the substantial delays, but reviews are largely positive.
“Holy crap, folks,” a somewhat satisfied backer wrote. “Hell has frozen over. I finally got them (no BS).”
One backer was surprised to get twice as many spoons as expected, referencing an explanation blaming Chinese New Year for one delay and writing, “I can honestly say after 8 years… and an enormous amount of emails, I finally received my pledge. Except… I only ordered 3… and I received 6. I’d be inclined to ship some back to Polygons… bare with me… I’ll return them soon… I appreciate your patience… mebbe after Chinese New Years 2033…”
Agarwal agreed to meet with Ars, show us the spoon, and explain why backers still haven’t gotten their deliveries when the spoon appears widely available to purchase online.
Failing prototypes and unusable cheap knockoffs
As a designer, Agarwal is clearly a perfectionist. He was just a student when he had the idea for Polygons in 2014, winning design awards and garnering interest that encouraged him to find a way to manufacture the spoons. He felt eager to see people using them.
Agarwal told Ars that before he launched the Kickstarter, he had prototypes made in China that were about 85 percent of the quality that he and his collaborators at InventIndia required. Anticipating that the quality would be fully there soon, Agarwal launched the Kickstarter, along with marketing efforts that Agarwal said had to be squashed due to unexpectedly high interest in the spoons.
This is when things started spiraling, as Agarwal had to switch manufacturers five times, with each partner crashing into new walls trying to execute the novel product.
Once the Kickstarter hit a million dollars, though, Agarwal committed to following through on launching the product. Eventually, cheap knockoff versions began appearing online on major retail sites like Walmart and Amazon toward the end of 2024. Because Agarwal has patents and trademarks for his design, he can get the knockoffs taken down, but they proved an important point that Agarwal had learned the hard way: that his design, while appearing simplistic, was incredibly hard to pull off.
Ars handled both a legitimate Polygons spoon and a cheap knockoff. The knockoff was a flimsy, unusable slab of rubber dotted with magnets; the companies aping Agarwal’s idea are seemingly unable to replicate the manufacturing process that Agarwal has spent years perfecting to finally be able to widely ship Polygons today.
On the other hand, Agarwal’s spoon is sturdy, uses food-grade materials, and worked just as well measuring wet and dry ingredients during an Ars test. A silicon hinge connects 19 separate plastic pieces and ensures that magnets neatly snap along indented lines indicating if the measurement is a quarter, half, or whole teaspoon or tablespoon. It took Agarwal two and a half years to finalize the design while working with InventIndia, a leading product development firm in India. Prototyping required making special molds that took a month each to iterate rather than using a 3D-printing shortcut whereby multiple prototypes could be made in a day, which Agarwal said he’d initially anticipated could be possible.
Around the time that the prototyping process concluded, Agarwal noted, COVID hit, and supply chains were disrupted, causing production setbacks. Once production could resume, costs became a factor, as estimates used to set Kickstarter backer awards were based on the early failed Chinese prototype, and the costs of producing a functioning spoon were much higher. Over time, shipping costs also rose.
As Kickstarter funds dwindled, there was no going back, so Agarwal devised a plan to sell the spoons for double the price ($25–$30 a set) by marketing them on social media, explaining this in a note to backers posted on the Polygons site. Those sales would fund ongoing manufacturing, allowing profits to be recycled so that Kickstarter backers could gradually receive shipments dependent on social media sales volumes. Orders from anyone who paid extra for expedited shipping are prioritized.
It’s a math problem at this point, with more funding needed to scale. But Agarwal told Ars that sales on Shopify and TikTok Shop have increased each quarter, most recently selling 30,000 units on TikTok, which allowed Polygons to take out a bigger line of credit to fund more manufacturing. He also brought in a more experienced partner to focus on the business side while he optimizes production.
Agarwal told Ars that he understands trust has been broken with many Kickstarter backers, considering that totally fair. While about 38 percent of backers’ orders still need filling, he predicts that all backers could get their orders within the next six to eight months as Polygons becomes better resourced, but that still depends on social media sales.
Agarwal met Ars after attending a housewares show in Chicago, where he shopped the spoons with retailers who may also help scale the product in the coming years. He anticipates that as the business scales, the cost of the spoons will come back down. And he may even be able to move onto executing other product designs that have been on the backburner as he attempts to work his way out of the Kickstarter corner he backed himself into while obsessing over his first design.
Kickstarter problem goes beyond Polygons
Hunsader told Ars there’s a big difference “in a lie versus bad management,” suggesting that as a business owner who has managed Kickstarter campaigns, he thinks more transparency likely could’ve spared Polygons a lot of angry comments.
“I am not sitting here with a dart board with [Agarwal’s] face on it, being like, when am I going to get my damn spoons?” Hunsader joked. But the campaign’s Kickstarter messaging left many backers feeling like Polygons took backers’ money and ran, Hunsader said.
Unlike people who saw the spoons going viral on social media, Hunsader discovered Polygons just by scrolling on Kickstarter. As a fan of geeky gadgets, he used to regularly support campaigns, but his experience supporting Polygons and monitoring other cases of problematic Kickstarters have made him more hesitant to use the platform without more safeguards for backers.
“It’s not specifically a Polygons problem,” Hunsader told Ars. “The whole Kickstarter thing needs maybe just more protections in place.”
Kickstarter did not respond to Ars’ request to comment. But Kickstarter’s “accountability” policy makes clear that creators “put their reputation at risk” launching campaigns and are ultimately responsible for following through on backer promises. Kickstarter doesn’t issue refunds or guarantee projects, only providing limited support when backers report “suspicious activity.”
Redditors have flagged “shitty” Kickstarter campaigns since 2012, three years after the site’s founding, and the National Association of Attorneys General—which represents US state attorneys general—suggested in 2019 that disgruntled crowdfunding backers were increasingly turning to consumer protection laws to fight alleged fraud.
In 2015, an independent analysis by the University of Pennsylvania estimated that 9 percent of Kickstarter projects didn’t fulfill their rewards. More recently, it appeared that figure had doubled, as Fortune reported last year that an internal Kickstarter estimate put “the amount of revenue that comes from fraudulent projects as high as 18 percent.” A spokesperson disputed that estimate and told Fortune that the platform employs “extensive” measures to detect fraud.
Agarwal told Ars that he thinks it’s uncommon for a campaign to continue fulfilling backer rewards after eight years of setbacks. It would be easier to just shut down and walk away, and Kickstarter likely would not have penalized him for it. While the Kickstarter campaign allowed him to reach his dream of seeing people using his novel measuring spoon in the real world, it’s been bittersweet that the campaign has dragged out so long and kept the spoons out of the hands of his earliest supporters, he told Ars.
Hunsader told Ars that he hopes the Polygons story serves as a “cautionary tale” for both backers and creators who bite off more than they can chew when launching a Kickstarter campaign. He knows that designers like Agarwal can take a reputational hit.
“I don’t want to make somebody who has big dreams not want to dream, but you also, when you’re dealing with things like manufacturing technology, have to be realistic about what is and is not accomplishable,” Hunsader said.
Polygons collaborators at InventIndia told Ars that Agarwal is “dedicated and hard-working,” describing him as “someone deeply committed to delivering a product that meets the highest standards” and whose intentions have “always” been to “ship a perfect product.”
Agarwal’s team connected with Hunsader to schedule his Kickstarter reward shipment on Friday. Hunsader told Ars he doesn’t really care if it takes another nine years. It’s just a spoon, and “there are bigger fish to fry.”
“Listen, I can buy that narrative that he was somebody who got totally overwhelmed but handled it in the worst possible way ever,” Hunsader said.
He plans to continue patiently waiting for his spoons.
This story was updated on March 14 to update information on the Polygons Kickstarter campaign.
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.
A new study from Columbia Journalism Review’s Tow Center for Digital Journalism finds serious accuracy issues with generative AI models used for news searches. The research tested eight AI-driven search tools equipped with live search functionality and discovered that the AI models incorrectly answered more than 60 percent of queries about news sources.
Researchers Klaudia Jaźwińska and Aisvarya Chandrasekar noted in their report that roughly 1 in 4 Americans now uses AI models as alternatives to traditional search engines. This raises serious concerns about reliability, given the substantial error rate uncovered in the study.
Error rates varied notably among the tested platforms. Perplexity provided incorrect information in 37 percent of the queries tested, whereas ChatGPT Search incorrectly identified 67 percent (134 out of 200) of articles queried. Grok 3 demonstrated the highest error rate, at 94 percent.
A graph from CJR shows “confidently wrong” search results. Credit: CJR
For the tests, researchers fed direct excerpts from actual news articles to the AI models, then asked each model to identify the article’s headline, original publisher, publication date, and URL. They ran 1,600 queries across the eight different generative search tools.
The study highlighted a common trend among these AI models: rather than declining to respond when they lacked reliable information, the models frequently provided confabulations—plausible-sounding incorrect or speculative answers. The researchers emphasized that this behavior was consistent across all tested models, not limited to just one tool.
Surprisingly, premium paid versions of these AI search tools fared even worse in certain respects. Perplexity Pro ($20/month) and Grok 3’s premium service ($40/month) confidently delivered incorrect responses more often than their free counterparts. Though these premium models correctly answered a higher number of prompts, their reluctance to decline uncertain responses drove higher overall error rates.
Issues with citations and publisher control
The CJR researchers also uncovered evidence suggesting some AI tools ignored Robot Exclusion Protocol settings, which publishers use to prevent unauthorized access. For example, Perplexity’s free version correctly identified all 10 excerpts from paywalled National Geographic content, despite National Geographic explicitly disallowing Perplexity’s web crawlers.
Google’s venerable 2015 Chromecast attempted to self-destruct earlier this week, upsetting a huge number of people who were still using the decade-old streaming dongles. Google was seemingly caught off guard by the devices glitching out all at the same time, but it promised to address the problem, and it has. Google says it has a fix ready to roll out, and most affected devices should be right as rain in the coming days.
Google is still not confirming the cause of the Chromecast outage, but it was almost certainly the result of a certificate expiring after 10 years. It would seem there was no one keeping an eye on the Chromecast’s ticking time bomb, which isn’t exactly surprising—Google has moved on from the Chromecast brand, focusing instead on the more capable Google TV streamer. Even if Google is done with the Chromecast, its customers aren’t.
If you left your 2015 Chromecast or Chromecast Audio alone to await a fix, you’re in good shape. The update should be delivered automatically to the device soon. “We’ve started rolling out a fix for the problem with Chromecast (2nd gen) and Chromecast Audio devices, which will be completed over the next few days. Users must ensure their device is connected to WiFi to receive the update,” says Google.
Gemini 2.0 is also coming to Deep Research, Google’s AI tool that creates detailed reports on a topic or question. This tool browses the web on your behalf, taking its time to assemble its responses. The new Gemini 2.0-based version will show more of its work as it gathers data, and Google claims the final product will be of higher quality.
You don’t have to take Google’s word on this—you can try it for yourself, even if you don’t pay for advanced AI features. Google is making Deep Research free, but it’s not unlimited. The company says everyone will be able to try Deep Research “a few times a month” at no cost. That’s all the detail we’re getting, so don’t go crazy with Deep Research right away.
Lastly, Google is also rolling out Gems to free accounts. Gems are like custom chatbots you can set up with a specific task in mind. Google has some defaults like Learning Coach and Brainstormer, but you can get creative and make just about anything (within the limits prescribed by Google LLC and applicable laws).
Some of the newly free features require a lot of inference processing, which is not cheap. Making its most expensive models free, even on a limited basis, will undoubtedly increase Google’s AI losses. No one has figured out how to make money on generative AI yet, but Google seems content spending more money to secure market share.
OpenAI is hoping that Donald Trump’s AI Action Plan, due out this July, will settle copyright debates by declaring AI training fair use—paving the way for AI companies’ unfettered access to training data that OpenAI claims is critical to defeat China in the AI race.
Currently, courts are mulling whether AI training is fair use, as rights holders say that AI models trained on creative works threaten to replace them in markets and water down humanity’s creative output overall.
OpenAI is just one AI company fighting with rights holders in several dozen lawsuits, arguing that AI transforms copyrighted works it trains on and alleging that AI outputs aren’t substitutes for original works.
So far, one landmark ruling favored rights holders, with a judge declaring AI training is not fair use, as AI outputs clearly threatened to replace Thomson-Reuters’ legal research firm Westlaw in the market, Wired reported. But OpenAI now appears to be looking to Trump to avoid a similar outcome in its lawsuits, including a major suit brought by The New York Times.
“OpenAI’s models are trained to not replicate works for consumption by the public. Instead, they learn from the works and extract patterns, linguistic structures, and contextual insights,” OpenAI claimed. “This means our AI model training aligns with the core objectives of copyright and the fair use doctrine, using existing works to create something wholly new and different without eroding the commercial value of those existing works.”
Providing “freedom-focused” recommendations on Trump’s plan during a public comment period ending Saturday, OpenAI suggested Thursday that the US should end these court fights by shifting its copyright strategy to promote the AI industry’s “freedom to learn.” Otherwise, the People’s Republic of China (PRC) will likely continue accessing copyrighted data that US companies cannot access, supposedly giving China a leg up “while gaining little in the way of protections for the original IP creators,” OpenAI argued.
Citibank has until March 15 to provide more information on orders to freeze funding. More details on that front were shared today, however, in a court filing in a lawsuit raised by Climate United—one of eight NCIF awardees whose funding was suddenly frozen.
In a motion opposing a request for a temporary restraining order forcing Citibank to unfreeze the funds, Citibank argued that it plays only an administrative role in managing accounts.
According to Citibank, it cannot be liable for freezing the funds because it’s legally required to follow instructions from the EPA and the Department of Treasury, and those agencies ordered Citibank “to pause all further disbursements from GGRF accounts, including those held by Climate United, until further notice.”
Citibank told the US district court that orders came to freeze the funding after “the government informed Citibank that the GGRF program was subject to an ongoing criminal investigation.”
Supposedly, the FBI received “credible information” that Climate United’s Citibank account was “involved in possible criminal violations,” allegedly including conspiracy to defraud the United States and wire fraud, Citibank’s filing said. In a footnote, Citibank said that it also “learned” that the EPA was “deeply” concerned about “matters of financial mismanagement, conflicts of interest, and oversight failures.”
So, freezing the funds was viewed as necessary, the filing alleged, to prevent “misuse of funds.” And Citibank claimed it had no authority to dispute “lawful” orders.
“Citibank is not vested with discretion to second-guess the government’s concerns regarding the ‘misconduct, waste, conflicts of interest, and potential fraud’ that the government has stated is occurring,” Citibank’s filing said.
Climate United, which describes itself as “a public-private investment fund that removes financial barriers to clean technologies,” said in a press release that freezing the funds had already harmed “hard-working Americans who are struggling to pay for groceries and keep the lights on.”
“Small businesses and developers are unable to draw committed funds for project expenses, critical programs are delayed or paused, and Climate United’s reputation as a lender is impacted,” Climate United said, rounding up stories from stakeholders already struggling through the freeze and urging, “this isn’t about politics; it’s about economics.”
The latest claim of a clear quantum supremacy solves a useful problem.
Right now, quantum computers are small and error-prone compared to where they’ll likely be in a few years. Even within those limitations, however, there have been regular claims that the hardware can perform in ways that are impossible to match with classical computation (one of the more recent examples coming just last year). In most cases to date, however, those claims were quickly followed by some tuning and optimization of classical algorithms that boosted their performance, making them competitive once again.
Today, we have a new entry into the claims department—or rather a new claim by an old entry. D-Wave is a company that makes quantum annealers, specialized hardware that is most effective when applied to a class of optimization problems. The new work shows that the hardware can track the behavior of a quantum system called an Ising model far more efficiently than any of the current state-of-the-art classical algorithms.
Knowing what will likely come next, however, the team behind the work writes, “We hope and expect that our results will inspire novel numerical techniques for quantum simulation.”
Real physics vs. simulation
Most of the claims regarding quantum computing superiority have come from general-purpose quantum hardware, like that of IBM and Google. These can solve a wide range of algorithms, but have been limited by the frequency of errors in their qubits. Those errors also turned out to be the reason classical algorithms have often been able to catch up with the claims from the quantum side. They limit the size of the collection of qubits that can be entangled at once, allowing algorithms that focus on interactions among neighboring qubits to perform reasonable simulations of the hardware’s behavior.
In any case, most of these claims have involved quantum computers that weren’t solving any particular algorithm, but rather simply behaving like a quantum computer. Google’s claims, for example, are based around what are called “random quantum circuits,” which is exactly what it sounds like.
Off in its own corner is a company called D-Wave, which makes hardware that relies on quantum effects to perform calculations, but isn’t a general-purpose quantum computer. Instead, its collections of qubits, once configured and initialized, are left to find their way to a ground energy state, which will correspond to a solution to a problem. This approach, called quantum annealing, is best suited to solving problems that involve finding optimal solutions to complex scheduling problems.
D-Wave was likely to have been the first company to experience the “we can outperform classical” followed by an “oh no you can’t” from algorithm developers, and since then it has typically been far more circumspect. In the meantime, a number of companies have put D-Wave’s computers to use on problems that align with where the hardware is most effective.
But on Thursday, D-Wave will release a paper that will once again claim, as its title indicates, “beyond classical computation.” And it will be doing it on a problem that doesn’t involve random circuits.
You sing, Ising
The new paper describes using D-Wave’s hardware to compute the evolution over time of something called an Ising model. A simple version of this model is a two-dimensional grid of objects, each of which can be in two possible states. The state that any one of these objects occupies is influenced by the state of its neighbors. So, it’s easy to put an Ising model into an unstable state, after which values of the objects within it will flip until it reaches a low-energy, stable state. Since this is also a quantum system, however, random noise can sometimes flip bits, so the system will continue to evolve over time. You can also connect the objects into geometries that are far more complicated than a grid, allowing more complex behaviors.
Someone took great notes from a physics lecture on Ising models that explains their behavior and role in physics in more detail. But there are two things you need to know to understand this news. One is that Ising models don’t involve a quantum computer merely acting like an array of qubits—it’s a problem that people have actually tried to find solutions to. The second is that D-Wave’s hardware, which provides a well-connected collection of quantum devices that can flip between two values, is a great match for Ising models.
Back in 2023, D-Wave used its 5,000-qubit annealer to demonstrate that its output when performing Ising model evolution was best described using Schrödinger’s equation, a central way of describing the behavior of quantum systems. And, as quantum systems become increasingly complex, Schrödinger’s equation gets much, much harder to solve using classical hardware—the implication being that modeling the behavior of 5,000 of these qubits could quite possibly be beyond the capacity of classical algorithms.
Still, having been burned before by improvements to classical algorithms, the D-Wave team was very cautious about voicing that implication. As they write in their latest paper, “It remains important to establish that within the parametric range studied, despite the limited correlation length and finite experimental precision, approximate classical methods cannot match the solution quality of the [D-Wave hardware] in a reasonable amount of time.”
So it’s important that they now have a new paper that indicates that classical methods in fact cannot do that in a reasonable amount of time.
Testing alternatives
The team, which is primarily based at D-Wave but includes researchers from a handful of high-level physics institutions from around the world, focused on three different methods of simulating quantum systems on classical hardware. They were put up against a smaller version of what will be D-Wave’s Advantage 2 system, designed to have a higher qubit connectivity and longer coherence times than its current Advantage. The work essentially involved finding where the classical simulators bogged down as either the simulation went on for too long, or the complexity of the Ising model’s geometry got too high (all while showing that D-Wave’s hardware could perform the same calculation).
Three different classical approaches were tested. Two of them involved a tensor network, one called MPS, for matrix product of states, and the second called projected entangled-pair states (PEPS). They also tried a neural network, as a number of these have been trained successfully to predict the output of Schrödinger’s equation for different systems.
These approaches were first tested on a simple 8×8 grid of objects rolled up into a cylinder, which increases the connectivity by eliminating two of the edges. And, for this simple system that evolved over a short period, the classical methods and the quantum hardware produced answers that were effectively indistinguishable.
Two of the classical algorithms, however, were relatively easy to eliminate from serious consideration. The neural network provided good results for short simulations but began to diverge rapidly once the system was allowed to evolve for longer times. And PEPS works by focusing on local entanglement and failed as entanglement was spread to ever-larger systems. That left MPS as the classical representative as more complex geometries were run for longer times.
By identifying where MPS started to fail, the researchers could estimate the amount of classical hardware that would be needed to allow the algorithm to keep pace with the Advantage 2 hardware on the most complex systems. And, well, it’s not going to be realistic any time soon. “On the largest problems, MPS would take millions of years on the Frontier supercomputer per input to match [quantum hardware] quality,” they conclude. “Memory requirements would exceed its 700PB storage, and electricity requirements would exceed annual global consumption.” By contrast, it took a few minutes on D-Wave’s hardware.
Again, in the paper, the researchers acknowledge that this may lead to another round of optimizations that bring classical algorithms back into competition. And, apparently those have already started once a draft of this upcoming paper was placed on the arXiv. At a press conference happening as this report was being prepared, one of D-Wave’s scientists, Andrew King, noted that two pre-prints have already appeared on the arXiv that described improvements to classical algorithms.
While these allow classical simulations to perform more of the results demonstrated in the new paper, they don’t involve simulating the most complicated geometries, and require shorter times and fewer total qubits. Nature talked to one of the people behind these algorithm improvements, who was optimistic that they could eventually replicate all of D-Wave’s results using non-quantum algorithms. D-Wave, obviously, is skeptical. And King said that a new, larger Advantage 2 test chip with over 4,000 qubits available had recently been calibrated, and he had already tested even larger versions of these same Ising models on it—ones that would be considerably harder for classical methods to catch up to.
In any case, the company is acting like things are settled. During the press conference describing the new results, people frequently referred to D-Wave having achieved quantum supremacy, and its CEO, Alan Baratz, in responding to skepticism sparked by the two draft manuscripts, said, “Our work should be celebrated as a significant milestone.”
John is Ars Technica’s science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots.
Meanwhile, the Texas health department on Tuesday provided an outbreak update, raising the case count to 223, up 25 from the 198 Texas cases reported Friday. Of the Texas cases, 29 have been hospitalized and one has died—a 6-year-old girl from Gaines County, the outbreak’s epicenter. The girl was unvaccinated and had no known underlying health conditions.
The outbreak continues to be primarily in unvaccinated children. Of the 223 cases, 76 are in ages 0 to 4, and 98 are between ages 5 and 17. Of the cases, 80 are unvaccinated, 138 lack vaccination status, and five are known to have received at least one dose of the Measles, Mumps, and Rubella vaccine.
One dose of MMR is estimated to be 93 percent effective against measles, and two doses offer 98 percent protection. It’s not unexpected to see a small number of breakthrough cases in large, localized outbreaks.
Across the border from Gaines County in Texas sits Lea County, where New Mexico officials have now documented 32 cases, with an additional case reported in neighboring Eddy County, bringing the state’s current total to 33. Of those cases, one person has been hospitalized and one person (not hospitalized) died. The death was an adult who did not seek medical care and tested positive for measles only after death. The cause of their death is under investigation.
Of New Mexico’s 33 cases, 27 were unvaccinated and five did not have a vaccination status, and one had received at least one MMR dose. Eighteen of the 33 cases are in adults, 13 are ages 0 to 17, and two cases have no confirmed age.
On Friday, the Centers for Disease Control and Prevention released a travel alert over the measles outbreak. “With spring and summer travel season approaching in the United States, CDC emphasizes the important role that clinicians and public health officials play in preventing the spread of measles,” the agency said in the alert. It advised clinicians to be vigilant in identifying potential measles cases.
The agency stressed the importance of vaccination, putting in bold: “Measles-mumps-rubella (MMR) vaccination remains the most important tool for preventing measles,” while saying that “all US residents should be up to date on their MMR vaccinations.”
US health secretary and long-time anti-vaccine advocate Robert F. Kennedy Jr, meanwhile, has been emphasizing cod liver oil, which does not prevent measles, and falsely blaming the outbreak on poor nutrition.
Google has a new mission in the AI era: to add Gemini to as many of the company’s products as possible. We’ve already seen Gemini appear in search results, text messages, and more. In Google’s latest update to Workspace, Gemini will be able to add calendar appointments from Gmail with a single click. Well, assuming Gemini gets it right the first time, which is far from certain.
The new calendar button will appear at the top of emails, right next to the summarize button that arrived last year. The calendar option will show up in Gmail threads with actionable meeting chit-chat, allowing you to mash that button to create an appointment in one step. The Gemini sidebar will open to confirm the appointment was made, which is a good opportunity to double-check the robot. There will be a handy edit button in the Gemini window in the event it makes a mistake. However, the robot can’t invite people to these events yet.
The effect of using the button is the same as opening the Gemini panel and asking it to create an appointment. The new functionality is simply detecting events and offering the button as a shortcut of sorts. You should not expect to see this button appear on messages that already have calendar integration, like dining reservations and flights. Those already pop up in Google Calendar without AI.
