
One of the biggest costs in robots is actuators – but China dominates their manufacture. How can the US catch up? CC-licensed photo by Ricardo Diaz on Flickr.
You can sign up to receive each day’s Start Up post by email. You’ll need to click a confirmation link, so no spam.
A selection of 10 links for you. Klaatu barada nikto. I’m @charlesarthur on Twitter. On Threads: charles_arthur. On Mastodon: https://newsie.social/@charlesarthur. On Bluesky: @charlesarthur.bsky.social. Observations and links welcome.
Inside Microsoft’s Project Solara: a new platform for devices that run AI agents instead of apps • GeekWire
Todd Bishop:
»
A team inside Microsoft has been quietly building a platform for devices that run AI agents instead of apps, based on Android instead of Windows, with two working hardware designs so far, and an initial set of big-name companies lined up to run pilots.
The platform, dubbed “Project Solara,” is Microsoft’s bet that AI will open up entirely new scenarios for computing — using agents to avoid the constraints of traditional software, and off‑the‑shelf components to develop new devices quickly and inexpensively.
Microsoft is racing against Google, Amazon, OpenAI and others to bring AI to devices and provide the technical backbone for a new generation of computing. In effect, the company is attempting to repeat with AI what it did for personal computers five decades ago, with much stiffer competition this time but also far greater technical freedom.
“Boundaries are collapsing,” said Stevie Bathiche, the Microsoft corporate vice president and technical fellow who leads its Applied Sciences Group. “You don’t necessarily need the traditional app model. You don’t need the traditional way of developing experiences.”
The company unveiled Solara on Tuesday at its Build conference in San Francisco, describing it as a new platform that spans from chip to cloud. GeekWire got a behind-the-scenes look at the project during a briefing last week in Redmond, including demos of the first two concept devices based on the platform:
• A desktop hub that sits beside a PC and responds to voice commands, signs users in using facial recognition, and surfaces the day’s most pressing items. With a monitor attached, it becomes a full Windows machine running in the cloud.
• A wearable badge that reimagines the standard employee ID card. A fingerprint button wakes an agent in one press; a single tap records and transcribes a conversation; and a built-in camera lets the agent act on what the user sees.Microsoft says it won’t ship these devices itself. Instead, it envisions hardware makers and other industry partners turning the reference designs into implementations of their own, each intended for a specific industry, company, or scenario.
«
You get all the way to that last paragraph and then, like Lucy pulling the football away from Charlie Brown, you discover that actually, no such thing! This is such a classic Microsoft thing. Someone else will surely do it if they’re encouraging enough.
Also, just what the world needs now: another OS stacked on top of Android.
unique link to this extract
Android phones will soon be able to detect spoofed calls and impersonation scams • Ars Technica
Ryan Whitwam:
»
According to Google, “impersonation fraud” is one of the most common types of financial scams. The FTC tracked almost $3bn in losses from such scams during 2024, and the improvements in AI voice cloning tools more recently are making the schemes easier to pull off. The voice models are becoming so capable that it can be difficult to identify a fake caller even when an AI is imitating someone you talk to every day.
Google’s solution is an expansion of the system it debuted last month for verified financial calls. Now, a similar feature will work with anyone in your contacts. Many of the most effective deepfake scams involve spoofing a contact’s number, which makes the call look more legitimate when your phone lights up. Victims of these scams are then greeted by an accurate re-creation of the person’s voice spinning a yarn that involves an urgent need for cash.
Google’s scam call detection feature will be available on all phones running Android 12 or higher, but it does require you to have three Google apps installed: Phone by Google, Contacts, and Google Messages. Depending on your device, you may already have these. They’re the preloaded options on Pixel and Motorola phones, and Samsung has now switched over fully to Google Messages. Google claims that Phone by Google is the most widely used dialer, but that doesn’t seem right—Samsung has its own phone app, and it’s the largest Android OEM by far.
Regardless, once you have Google’s trio of communication apps, they will work together to verify phone calls that appear to come from a known contact. When scammers want to impersonate a contact, they use an online relay to spoof the number. When a call comes in, the caller’s Google dialer app sends a confirmation signal that is missing in spoofed relay calls. If that signal is absent, your phone uses the Messages app to send an authenticated RCS ping (hence the Google Messages requirement) to the supposed caller. If their phone reports it’s not placing the call, a pop-up will alert you that the person on the line may not be who you think they are.
«
That’s fab–
»
There’s one more notable caveat you may have noticed. Because the system contacts the other party’s phone for verification, that person must also have the same three Google apps installed. If a caller is using the Samsung dialer or the OnePlus contacts app, Google’s scam detection won’t work.
«
Well that’s stupid. In the US particularly, the chances of a contact owning an iPhone are extremely high, so this is going to fail. But won’t an RCS ping work on iPhones? It seems like this should be something that could be figured out.
unique link to this extract
This is why America can’t have robots and other nice things • Core Memory
Kylie Robison:
»
What is an actuator? …It’s part of a machine that turns energy — electric, hydraulic, pneumatic — into motion. An electric actuator, which is the one we care the most about here, is usually a package of three things: a motor (the thing that spins), control electronics (that tell it how fast and how hard), and gearing (that trades speed for torque so it can push or hold weight). Actuators can move in a straight line or in a circular motion, known as linear or rotary, respectively.
What makes them so special is their broad use in manufacturing things like a plane’s landing gear, sewing machines, your car’s seat adjusters. Just about every machine that moves is thanks to an actuator. I will repeat: these parts are largely manufactured in China.
China’s dominance in actuator manufacturing traces back to two industrial markets that happen to need the same part. The first is drones, which use motors in their propellers. One report estimates Chinese companies “control 90% of the consumer drone market, 70% or more of the enterprise market, and 92% of the state and local first responder market.” (I previously wrote about a startup working to revive the U.S. drone industry.)
The other, bigger one is electric vehicles. China’s rush to go all-in on electric vehicles gave it exactly the industrial stack that motion-based hardware runs on: batteries, power electronics, sensors, precision motors, and the rare-earth magnets that sit at the heart of any electric motor. Tens of millions of EVs later, China controls both the assembly and the whole supply chain beneath it, down to the magnet processing. Chinese automakers produced roughly 60% of all electric cars sold worldwide in 2025.
There is a blossoming third industry here: robotics. China accounted for nearly 90% of the humanoid market last year. It’s still a really tiny market, with somewhere between 13,000 and 18,000 humanoids sold around the world in 2025. But those robots require a load of actuators, which eat up between 40% to 60% of the cost of a building one.
…The real barrier that has held the U.S. back from motor and actuator glory is cost. The Chinese-style designs are optimized for things that are cheap in China and expensive here. [Westmag founder David] Hansen holds up a motor part machined from a solid block of aluminum. In China, he says, that costs about as much as the raw block — the labor rounds to nothing. “Go ask [SendCutSend CEO] Jim Belosic to do that. It’s very expensive to do,” he adds. (Belosic also invested in Westmag, and SendCutSend sponsors Core Memory).
Westmag’s gamble is that the expense is only temporary — a function of low volume, not American inadequacy. Hansen’s argument runs like this: at a big enough scale, the cost of almost anything drifts down toward the cost of its raw materials, the steel, the copper, the magnets, and the labor premium that makes a single American-made part pricey shrinks toward nothing. “You can reach efficiencies of scale with almost any widget once there’s enough of them,” he says.
«
How lawyers tried to evade AI analysis of court documents • Linkedin
Jin Yoshikawa:
»
I came across one of the first real-world examples of a court sanctioning lawyers for prompt injection in a filing.
In a Brazilian labour-court judgment, the court found that a petition included hidden white-on-white text, invisible to a reader, directed at any AI system processing the document. The hidden instruction told the AI to contest the petition only superficially and not challenge the documents, regardless of the command it was later given.
The court discovered the prompt injection and characterized the conduct as an attempted manipulation of the court’s AI system. The court deemed it an act “offensive to the dignity of justice.” The lawyers who signed the filing were sanctioned with a fine of 10% of the case value, and the matter was referred to the bar and court authorities.
This is exactly the risk I flagged earlier this year. Lawyers are increasingly using AI to summarize pleadings, triage discovery, analyze briefs, and draft responses. But every document from an adversary is untrusted input. Hidden text, metadata, or buried instructions can be designed to influence a model into missing issues, downplaying arguments, or producing biased output.
I suspect we will see more attempts like this, especially from unscrupulous lawyers or pro se litigants who realize that AI tools are now in the litigation workflow. In the US, this kind of deception would be difficult to square with professional responsibility rules, candour obligations, and duties of fairness to opposing counsel and the tribunal.
«
Mind over antibody • For Better Science
Sholto David:
»
Antibodies are frequently used to investigate protein expression by western blot or immunostaining because of the specificity of their binding. Abcam is a major supplier of antibodies, and if you go to their website today and search for a “p16” specific antibody a list of potential choices is offered, importantly for this story a p16-ARC antibody is the first search result, the product code is “ab51243”. There is also another less frequently cited p16-ARC antibody “ab151303”. Similarly, if you head over to Santa Cruz (another supplier) you can find a p16-ARC antibody with the product code “sc-166760”. I think most people can guess where this is leading… How many researchers have muddled these two proteins and mistakenly ordered an antibody that binds p16-ARC when trying to investigate the expression of p16-INK4a?
I decided to check, searching for the “ab51243”, “ab151303”, and “sc-166760” product codes in Google Scholar I found over 400 unique research papers mentioning at least one of these p16-ARC antibodies (after removing duplicates, false positives, preprints, and dead links). Of these papers I could access the full text of 334, with the remaining 72 articles being paywalled. I reviewed each accessible paper to determine whether the antibody used in the paper was correctly intended for p16-ARC or incorrectly used to try and bind p16-INK4a
Here is the astonishing result: 95% of these papers have got it wrong. The vast majority of researchers who purchased either ab51243, ab151303, or sc-166760 have tried to use these antibodies to investigate p16-INK4a expression! Only seventeen used these p16-ARC antibodies correctly.
«
p16 is a critical tumour suppressor and cell cycle regulator protein in the body, so these mistakes matter. And show that it’s incredibly easy to go wrong at the very first step. Which means chunks of scientific work are wrong. Who fixes that?
unique link to this extract
Norse Atlantic Airways offers dirt-cheap tickets. There’s a catch • WIRED
Caroline Haskins:
»
On March 31, I received an email from Norse Atlantic Airways. The $940 flights for my upcoming round trip to Rome had been cancelled, it said, and I had 14 days to request a refund.
At first, I didn’t panic. That began to change when the company’s refund request page wouldn’t load on two browsers across three devices. After Norse didn’t respond to several emails, I looked for a phone number. There wasn’t one. On Reddit, I found dozens of posts about Norse’s allegedly haphazard customer service.
The same day, I filed a public records request with the Federal Trade Commission, which I hoped would give me a better idea of how common this experience was. I eventually received around 75 detailed complaints from people who had bought or tried to buy tickets from the airline. Many described a customer service operation in which the inability to get in touch with a human created a vacuum that scammers appeared happy to step into. Of the 41 complaints that reported a dollar figure, 21 claimed they lost more than $1,000.
Norse Atlantic Airways does have human customer service workers, but in recent years, the airline has leaned into a tech-forward approach, deploying AI agents to help power its operation.
“Technology will help us have a higher level of availability and customer support, while still maintaining low fares for more people to enjoy travel between continents,” Bård Nordhagen, the company’s chief customer and communications officer, tells WIRED.
…At the time of writing, a Google search for the “Norse Atlantic airways phone number” returned links to three Yelp pages, which listed two different phone numbers. Both of these appear to be scams.
When WIRED called the first number, a man claimed to be a representative of Star Alliance, a network of 26 airlines. However, Star Alliance’s website doesn’t list Norse Atlantic Airways among its affiliated airlines, and it doesn’t include the phone number. (A representative for Star Alliance confirmed that the number isn’t associated with the company, and said Norse isn’t one of its members.)
When WIRED called the second number, a different man said he was a representative of “Flight Travel Portal,” a service that does not appear to exist. When WIRED asked the man about online posts that claimed his phone number was a scam, he sounded unfazed. People online can say anything, he offered.
«
So basically because Norse Atlantic has tried to cut humans out of customer service, its passengers are now vulnerable to human scammers. Sound familiar?
unique link to this extract
Amazon scraps AI leaderboard to stop workers chasing usage scores • Financial Times
Rafe Rosner-Uddin:
»
Amazon has shut down an internal leaderboard that tracked employees’ use of AI tools after workers tried to boost their scores with unnecessary activity that increased the company’s computing costs.
Employees at the $2.9tn group were told this week its “Kirorank” service — which scored users of Amazon’s Kiro developer platform based on their AI activity — had been taken offline, according to two people familiar with the matter.
The decision came after the tool led some workers to assign AI agents — autonomous bots that can take actions on behalf of users — to carry out needless tasks in an apparent attempt to climb the rankings.
Dave Treadwell, an Amazon senior vice-president, told staff earlier this week that the leaderboard had been built with “good intentions”, according to people familiar with his remarks.
But he added that the result had been additional costs for Amazon due to employees “tokenmaxxing” or inflating their consumption of AI tokens — units of data processed by models.
“Please don’t use AI just for the sake of using AI,” he told staff.
«
Absolutely classic example of Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.”
unique link to this extract
The structural barriers to AI lawyers • Diffuse AI
Sean Harrington:
»
Legal AI has a data problem that most industries don’t face, and it has two layers.
The first layer is raw legal data. To build useful AI for legal research, you need comprehensive databases of case law, statutes, regulations, and secondary materials. Only three entities in the United States have anything approaching complete coverage: Westlaw (Thomson Reuters), Lexis (RELX), and vLex/Fastcase, which Clio acquired in a $1 billion deal in November 2025. That deal pulled the third meaningful legal research database under a company focused on small and mid-size firm practice management, and Clio’s $5 billion valuation and $500 million Series G round suggest investors see the strategic value of owning one of only three complete legal datasets in the country. Everyone else either licenses from one of these three or works with incomplete data.
The second layer is what makes those databases worth paying for. Westlaw and Lexis don’t sell raw judicial opinions (much of that is publicly available). They sell the editorial infrastructure built on top: headnote taxonomies that organize millions of opinions into searchable categories, practice guides written by specialists over decades, and treatises that synthesize primary law into usable guidance. A California real estate attorney without access to Miller and Starr would be at a serious disadvantage, not because the underlying case law is hidden, but because navigating it without an expert-curated roadmap takes exponentially longer. Imagine being handed an encyclopedia to learn something vs. having a beautifully curated twenty-page guide from a panel of practitioners who have been through the procedure a thousand times. That’s the difference: substantive knowledge plus procedural shorthand, built up over years of practice in a single area of law.
…The data moat is real, but it may be more porous than it appears.
The Free Law Project’s CourtListener provides free access to millions of federal and state court opinions, oral arguments, and PACER documents. State-level open data initiatives, like Oklahoma’s, have made primary legal materials freely accessible. Harvard’s Caselaw Access Project digitized every official state and federal case through 2020. All U.S. state bar associations now provide members with free access to either vLex Fastcase or Decisis, which, for a solo practitioner handling state court matters, might be enough.
The editorial layer that was essential for human researchers may matter less for AI systems. vLex’s Vincent AI demonstrates a different approach: using AI to generate the synthesis layer rather than paying human experts to write it.
…The barriers inside most law firms are organisational, not technical. Even firms that want AI can’t deploy it because their data is a mess and their governance structures punish change.
«
Organisation as the barrier is entirely predictable.
unique link to this extract
US Oil Buffer Stress Monitor
Michael Puscar:
»
The simple estimate extends the latest four-week commercial crude draw rate toward the modern low-water mark. It is not a physical tank-bottom estimate. If inventories build instead of draw, no low-water retest is projected. Oil prices can react before or after physical stress appears, so the pressure window is a risk signal rather than a prediction.
«
Currently at 75 days to the “modern low-water mark”. The “upward price pressure window” would start around August 5th.
Developed by Puscar using the APIs from the US Strategic Petroleum Reserve (SPR). So the next thing to expect on past form is that the API will be shut off when things get tight, as happened with US labour statistics as the jobs market plummeted.
unique link to this extract
Arsenal v PSG got 16.2m illegal stream views in UK after not being free-to-air • The Guardian
Matt Hughes:
»
Arsenal’s Champions League final defeat by Paris Saint-Germain attracted more than 16.2 million views on illegal streams in the UK after not being made free to air.
Analysis conducted for the Guardian by the technology analyst Gaming Compliance International (GCI) shows there were 16.2m illegal stream views of longer than 90 seconds, traced to 3.7m unique IP addresses. The final was watched legally on TNT Sports and HBO Max by more than 7 million people.
TNT sparked a political row with its controversial decision not to make the final available free to air for the first time since the tournament’s rebrand as the Champions League in 1992, with Sir Keir Starmer writing to the broadcaster urging it to reconsider.
TNT is understood to have been happy with its combined linear and streaming viewing figures of more than 7m and 25.6% audience share, but the large numbers who watched illegally will be a major long‑term concern for it and all broadcasters, as well as for TV rights owners such as Uefa and the Premier League.
…The exact size of the illegal audience is impossible to discern because there is likely to have been more than one viewer for many of the 3.7m unique streams, and some viewers will have accessed more than one stream owing to technological problems and forced refreshing because of advertising, which explains the 16.2m figure.
There is a large overlap between the piracy of premium sports rights and unlicensed gambling, highlighted by the fact that 89% of adverts on illegal streams of the Champions League final were for gambling brands not licensed in the UK.
«
Not explained where the illegal streams originate from, but the gambling link carries its own hint. But also: sports remains the area where you can absolutely charge money and get a lot of people to sign up at once.
unique link to this extract
| • Why do social networks drive us a little mad? • Why does angry content seem to dominate what we see? • How much of a role do algorithms play in affecting what we see and do online? • What can we do about it? • Did Facebook have any inkling of what was coming in Myanmar in 2016? Read Social Warming, my latest book, and find answers – and more. |
Errata, corrigenda and ai no corrida: none notified








