Non-Technological Constraints to AI

Market manias have patterns. The most powerful ones are genuine technological revolutions pushed far beyond rational limits by crowd psychology.

By mid-1999 it was already clear to veteran investors and students of economic history that the dotcom bubble had reached parabolic insanity.

The speculative momentum was still unstoppable – and would run a lot further – but grown-ups knew by then that few of the high-flying start-ups were ever going to generate a viable revenue stream. The authentic success stories would have to fight each other in a cannibalistic struggle for survival.

We are nearing the same point today with AI, although this time for a different and overwhelming reason. The $20tn (£15tn) valuation of hyperscalers, chipmakers and the larger AI complex, has wildly outpaced the electrical infrastructure needed to run data centres and sustain the technology on anything like the projected scale.

The physical constraint is rock hard. “Our grid in the United States hasn’t had any meaningful upgrade since the 1970s,” said Bobby Majumder from the industrial law firm FBT Gibbons.

The threat to AI stock mania is not so much lack of energy – though that is serious – but rather the global bottleneck of transformers, substations, switchgear, transmission lines and all the unsexy stuff we rarely think about, leaving aside the acute shortage of skilled workers in the US able to install and run such kit.

A single big campus in the data centre hub of Hays County, Texas – an area where I once played a lot of golf (misspent youth) and know well – can use 10 million gallons of water a day for evaporative cooling and power generation, draining the Edwards Aquifer that also supplies the Austin-San Antonio corridor.

“Nobody is talking about cooling; nobody is talking about water,” said Majumder, speaking at the recent Marshall & Stevens forum on energy infrastructure. “The farmers are not going to be happy at all about you pumping down their aquifer for cooling.”

There are other obvious catalysts that could puncture the bubble. Stubborn US inflation – input prices are rising at the fastest pace in four years – may force the Federal Reserve to stop its “stealth-QE” via bill purchases. The bond markets may hold Kevin Warsh’s feet to the fire as he takes over the institution.

Inflation may stop Scott Bessent, the poacher turned gamekeeper now running the US treasury like a hedge fund, from using the $8tn money market to help soak up massive fiscal deficits at the peak of the economic cycle.

Cheaper “commoditised” AI from the likes of DeepSeek in China may start to undercut American rivals, threatening the implicit pricing model behind today’s equity valuations. If it is true that DeepSeek v4 can achieve 80pc-90pc of the performance of Anthropic’s Claude at 10pc of the cost, you start to see the problem.

Liaquat Ahamed, author of the wonderful Lords of Finance covering the Great Depression and now releasing his new book 1873, likens the AI boom to the American railway mania after the Civil War. Routes were duplicated in the rush for dominance.

Costly lines passed through sparsely inhabited regions where there would never be enough human traffic in time to justify the scale of debt issuance. [...]

Hyperscalers can try to leapfrog the grid bottleneck by building their own power plants, but that will not solve the problem either, at least not in time to alleviate the burden of fast-mounting and opaque AI debt.

It took 17 years to plan, license and build the recent Vogtle nuclear plant in Georgia. Costs ballooned from $12bn to $30bn. Small modular reactors may be cheaper per gigawatt – don’t hold your breath – but none yet exist in the West, and there will be no serious supply chain until circa 2040.

Shale gas frackers can drill until they drop, but that makes no difference if there are no gas turbines available on the world market. The waiting list for heavy-duty models used in combined-cycle plants has stretched to seven years, although hyperscalers with the deepest pockets are jumping the queue for a fat fee with 2030 delivery dates. [...]

The AI revolution is real. The language models are fabulous. The technology will make economic life almost unrecognisable by mid-century.

But the internet revolution was also real in 1999 before the Nasdaq index dropped 77pc, flushed out the commercial nonsense and overshot in the other direction.

Don’t track Nvidia chip orders if you want to know where the AI market is heading. Track the metaphorical picks and shovels that make it all possible. 

by Ambrose Evans-Pritchard, The Telegraph | Read more:
Image: Richard Newstead
[ed. See also: How bad is AI for the environment? (Yale Climate Connections).]

The Licensing Revolution: Is Resistance Futile? Part 1: Loss of Ownership Comes to the Car

“Neoliberalism as an economic system enshrines the extraction of rent over industrial production.”
—Yours truly, here

Two of the most revolutionary inventions man ever made were created in the 20th century, one at its start and the other close to the end. Both offered the same innovation: a quantum advance in individual freedom and power.

I’m talking, of course, about the automobile, personal transportation, and the PC, your own personal computer.

Cars and Computers

If you own a car, you own your own transportation; you don’t rent it or borrow it. You can argue the merits of “owning” personal transportation — there are climate, pollution, and crowding arguments against — but there’s no question about the freedom it gives to people. You want to leave now? Just jump in the car and go.

If you own a PC, same thing. Before the PC, some calculations and modeling were just too painful and time-consuming to do, and many were simply impossible. Think of the most complicated spreadsheet you’ve ever created — could you have done that by hand? Or better, if you could have done it by hand, would you have?

Before the PC and its business equivalent, the UNIX-based Sun Workstation, access to computing power were through IBM-style mainframes and minicomputers, like those made by DEC. None of these could be considered “personal”; they were too costly, and though they could accommodate multiple users at terminals, the computing itself was centralized and corporate-owned.

Keep this in mind: Before the PC, computing was centralized and corporate-owned. After the PC, computing power was inside the box you worked at, and priced for individual sale. Now thanks to Windows 11, that’s all been reversed.

Cars and computers, each a revolution in personal power and control. Now both will be taken away. Your car will no longer be yours, nor will your PC.

Soon You Won’t Own Your Car

The above statement is true in too many ways. The car you’ve already bought will be licensed to you, a license that can be revoked.

Your New Car Is a Spy

Cars have become computers over the last few years. And that means cars have become spy machines. Here’s one review, by the Mozilla Foundation, of the automobile industry from the standpoint of privacy, written in 2023. Its bottom line is the headline:

It’s Official: Cars Are the Worst Product Category We Have Ever Reviewed for Privacy

All 25 car brands we researched earned our *Privacy Not Included warning label -- making cars the official worst category of products for privacy that we have ever reviewed.

The link for individual brand reviews is here. Their sins are many; these are the important ones:

1. They collect too much personal data (all of them)
2. Most (84%) share or sell your data
3. Most (92%) give drivers little to no control over their personal data
4. We couldn’t confirm whether any of them meet our Minimum Security Standards

Recipients of the sale of your data could include your insurance company, which can purchase everything recorded about your driving habits.

And you can’t shut this stuff off, because it’s not hardware, but software, and the car needs its software to run. Here’s Tesla’s warning about its software, again from 2023 (emphasis mine):

However, “if you no longer wish for us to collect vehicle data or any other data from your Tesla vehicle, please contact us to deactivate connectivity. Please note, certain advanced features such as over-the-air updates, remote services, and interactivity with mobile applications and in-car features such as location search, Internet radio, voice commands, and web browser functionality rely on such connectivity. If you choose to opt out of vehicle data collection (with the exception of in-car Data Sharing preferences), we will not be able to know or notify you of issues applicable to your vehicle in real time. This may result in your vehicle suffering from reduced functionality, serious damage, or inoperability.”

It’s gotten worse since then; Tesla’s just getting started.

The Biden Bill–Mandated ‘Kill Switch’

Watch the Breaking Points video at the top; it details, from reputable reporters, the next dystopian “feature” of cars manufactured in 2027 and later — a “kill switch” that turns your car off if it thinks you shouldn’t be driving.

The detail is here. Basically, under Joe Biden, Section 24220 of the Infrastructure Investment and Jobs Act “requires all new passenger vehicles to eventually include factory-installed technology that detects driver impairment and prevents or limits vehicle operation.”

The implementation falls under the NHTSA, which is writing the rule. Barring congressional prevention or modification, the kill switch is expected appear in all newly manufactured cars (but not used ones) starting in late 2026 or early 2027.

Privacy and Control

In modern America, two things are certainly true. 1) Once privacy is taken away, it never comes back; and 2) when a power is gained by corporations and government, they pervert it as fast as they can.

The prime example is this war — because Congress long ago surrendered its war-making power, the Executive has steadily moved in, to the point that today there’s not even a pretense of getting congressional permission. Trump wants a war wherever, that’s what he does. Or consider the definition of “terrorist” — today it’s “whomever the feds wishes to hurt, and to whatever extent.”

So what’s the maximum harm that can be done by the “new automobile”? Your driving is monitored by AI; the data is fine-grained and stored; anyone who wants it can buy it for whatever goal, including to raise your insurance, or deny you coverage.

Further, anyone with control of the software — the manufacturer, the FBI (initially under subpoena, but later, who knows?), cops, Homeland Security, or any branch of the law, whatever that means — can turn off your car when it wants, or (why not?) gain full control, lock you in, and drive you wherever it wishes. Remember, eventually every new power is perverted.

It starts, as always, with calls to Save the Children (MADD is mad for this law).

The next expansion is to further the War Against Crime. (“Remember the OJ Simpson highway chase? What if they could just turn off the car? You want to catch OJ, right? Do you hate the cops?”)

Then it transforms into … what? Whatever the security state wants, because “keeping you safe.”

The Licensing Revolution

You won’t own your car for another reason as well. You may have noticed a trend: what you used to be able to buy, you now merely rent.

• Apple doesn’t sell music, it licenses use.

• You no longer own your software. TurboTax, for example, sells a “personal, limited, nonexclusive, nontransferable, revocable license to use the applicable Software only for the period of use provided in the ordering and activation terms”.

• Same with Amazon’s ebooks and audiobooks.

• Same with Microsoft Windows. (More on that later.)

Non-transferable and revokable licenses. Renting your life.

by Thomas Neuberger, God's Spies |  Read more:

Images: uncredited; and Branimir Kvartuc/ZUMAPRESS.com/Corbis

[ed. In fact, Sony just made news the other day about remotely deleting all previously purchased content in digital libraries, and a couple days later ditching physical disks in favor of licensing. Amazon has already made this transition with Amazon Prime videos. See also: The Licensing Revolution: Windows Edition. Part 2: The computer you bought isn't yours. A tale about power.]

***

"Words have meaning. Proper word selection is integral to strong communication, whether it’s about relaying one’s feelings to another or explaining the terms of a deal, agreement, or transaction.

Language can be confusing, but typically when something is available to “buy,” ownership of that good or access to that service is offered in exchange for money. That’s not really the case, though, when it comes to digital content.

Often, streaming services like Amazon Prime Video offer customers the options to “rent” digital content for a few days or to “buy” it. Some might think that picking “buy” means that they can view the content indefinitely. But these purchases are really just long-term licenses to watch the content for as long as the streaming service has the right to distribute it—which could be for years, months, or days after the transaction." via:

The Billion Dollar Crypto Man

President Donald Trump took in nearly $1.2 billion dollars from his crypto businesses last year, a federal filing released Tuesday shows, locking in profits while his investors were socked with losses.

Mere startups when he took the oath of office, the new ventures have now eclipsed in revenue much of his vast property portfolio that took him decades to accumulate. Fueling their rise were billionaire investors and Trump’s own move to quash a federal crackdown on the industry.

Trump got more than $500 million from his World Liberty Financial business selling new crypto products, including “governance tokens,” according to the required annual disclosure report with the Office of Government Ethics. It also showed another crypto business, CIC Digital LLC, took in more than $600 million from sales of souvenir-type “meme” coins stamped with his face.

Both the tokens and the coins have plunged in value since the sales.

Trump also took in millions last year from selling Trump-branded bibles, sneakers and other small items in another unprecedented move for the presidency. The sale of Trump-branded watches alone brought in $4.7 million.

The 927-page disclosure form paints a stark, if incomplete picture of the massive growth of the president’s wealth since taking office last January through a web of business interests — many that have benefited from the policy moves of Trump’s own government. Trump has insisted that his sons direct his finances but the arrangement rejects the conflict of interest protections that his recent predecessors in office had instituted.

Forbes estimates Trump’s net worth at $6 billion, up from $2.3 billion in 2024.

The Trump business is growing abroad

The rise of crypto relative to Trump’s property is especially noteworthy because he first rode to office boasting of his property wins. It’s also remarkable because that mainstay business also boomed last year. Trump took in tens of millions in fees from a flurry of new hotel, resort and condo deals overseas that amounts to the biggest property expansion ever in the century since the family business was founded.

Many of those countries were negotiating with the U.S. over tariffs, military aid, and other important matters.

A property in the United Arab Emirates took in $10.4 million. One in Saudi Arabia being built by a real estate developer close to the ruling family sent the president’s company $9 million. And one in Bucharest, Romania, and another in Qatar sent him $5 million each.

One of his prominent domestic properties, Mar-a-Lago in Florida, notched big growth last year, too.

Trump took in in $77 million from the property, a 50% jump from the year earlier when he was just another citizen, as heads of state and business people flocked to it in his new term.

The disclosure report doesn’t give profit figures, just revenue, so it’s impossible to know how much he is earning.

Trump is now the billion dollar crypto man

After taking office last year, Trump reversed the Biden administration’s tough stance on the crypto industry and pushed policies friendly to the industry.

But regulators still had some concerns. Before Trump’s World Liberty began selling “governance tokens,” they issued warnings about this new kind of crypto asset, saying that unlike stocks, the tokens offer no ownership stake in the issuing company, just voting power on certain corporate polices, and are difficult to value.

Buyers pounced anyway, including a Chinese billionaire who spent $75 million on the tokens and $200 million on the souvenir coins. In February last year, a federal lawsuit charging him with duping investors was paused before being settled last month for a $10 million fine. [...]

Meanwhile, investors have seen the value of their meme coin holdings drop significantly. The price spiked to more than $74 in the days after its launch in January 2025, but now sells for just $1.68. Also, the value of the World Liberty tokens has fallen 80% since they first started trading in September.

by Bernard Condon, Seattle Times/AP |  Read more:

Image: Alex Brandon
[ed. This actually plays like a feel-good story. The sheep MAGA cultists and influence buyers get fleeced - as predicted, as they deserve (Under the Trump crypto playbook, the family always wins. Investors don’t). Is this a great country or what? In other corruption news, see also: Trump is using a $500M no-bid contract to build his White House ballroom (Washington Post):]

***

White House officials last year secretly awarded a no-bid contract worth up to $500 million for the construction of the East Wing ballroom in an unusual arrangement that sidestepped typical contracting procedures designed to control costs, according to a copy of the agreement obtained by The Washington Post. [...]

The estimated East Wing construction cost has tripled since July, when the project was first announced, with half expected to come from taxpayers, The Post previously reported.

Trump has repeatedly claimed that the ballroom would be paid for by private donors and once said that Clark executives offered to build it for free.

“They said: ‘Sir, we’ll do it for nothing. This is the greatest honor,” Trump told The New York Times in January.

Clark’s internal cost projections show the McLean, Virginia-based company, the largest general contractor in the D.C. metro area, stands to make tens of millions of dollars from the work...

The records reviewed by The Post do not break out Clark’s estimated profit margin for the entire project, but a March document shows the company projected it would receive a total of $65 million in combined profit, overhead and daily rates for on-site staff and other costs.

[ed. But, but... Hilary's emails!]

Asteroid Day, June 30, 2026

Asteroid Day, June 30, 2026

Asteroid Day was cofounded in 2014 (the year after the 2013 Chelyabinsk meteor air burst) by physicist Stephen Hawking, B612 Foundation president Danica Remy, Apollo 9 astronaut Rusty Schweickart, filmmaker Grigorij Richters, and Brian May (Queen guitarist and astrophysicist). Remy, Schweickart, Richters, and May initiated Asteroid Day in October 2014, which they announced during a press conference. It was launched on December 3, 2014.

In 2016, the United Nations proclaimed Asteroid Day be observed globally on June 30 every year in its resolution. The event aims to raise awareness about asteroids and what can be done to protect the Earth, its families, communities, and future generations from a catastrophic event. - Wikipedia

See also: Asteroid Day 2026: What Is It and How to Celebrate It?

There are about a million asteroids in the Solar System with the potential to strike Earth and destroy a city. Astronomers have discovered only 1% of them. Asteroid Day is an effort to educate the public and encourage policy makers to fund this important effort.

King Tut may have celebrated an ancient Asteroid Day by asking his assistants to make a dagger out of a broken-off asteroid that landed on Earth. Astronomers discovered that the blade of the knife contained much more nickel than is found in terrestrial iron, an amount consistent with iron meteorites, especially with one found in the year 2000 in the Kharga region in northern Egypt. For more information about the dagger, go to http://goo.gl/BHBivd. (via: Bruce Palmquist, Daily Record)

[ed. Brian May was also an astrophysicist? Wow. A man of many talents. Another one would be Jeff "Skunk" Baxter, guitarist for Steely Dan and US missile defense contractor/consultant.]

We Were Promised Sex Robots

Neil McArthur was sure we'd have sex robots by now. The University of Manitoba philosophy professor has spent over a decade studying sex tech. In 2019, when he went to the AVN Adult Entertainment Expo, the industry's largest annual conference, he saw robots with tough, tire-like skin that couldn't walk and spoke more jaggedly than early versions of Siri. When he returned in 2024, well into the LLM boom, he thought, "Things have to have come a long way."

They hadn't. The robots' skin and speech were still unrealistic, and they couldn't move around the conference floor. What was new, though, were several Chinese companies had arrived. (Their founders were invariably young men; one was so young his mom was there, hovering in the background, McArthur says.) As with AI, electric vehicles, and several other tech sectors, China's entrance into the sex robots market had knocked down the price point. Whereas American-made sex robots from the 2010s hype cycle typically started at around $7,000 and quickly exceeded $10,000, some Chinese manufacturers sell sex robots at around $3,000. "The technology had gotten cheaper, but not better," McArthur says.

Several of the Chinese sex doll producers I reached out to did not respond to emails, including VMDoll and IronTech. Others seemed to have AI bots operating their WhatsApp messages. Eventually, I reached Stella Lau, a sales director for Jiggly Joy, a doll manufacturer based in Guangdong province with 160 employees. Lau, 32, has worked for Jiggly Joy for seven years, long before the company released its first AI robot in February.

Jiggly Joy's new model has all the classic features of a sex robot — Lau is one of many merchants who hyped up the "sucking vagina," a suction-and-release pump system — plus it could smile, talk, and wave. It also has a blonde bombshell haircut and can turn its neck like M3GAN. The robot still cannot walk, but that's mostly for safety reasons, Lau says; she's too heavy. The company has been selling about 21 AI dolls a month at $3,000, Lau says. Most of the buyers are American; they're either former sex doll users or lonely and wanted someone to talk to, Lau says.

I also reached a representative for Formosa Doll, a 5-person Hong Kong-based distributor that works exclusively with Chinese sex doll companies. (He asked for anonymity to protect his privacy.) He says AI sex robots are "underdeveloped" and not ready for sale. For one, some doll head prototypes removed the oral sucking motors from the mouth to make space for the AI voice. Trading sucking for talking, he says, is a "big downside."

Voice AI can also be unpredictable and unruly, and sex doll users may be used to making up role-play scenarios in their heads — scenarios they have full control over. That makes him skeptical that AI robots would sell well. "People want an experience, they want to satisfy a fantasy," he says. "People don't want something at home that talks."

The Western market, meanwhile, has mostly flattened out. I tried to contact four of the sex doll makers featured in articles in the 2010s hype cycle. My emails bounced, and my calls went to disconnected numbers.

The only company remaining from the late 2010s appears to be RealDoll, which is now spinning off from the publicly traded Realbotix. The independent RealDoll will be led by Sue Ennis, who started as president of Realbotix the day before our chat. She has big plans, repeating four times that the company would be the "Apple store of intimacy technology."

The robots are built and selling; RealDoll was shipping out 12 as we speak, Ennis tells me. (It's generally a low-revenue business: Realbotix, whose humanoids are also used in healthcare and corporate training settings, reported $353,037 in Q1 earnings.) They have AI voices, AI vaginas, and proprietary skin technology that's also sold to burn victims. Still, the dolls remain very heavy and lack mobility. Some customers take their dolls out on dates. "The dolls are definitely not walking into the theater," Ennis says. "They're being wheeled in."

If the sex robot revolution does happen, it may spread through specialization.

Most of the current AI robots look the same: blonde, skinny, hourglass-shaped. The sex doll underclass is growing more diverse, though. Elves were popular at Formosa Doll, as was Judy Hopps from the "Zootopia" movies. "Goblin dolls are a really hot trend now," Formosa's rep tells me. Consumers don't want generic sexbots; they want their sexbot.

Porn stars are an easy way in. Fans spend thousands in tips to their favorite OnlyFans models. Some are finding that they're willing to spend even more to see them in the (artificial) flesh. Cliff Jensen, a 37-year-old award-winning porn star and OnlyFans model, says his fans want to date him, to prank their friends with him, and to make him take it up the bum. "They've always wanted me to bottom, and I never have," he says.

I meet Jensen at his rep's apartment in Silver Lake, California. We sit side-by-side on the couch, a clutter-filled table with joints and doughnuts in front of us. The big chair is reserved for his sex doll doppelgänger, which he heaved in from his trunk. Jensen is upset; the previous owner, it seemed, had stuffed the sex doll in a closet and piled things on top. The doll retained some head scratches and a mild case of pink eye.

Jensen has worked with the Chinese company IronTech for over 3 years, during which the doll has undergone many evolutions. He performed a 3D body scan for the first iteration, but they couldn't scan his penis. When he saw the doll in-person, he ripped its too-small penis off clean. "It's bad for my brand," he says. He keeps that early, poorly sized phallus as a keepsake.

Yes, Jensen has had sex with himself. It was in an orgy scene, and he found it hilarious. After that scene, Jensen accidentally dropped the doll down a flight of stairs, damaging it beyond repair. He threw the doll in the dumpster, but a hairy elbow peeked out of the trash bag. A neighbor called the cops, thinking it was a corpse. The cops were delighted, he says. "They've seen sex dolls before, but they're those cheap, smaller ones that are washed up on the shore," he says. "They're like, 'Dude, this is gold.'"

Indeed, Jensen's doll didn't look cheap at all. I feel the skin and the hair, which are hauntingly realistic. I hold the breathtakingly large penis in my hand, and it feels like a breathtakingly large penis. Jensen has dozens of ideas to keep improving it: an opening in the lips so you could kiss it, a kit of different penis sizes for those who cannot take his full member, and an AI voice. His primary goal, though, is weight reduction: the current model is at least 140 pounds. He has to haul it over his shoulder to move it.

Jensen has sold around 100 dolls at about $3,800. His customers seem price-sensitive; sales have dropped since the tariffs went into effect. Some fans have considered a doll-sharing model.

by Henry Chandonnet, Business Insider | Read more:
Images: Simon Simard; Cliff Jensen

[ed. See also Lars and the Real Girl (with Ryan Gosling). Now streaming on Tubi for free (with ads). Also, Are Humanoid Robots Ready to Be Deployed? (New Yorker).]

What's Elon Worth?

[ed. Let's see, by my watch $103,000 every minute. He could own every major league sports team 2.5 times over; buy all the gold in Ft. Knox (with billions to spare)... (more).]

via:

The Shape of the Thing

via:

Meta Culpa

Early last year, Meta's chief technology officer, Andrew Bosworth, had a clear message for his staff. "You should quit if you feel that way," he told one employee who said workers were being treated poorly. "You should consider working elsewhere," he told another person who questioned controversial changes at the business. He was reinforcing the company Meta had spent the last few years trying to become: a lean, fast, high-pressure organization that no longer had the patience for internal debate. "You can leave," Bosworth said, "or disagree and commit."

But this month, in a memo and a meeting with employees, Bosworth sounded like a different person. Morale is "probably one of the worst it's ever been," he said, adding that the business had done "an atrocious job" with its recent restructuring. "We've undermined the trust you have that your specific expertise and contribution will be valued."

Since 2022, Meta has remade itself around a ruthless management playbook that helped define a new era in Silicon Valley. Through relentless layoffs and many other unpopular decisions, executives charged ahead, emboldened by record profits and apparently immune to the building discontent. Bosworth's comments last week were different — an acknowledgement that Meta's leadership may finally be confronting the costs of its actions.

Meta's workforce is at a breaking point. Employees in the UK are trying to form a labor union, decrying executives' "cruel and shortsighted behaviors." More than 1,600 workers have signed a petition demanding that Meta stop tracking employees' keystrokes to improve its AI models. As Wired reported this month, things have gotten so bad that one frustrated employee hijacked a livestreamed meeting with a profanity-laced outburst directed at an executive. Another compared working in a new AI-training unit to the gulag. Others are so dejected they're actually praying to get laid off so they can leave with at least some severance.

Against this backdrop, Bosworth was one of several executives in recent weeks scrambling to do damage control. Chief Product Officer Chris Cox acknowledged the "insanity of this company" that created a "difficult" and "brutal" environment. CEO Mark Zuckerberg admitted "we've made mistakes."

"It's a classic example of chickens coming home to roost," says Sandra Sucher, a professor of management practice at Harvard Business School. "They have almost systematically destroyed trust. They are trying to figure out how to dig themselves out of the hole that they dug."

The digging started with a mass layoff of 11,000 people in late 2022, which Zuckerberg was at least apologetic about. The company then slashed another 10,000 jobs the next spring in what Zuckerberg hailed as a "year of efficiency," and then another 3,600 in 2025 that he said was to get rid of "low performers," effectively torpedoing some workers' job searches (many of them, it turned out, had received good performance reviews). In March this year, news leaked that the company was about to ax even more jobs, but it didn't confirm the cuts for weeks and didn't notify those affected until May, sending everyone into a nauseating, two-month purgatory. In April, amid the limbo, Meta announced it would start tracking employees' keystrokes, stoking fears that the company wanted to automate their work. And in May, as it laid off 8,000 employees, it reassigned another 7,000, many of them to menial jobs that involve training AI. Meta declined to comment on this story. [...]

For employees caught in the hailstorm, it must have felt validating for an executive to empathize with their situation. But surely he and the rest of Meta's leadership knew all these things would make employees unhappy, and yet they did them anyway. So why the sudden mea culpa?

Perhaps all the anger, dissatisfaction, and open rebellion was harming productivity. Or the particularly public nature of Meta's dysfunction, with the crescendo of news reports, had become a liability for its reputation with investors. Or maybe executives finally realized what had become patently obvious to everyone else — that whatever Meta was doing just wasn't working. The whole point of adopting this hard-charging management style was to get employees to innovate faster and catch up to competitors like OpenAI, Anthropic, and Google in the all-consuming battle over AI. Instead, Meta has been falling farther and farther behind.

by Aki Ito, Business Insider |  Read more:

Image: Wally Skalij/Getty; Getty Images; Tyler Le/BI
[ed. Why anyone would want Facebook/Meta on their business resume is beyond me. The money might be good, but working for a company like that would just be burning life years. See also: The Internet Has Become Too American to Trust (The Walrus).]

Bitcoin Winter

Why bitcoin is trading at a 2-year low

Bitcoin is in the dumps.

The apex cryptocurrency is down more than 30% in 2026, slumping to its lowest level since 2024 this week to trade around $59,200. That marks about a 53% drop from the token's all-time high above $126,000 last October. Ethereum, the second-biggest crypto, is doing even worse, down 48% this year.

So, how did the Trump-era bullishness for crypto that took bitcoin to record highs give way to a brutal crypto winter that shows little sign of thawing?

Scanning around, there's little good news to be gleaned from the headlines. Interest from institutional and retail investors alike looks tapped out. That's evidenced by record outflows from bitcoin ETFs, which Deutsche Bank says have hit $6 billion in six weeks, the longest losing streak since the funds were launched in early 2024.

"This matters because ETF demand has become central to Bitcoin's price formation: the same vehicles that supported the 2024-25 rally now amplify the decline mechanically when flows reverse," the bank wrote this week.

And then there's Strategy. The business data firm founded by Michael Saylor, the "never sell" bitcoin evangelist, has sold some bitcoin.

"On 1 June, Strategy (formerly MicroStrategy) disclosed it had sold 32 bitcoin, its first sale since December 2022. The amount was negligible (0.004% of holdings) and the immediate price reaction was modest (~3%), but the signal was not," Deutsche wrote.

In the days following the sale, bitcoin dropped nearly 20%.

Selling by Strategy—which is the largest corporate holder of bitcoin—has been a looming question mark all year as the token's price has slumped below the Strategy's average cost. The difference in the firm's net asset value of its bitcoin holdings versus its market cap has driven speculation that it could sell more tokens, an event that would weigh further on sentiment.

"Bitcoin currently trades below Strategy's average cost of $75,699, and the market has begun to price the possibility of forced selling by leveraged corporate holders. We expect this question to persist," Deutsche analyst said.

Capital is also flowing away from bitcoin and into another speculative area of the market: AI. Analysts attribute much of the waning enthusiasm for crypto among retail traders directly to their relentless appetite for artificial intelligence. The rapid outflows from bitcoin ETFs in the last month have been mirrored in blistering pace of investing in many of the top AI and chip ETFs.

A final wrinkle is the surprisingly hawkish new Fed boss, Kevin Warsh. The policy meeting this month officially dashed all hope of a rate cut, with Warsh's first meeting further boosting odds of a rate hike, a bearish development for risk assets like bitcoin.

by Max Adams, Business Insider |  Read more:

Image: Yahoo Finance; Jennifer Sor/BI

Leviathan Waking

[ed. I'd suggest reading this first: The Once And Future Fable #2.]

Imagine that there were no Food and Drug Administration (FDA), but there remained a large pharmaceutical sector, similar in size and scope to the one the United States enjoys today. In this alternate world, imagine that drugs were not licensed or otherwise formally approved by regulators; there were even officials in the executive branch who boasted that the U.S., unlike other countries, would not get into the regulatory morass of licensing drugs.

One day, a pharmaceutical developer warns that they think they have made a drug that cures a major Cancer at one dosage but is lethal at a slightly higher dosage. The company says, for this reason, that they are going to restrict release only to pre-approved patients and monitor their usage of the drug carefully—a sharp break from prior industry practice but one that the company insists, controversially, is necessary. This particular company had been advocating for years for stricter drug regulation, much to the chagrin of the government.

This causes a stir, and the government, not quite knowing what to do, announces that it will give drug developers the helpful option to show their drugs’ safety profiles to government officials before they are released. They are adamant that this is a voluntary program. The pharmaceutical company, being hopelessly literal nerds, and if we are being honest, more than a little bit obstinate, decides to release their drug without going through the voluntary program. “We already paused general availability of the drug while we did our own safety study, so we don’t need the government’s testing, and besides it is voluntary, isn’t it?” the company seems to be saying.

But then a handful of patients get side effects severe enough to hospitalize them, but not severe enough to be lethal. The government gets understandably upset, particularly considering their lack of experience in regulating drugs. “You talked up your own safety practices so much, and now we have people in the hospital. You are telling us that you are comfortable releasing chemicals that can put people into the hospital?,” the government argues to the company.

The company’s literal and obstinate nerds say, “well, we’ve thought about drug safety regulation quite a bit, and given how common hospitalization of a small number of patients is with a new drug, compared to the lifesaving benefits of our drug for millions, yes, we think the benefits outweigh the risks in this case.” But trust has already broken down, and this abstract, technocratic defense falls on deaf ears. “People are being hospitalized,” the government says.

And so the government bans the drug, indefinitely. It is not clear what the government wants more: a remedy for this specific side effect, a solution to all side effects from drugs, or, really, an apology from the company, as well as the sensation of domination over these disobedient, obstinate, and literal nerds.

In a matter of weeks, in our alternative world, the United States went from a system that was implausibly laissez-faire for the level of risk involved in this industry, to a system that was, in the eyes of essentially all expert onlookers, incomprehensibly strict and risk averse.

Fable, Jailbreaks, and Export Controls: What Happened

This, of course, is my read of what happened in the Trump Administration’s latest dispute with the AI company Anthropic. For those not following the blow-by-blow, what happened, in a few sentences, is:

1. Anthropic released Fable, a commercial version of their very-powerful Mythos model with severe guardrails to prevent misuse.

2. People liked it, though broadly speaking thought the guardrails were far too strict.

3. A few days later, officials in the Trump Administration (it is not clear who) became aware of a jailbreak that got around some of Fable’s safeguards (it is not clear how severely), and demanded that Anthropic de-deploy the model (it is not clear with how much specificity the government expressed the concern).

4. Anthropic did not de-deploy the model (it is not clear why), so the government imposed worldwide export controls against all non-U.S. persons on Fable and Mythos.

5. Because Anthropic lacks the ability to validate U.S. personhood for end users, this meant they had to pull down the models globally, for everyone. In fact, by some accounts, Anthropic has had to suspend internal usage of their model because of the risk that their own non-U.S. person employees might use the model.

You’ll notice the clause “it is not clear” repeated frequently above. The sheer opacity of everything that is unfolding makes it hard to analyze. There is no text for me to draw on, and no actual policy to criticize. There is simply a game of he-said, she-said played between two actors whose animosity toward one another is only growing and who both, if we are honest, seem to be making things worse for themselves and for the whole industry. [ed. Iran, anybody?]

by Dean Ball, Hyperdimensional |  Read more:

Image: via

[ed. Why does this same chaos script keep repeating with everything this administration touches. Rhetorical question. See also: White House Will Ad Hoc Decide Who Can Individually Access GPT-5.6 (DWAtV).] 

[ed. Update: Sorry, this has nothing to do with AI frontier models, but everything to do with decision-making in this administration. Can't help but laugh (or cry)... Promises Made, Promises Kept (Defector):]

***

"If everyone in the United States weren't living downstream from its consequences, it would be a pretty good tragic flaw that Donald Trump wants more than anything to be seen as a brilliant man who has always been right about everything when he is transparently a butterfingered dunce whose professional expertise more or less begins and ends at making cutting remarks from a safe distance and directing other people to file nuisance lawsuits on his behalf. If assessed from a sufficient remove, the spread between the opening proposition—the man who knows more about every subject than any expert without even having to study or even pay attention to any of it, because he is just that much of a natural talent—and the relentlessly oafish output is a great bit, if admittedly also a bit one-note.

Lots of awful people are like this, and a great percentage of the degenerate gentry that is Trump's truest and most durable base is extremely like this: Dumb old bullies all grandiose and soft from golf and infidelity; illiterate real-estate types with detailed opinions on The Differences Between The Races; the luridly unemployable adult children of car-dealership guys; anhedonic beneficiaries of a good investment or two who have, through sheer restless indolence and various dull biases, backed into some truly berserk and totally bespoke authoritarian worldviews. Aging phone addicts who think the country "needs a pharaoh." Ruddy tax evaders who fear cities and are insecure about their boats. None of these people really do things especially well, and all of them are visibly getting worse, but they are all far enough from experiencing any kind of consequences that they can't really imagine failing at anything they try.

This mindset scales all the way up to some of the most powerful people in human history, but it is the same all the way down. It amounts to the belief that only these particular wimpy pink goofs, each one the protagonist of reality, can be entrusted to run things, and that any problem can be solved by telling some underling to handle it, and also to the idea that such an order becomes a glorious and vindicating solution immediately after it is issued. Nothing that follows will ever be their fault. Provided you do not care about or pay attention to the world, this worldview absolutely rocks."

What If It All Came Out?

The nightmare began with an annoyance as benign and commonplace as a housefly. “Hi there Matt,” the July 11, 2024, email read. “We received a message from you earlier today through our support page related to a changed password on your account … If you didn’t make a support request,” the sender asked politely, “please let us know.”

Matthew Van Andel, 44, who goes by the nickname Dutch, had never heard of “nullbulge.se,” the domain name that sent the message. It appeared to be a classic phishing attempt, a prompt to get him to reply to the email with personal information. So he marked it as spam, swatting it away with a near-automatic series of clicks. Van Andel worked in technology at Disney corporate in Burbank. He loved his job at “the Happiest Place on Earth”; over his seven years at the company, he and his wife, Nicole, had become Disney adults, taking advantage of discounted park tickets with their two kids. Their house in La Crescenta, where Van Andel was working remotely when he got the email, was filled with Mickey and Star Wars and Marvel memorabilia.

Fifteen minutes later, another message arrived from the same sender. This one took a different tack. “Hi Matt. We regret to inform you we have gained access to certain sensitive information related to your personal life.” Van Andel would have deleted this, too, but he had received exactly the same message on Discord, a platform he used to chat about gaming. And it contained specific information that only a few people could, or should, know. “We noticed you had a conversation with Aadya and Shawn about being at Granville for ‘$veg && $keto,’” it read. That was strange. Aadya and Shawn were Van Andel’s co-workers; “$veg && $keto” was a joke about lunch that Van Andel had made while chatting to them on Slack, the internal-messaging system Disney used, a few days earlier.

Seeing his own private words on the screen, Van Andel messaged Disney’s information-security department. The emails had been sent to his personal account, which he was reading on his personal gaming PC in his home office. Info-sec told him his Slack account and work laptop appeared to be operating normally. Still disturbed, Van Andel deleted the second email. Immediately a third arrived: “You think we didn’t see you mark our first test as spam? Then our actual attempt [at] contact went right in the trash.” Van Andel felt his stomach drop. Someone had live access to his account and was watching him use it.

As an engineer, Van Andel thought he had above-average personal op-sec. He ran anti-virus software on his computer. He used Proton Mail, which encrypts messages between users. He turned on multifactor authentication for serious stuff like iCloud. For the past decade, he depended on a password manager called 1Password, which generates random, long, and complex passwords; stores them; and automatically remembers them whenever a user needs to sign in. For Van Andel, 1Password even managed his multifactor-authentication codes. But his diligent, longtime use of his password manager turned out to be Van Andel’s vulnerability. Having all that information in one handy place meant that once someone else was inside, they had a master key to every aspect of his life: his iCloud, iMessage, emails, photos, PayPal, financial information, medical records, social media, his parents’ financials. Over 1,000 accounts. The only way someone could have gotten into his email was if they had cracked his 1Password; when Van Andel realized they must have access to everything, the room began to spin.

He had no idea why the hackers had targeted him or what their plan was, whether they would drain his family’s finances or stalk his home. Eventually, after running another anti-virus program, he found a piece of malware hidden in a plug-in he had downloaded from GitHub, the open-source coding site, one day in February when he was messing around with an AI image generator. He had checked the code himself, it had looked legitimate, and others had reviewed it positively. But it seems it contained a Trojan-horse virus that gave the hackers free rein of his PC. Once inside, they just had to wait for Van Andel to log in to 1Password. From there, they were able to steal all his credentials, plus many of his multifactor-authentication codes, so every time Van Andel logged in to an app, a website, or an account, they could follow behind him. They’d had access for months.

By morning, Van Andel had received a call from Disney info-sec: The intruders had revealed themselves on a blog post celebrating the hack as NullBulge, an activist collective “protecting artists’ rights and ensuring fair compensation for their work,” according to their website. It was later reported that they were Russian furries. They had dumped the contents of Van Andel’s 1Password onto BitTorrent along with his full name — every personal log-in credential, his messages, his bank information, his medical diagnoses, his Amazon account. They’d also managed to access more of Disney’s data than just Van Andel’s Slack messages and published that too: employee Social Security numbers and Slack messages, budget spreadsheets and passport information for the company’s cruise-line workers. It was a massive breach. As people around the world tried to use the information NullBulge had posted, Van Andel’s iPhone began pinging every few seconds with attempts to get into his accounts. Someone logged in to his children’s Roblox profiles and began defacing them with Nazi screeds. Unknown callers left voice-mails. “Dude, your life is over, haha,” one said. “Just leave the country; that’s my advice. Good luck, have fun, and I hope your type 2 diabetes doesn’t get the best of you.” Van Andel raced around the house unplugging Ring cameras and Amazon Echos. Discovering every new potential violation was like learning he was bleeding from a limb he didn’t remember he had. Viscerally, painfully, he could feel the overwhelming breadth and permanence of everything he had ever recorded online, ephemeral and vital and intimate and stupid. Somehow it was only the first wave of exposure he would endure.

by Bridget Read, Intelligencer |  Read more:

Image: Tracy Ma

[ed. Privacy is dead. Edward Snowden is still exiled in Russia.]

America Has a Pangram Problem

AI-detection tools are getting better. But they still aren’t good enough.

Basically every recent, high-profile accusation of someone passing off AI-generated writing as their own has started in the same way: with a tool called Pangram. In March, when a horror novel from a major publishing house was pulled just days before its scheduled U.S. release date, it was in part because Pangram, an AI-detection program, had identified the text as AI-generated. Other people have fed text into Pangram to suggest that chatbots have been used to write articles in major newspapers including The New York Times, multiple short stories awarded a prestigious literary prize, and most recently, significant chunks of Pope Leo XIV’s encyclical warning about the dangers of AI. The tool is also used by universities to vet student work and scientific associations to scan research papers. As panic builds over AI-generated writing, Pangram is at the foundation.

Just a few years ago, it seemed like it might never be possible to instantly and reliably determine whether a piece of text was written by a bot or a person. In 2023, one detection tool, ZeroGPT, declared the U.S. Constitution to be AI-written; the same year, OpenAI abandoned its AI detector altogether owing to a “low rate of accuracy.” And that was when the quality of ChatGPT’s writing was markedly worse than it is today. But detection tools have gotten much better of late—and Pangram, in particular, has emerged as the gold standard: Paste a chunk of text into Pangram, and the model appraises what portions were “AI Generated,” “AI Assisted,” or “Human Written.”

Yet an AI detector that is mostly reliable might in some ways be more dangerous than a broken one. While Pangram is accumulating the power to end reputations and careers, the tool does make mistakes, perhaps to a greater extent than is currently understood. In turn, AI accusations could very quickly spiral into a witch hunt.

Pangram says its algorithm is so accurate that it incorrectly identifies text as an AI output only about one in every 10,000 times. “There is a great responsibility, a huge weight” in saying something is AI-generated, Max Spero, Pangram’s CEO, told me. “The only reason we do so is because we’re extremely confident.” Several independent analyses have also confirmed that it is quite good. One paper, from the University of Chicago, found that Pangram had almost no false positives on some 3,000 sample texts of roughly 500 to 1,000 words.

But Pangram’s ability to guarantee something was written by a human is shakier. Spero pointed me to a test showing that Pangram’s false-negative rate, or how frequently the model incorrectly labels text as human, is closer to one-in-70 (although some other assessments say it is more accurate than that).

Part of the problem is that Pangram is in an arms race with the major AI labs, which have an interest in making the writing of ChatGPT and Claude sound as natural and human as possible. And at the same time, Pangram has to deal with AI “humanizers”—programs designed explicitly to disguise AI text as your own. Reddit users rave about a humanizer called Walter Writes AI, which I decided to test out for myself. I had ChatGPT and Claude write brief articles, then pasted them into Walter Writes AI. The program, like other humanizer tools, does some anodyne rewording, swaps one clunky transition clause for another, and introduces grammatical oddities. For instance, ChatGPT’s “The numbers are no longer small enough to ignore” became “The sheer size of these usage figures can no longer be ignored.” When I pasted any output from Walter Writes AI into Pangram, it invariably told me that the twice-baked AI article was human-written. (It’s worth mentioning that The Atlantic forbids using AI-generated text unless labeled as such, and that I do not use AI for research.) [...]

Further complicating matters are the opaque ways in which Pangram and similar tools are designed. The model was trained by feeding it mountains of examples written by a human and by a bot—a book review in an actual magazine, then a review about the same book in the style of the same magazine, but produced by ChatGPT—until it can tell the two apart. This is akin to feeding millions of photos of cats and dogs into an image-recognition algorithm until it learns to spot the differences. Pangram cannot point to much specific evidence or patterns in diction, phrasing, or punctuation to support why it deems something AI or human. (I do not, for instance, understand why “these usage figures” was more human than “the numbers.”) Moreover, while Pangram distinguishes between “lightly” and “moderately AI-assisted,” these broad categories can mean just about anything short of copy-pasting from Claude—using AI for research, coming up with counterarguments, as a thesaurus, for a grammar check. The algorithm’s inner workings are “pretty uninterpretable,” Spero said, and although he wants to make Pangram’s “AI-assisted” label more granular, he is also “still not sure how possible it is.” Amid concerns of overreliance on AI chatbots, we risk simply layering on dependence on yet another black-box algorithm.

Spero told me that Pangram should “never be the ending arbiter” but instead a starting point for a more thorough investigation, and that the company looks into every reported error its model makes. He also noted that all sorts of detection technology we rely on—smoke detectors, TSA scanners—have base error rates too. On some level, in all these cases the biggest problems lie not in the technologies themselves but in what they’re trying to detect. It’s a problem that buildings catch on fire. It’s a problem that AI is seeping haphazardly into every facet of written communication.

by Matteo Wong, The Atlantic |  Read more:

Image: Atlantic/Getty
[ed. This seems like a transient issue to me. If AI is eventually able to write something (or create art) that's undetectable from what a human would produce, who cares? (except for writers and artists, obviously). You don't see this controversy in coding. See also: AI-Writing Scandals Are Getting Very Confusing (Atlantic). Also via DWAtV:

***

Again, we learn not that AI is a good writer, or that humans are bad writers, but that the literary prize judgment processes are worthless.

Jack: That which can be won with undisclosed AI output should be

Nabeel S. Qureshi: *Another* apparently AI-generated story wins a literary prize, this time judged by a panel including the novelist Ruth Ozeki.

Literary prizes need to start including Pangram checks in their process, or else change the rules to make AI writing ok. It’s very simple! [...]

How should we think about ‘witch hunts’ where people identify writing as AI?

Shashank Joshi: One of the worst trends of recent months: pseudoscientific witch-hunts using AI detection tools

The hunts are fully scientific. The detection tools work, at least for now. I have yet to see a case where Pangram said something was AI, and the piece was neither written using AI nor crafted intentionally to fool Pangram. There are some cases of heavy copyediting that trigger Pangram, but if it’s heavy enough to trigger Pangram then I consider that to be on you.

Escaping the Ogallala Trap

There is a closing window to stop driverless cars from creating omnigridlock.

Self-driving cars are not a hypothetical future but a familiar part of the urban background in San Francisco. I have driven in them several times and the novelty of seeing a steering wheel turn itself has pretty much worn off. During 2026, Waymo service will expand to Dallas, Houston, San Antonio, Orlando, and Miami, joining Atlanta, Austin, Los Angeles, San Francisco, and Phoenix.

Right now, self driving is a premium experience, more expensive than a human driver, in part because Waymo uses new cars, and in part because there are still relatively few Waymos on the road, spreading operational overheads thickly on a small fleet. Over time, Waymo and its competitors will become cheaper than human-driven taxis.

You make driving fun

Self-driving cars need not look like traditional cars inside. Normal cars are heavy and bulky, in large part due to safety requirements. Despite sharing the road with human drivers, Waymos already have 80 percent fewer accidents. When self-driving cars become 90 percent of the cars on the road, they will be able to platoon and join up into little trains, saving the space usually spent on gaps between vehicles and doubling road capacities.

They can be more comfortable as well. The Volkswagen GEN.TRAVEL has seats that fold out into flat beds, with passenger restraints for safe sleeping while moving and lighting designed to generate natural circadian rhythms. The Volvo 360c offers a first-class private cabin with a classic Volvo touch: a special safety blanket that acts like a seatbelt, usually loose and comfortable but tightening instantly on impact. In theory it can be an entertainment space or a mobile office too. Simpler, working versions of this idea, like the Amazon Zoox, are already driving around Las Vegas and San Francisco.

With imagination, you can see how a wide range of functions could be performed in a car: working, sleeping, eating, and even socializing, effectively bringing back the bar cars once enjoyed by New York commuters to Connecticut. I already buy cans of beer for long train rides with my friends. Train lines created entirely new seaside resorts like Atlantic City in the US, and Heringsdorf, Ahlbeck, and Bansin in Germany. Just imagine the trips people would make with the ability to effectively travel business class in their cars, driving overnight.

Our gridlocked future

Autonomous vehicles are the centrifugal water pump of the roads. Just like the Ogalalla Aquifer, most roads are currently free at the point of use. And just like the Ogalalla Aquifer, they will be overused if we do not charge for the privilege of drawing on them. Anyone who needs to get where they’re going quickly will be stuck in traffic with all the people enjoying a beer, working from a mobile office, or having a nap. There will be total gridlock.

Though taxes on fuel and registering cars are universal across the developed world, imposing charges at the point of use has been trickier. It took New York City 60 years to impose congestion pricing, and it was almost revoked several times along the way. London’s congestion charge has survived, but attempts to extend it out of the very inner core have not. Dutch voters destroyed per-mile charges, the Kilometerheffing, in 2010. Hong Kongers rejected such a scheme in the 1980s, despite an effective trial.

These attempts failed for a range of reasons. But a major one is that they aimed to change the rules of the game for everyone at the same time, creating a lot of people who lost out under the policy while giving them nothing in exchange.

by Ben Southwood, Works in Progress | Read more:
Image: Getty

AI in Biology

If you wind your way through a quiet, wooded suburb outside of The City, you’ll reach a harbor. Situated on a hill overlooking the water, there is a Temple of Science. This Temple is centered around a task of the utmost importance: preserving a magical thread that connects the past, present, and future of the life sciences.

On one end, there is a gentle tug from the ghosts of Barbara McClintock, Martha Chase, and Alfred Hershey, reminding you of their elegant experiments that became part of the canon of genetics. Farther along, figures like Jim Watson grip the thread more fervently as they advocate for the centrality of their discoveries in the birth of molecular biology. If you put one hand in front of the other and continue to follow where it takes you, you’ll pass through the rise of genomics and end up on the frontier of biology.

Of course, I’m talking about Cold Spring Harbor Laboratory. For over one hundred years, this little research institute in Long Island, New York has punched well above its weight. CSHL played a critical role in multiple paradigm shifts in biology—including genetics, molecular biology, and genomics—as evidenced by the eight Nobel Prizes awarded to researchers from “The Lab” over the years. When normalizing for size, the Nature Index ranked CSHL as the most prolific biomedical research institution in the world.

I’ll never forget my first visit to The Lab. In February of 2020, I flew from Seattle to interview for the CSHL graduate school program. Famously (among researchers on the grad school interview circuit), they would arrange for each recruit to be picked up in a black car from the airport.

The campus itself, which is a direct physical representation of the magical thread that The Lab preserves, is equally memorable. A cluster of pristinely maintained colonial buildings, each painted white, borders the water. Above them is the Upper Campus, consisting of darker, modern renditions of the same pattern. Scientific art installations—like the Waltz of the Polypeptides or a gazebo with a phage structure on the tip—can be found along the walking trails.

Over the course of three days, I hurried around The Lab for a wide range of activities, including eleven interviews with faculty—two to three times the number that most other graduate school programs typically scheduled. It was wonderful and intense.

Ultimately, I was persuaded to go west for graduate school. Thankfully, there are many reasons to continue coming back to CSHL, which has been described as “the crossroads of biology.” Each year, they host dozens of conferences and courses that draw top researchers from around the world.

But one particular conference stands out in importance. Since 1933, CSHL has hosted an annual Symposium on Quantitative Biology. Reginald Harris, who conceived of the conference, wrote that the “primary motive of the conference symposia is to consider a given biological problem from its chemical, physical and mathematical, as well as from its biological aspects.” In retrospect, this was visionary.

Over the next several decades, chemists and physicists would revolutionize the life sciences. In 1944, Erwin Schrödinger, a leading physicist, wrote What is Life?, a book exploring open questions in biology through a new lens. It inspired many researchers and students, including a young James Watson, to pursue biological research. In 1953, at the 20th annual CSHL Symposium, Watson presented the structure of DNA for the first time in public.

For obvious reasons, this gave the CSHL Symposia a sort of “mythic quality” moving forward. This reputation compounded quickly. Over the next 15 years, the pioneers of molecular genetics would travel each year to present their most important discoveries—such as the central dogma and the genetic code—at CSHL.

The tradition continues to this day. Each year, the Symposium is organized around a topic considered to represent the frontier of life sciences research.

Which brings us to the topic of the 90th Cold Spring Harbor Laboratory Symposium on Quantitative Biology: AI in Biology.

Readers of this newsletter are not strangers to the fact that AI is reshaping biology. The tools derived from breakthroughs such as AlphaFold have been adopted by seemingly all biologists at this point. But it was stunning to see these advances celebrated so prominently in this venue. It felt historical.

As Bruce Stillman, CSHL’s current President, pointed out in his opening remarks, this topic connects back to the very origin of the Symposia—as the name suggests. Harris had spotted the emergence of a new quantitative paradigm in biology. Between then and now, molecular genetics did in fact transform biology into an information science.

It’s becoming more clear each day that the next chapter of this story is AI. Sydney Brenner, one of the most central figures of molecular biology, gave one of the most incisive criticisms of the field in his Nobel Prize lecture: “We’re drowning in a sea of data and starving for knowledge.” AI is starting to change that equation.

For five days, top researchers in the field shared updates on their efforts to use machine learning to decipher the mechanisms of DNA, RNA, proteins, cells, tissues, organs (especially the brain), and how information flows between these different biological scales. And there were examples of how AI agents might be able to autonomously carry out some of this research—which was met with a combination of excitement and anxiety from attendees.

It was one of the most compelling conferences I’ve ever attended, so I want to share some of what I saw. Before jumping in, this requires a few quick notes on the format of the event.

First, attending a Symposium feels like drinking from a scientific firehose—by design. CSHL is truly a Temple, or maybe even a monastery. Most attendees stay on campus and don’t leave for the duration of the conference. Talks are back-to-back all day in the main auditorium, followed by communal meals and poster sessions that run throughout the evening. It’s non-stop. My goal isn’t to give an exhaustive blow-by-blow, but to highlight some of the themes and topics I found most exciting.

Second, following in the tradition of Watson, many researchers share more new and unpublished data than is typical at other conferences. To respect this tradition, I’m going to focus on the data shared that has already been published, with more high-level descriptions of new research directions and results.

With all that said, let’s get into it! [...]

Agents, Agents, Agents

Maybe I’m in a bubble in San Francisco, but it’s hard not to constantly hear about AI agents in the year 2026. It’s strange to think, but it’s been three and a half years since ChatGPT was first released. That’s long enough for many humans to feel frustrated by the shortcomings of what was once magic. Now, we want these models to do work for us, and to carry out longer, more complex projects that require reasoning.

There are now many efforts to develop systems for “agentic science,” where AI models are able to autonomously develop new hypotheses, design experiments, and analyze results. This concept was another recurring theme at the symposium.

Pushmeet Kohli hit on this the first evening. The last third of his talk focused on DeepMind’s efforts to build an AI Co-Scientist, which they published a new paper on last month. Given a research goal by a human scientist, this system develops a research plan and then kicks off a “tournament” of agents competing to develop new hypotheses. Agents within this system have different tasks. Some are designed to “reflect” on the ideas being generated. Others are tasked with “evolving” them.

While the goal is hypothesis generation, the AI Co-Scientist itself is no longer just a hypothetical. DeepMind has already given early access to academic researchers working in a wide variety of biomedical domains. Kohli highlighted a high profile example where the Co-Scientist was able to predict a new mechanism of bacterial gene transfer before the result was published in the literature.

by Elliot Hershberg, The Century of Biology | Read more:
Image: uncredited/CSHL

[ed. See also: What’s new in biology: June 2026 (Works in Progress).]

The Modern Efficiency of Squid Fishing

How Japanese Fishermen Use Robots To Catch Billions Of Squid (IE).

Video: YouTube

[ed. For calamari lovers. Squid fishing has gotten pretty efficient these days (and they land some big ones!). I remember catching them at night with my brothers in Kona, to use as bait for over-night tuna fishing (Ika Shibi). We'd go a ways offshore, put out a parachute anchor, then turn on the floodlights to attract them to the boat. Soon there'd be hundreds of them darting in and out of the light, coming from nowhere, out in the middle of the ocean. Using a multi-pronged snagging jig we'd catch our needed supply in no time. Fun! But wierd too - being surrounded by darkness except for the lights illuminating a small circle around the boat. It felt like fishing in a swimming pool.]

SignalTrace: New Levels of Surveillance

If you thought Flock cameras were concerning, meet what comes next. 

A company called Leonardo has developed a system called ELSAG SignalTrace. It broke into public awareness just days ago and is already being marketed to law enforcement agencies across the country. It makes Flock Safety look modest by comparison. 

Here is what SignalTrace does: 

It clips sensors directly onto existing license plate reader cameras — the same poles, the same hardware already installed in your community. No new infrastructure required. A software and sensor upgrade is all it takes. 

Every time you drive past one of these upgraded cameras, the sensor sweeps up the unique electronic identifiers of every device in your vehicle. Your cell phone. Your smartwatch. Your wireless headphones. Your fitness tracker. Your laptop. Your tablet. Your car's own infotainment system. Your tire pressure sensors. Your vehicle's Bluetooth hotspot. 

And your pet's microchip. 

Every one of those devices emits a signal. SignalTrace captures those signals, timestamps them, ties them to your license plate, and stores them in a searchable database for future investigative use. The result is what Leonardo calls an electronic fingerprint — a unique profile built not from your face or your name, but from the constellation of devices you carry with you every day. 

Leonardo announced the ELSAG EOC Plus patent as early as May 2024, describing it as an electronic detection system for identifying people of interest through electronic device signatures. SignalTrace is the commercial product built on that foundation. The patent came first. The marketing came after. The sales calls are happening now. 

Here is where it gets worse. 

SignalTrace is explicitly designed to track vehicles even when the license plate cannot be read. If your plate is obscured, dirty, or misread — it does not matter. The system identifies your vehicle by the electronic fingerprint of the devices inside it instead. The plate reader becomes optional. The surveillance does not. 

The strategic advantage for police agencies is adoption friction. SignalTrace can be pitched as an extension of an existing ALPR ecosystem rather than a wholly separate surveillance buildout. That is exactly what happened with Flock. License plate readers went in first. Video came later through a software update. Nobody voted on the expansion. Nobody was told. SignalTrace follows the same playbook — attach to existing infrastructure and expand what it captures without requiring a new procurement process, a new vote, or a new public conversation. 

Who is Leonardo and why does their background matter? 

Leonardo US Cyber and Security Solutions is not a Silicon Valley startup. It is the American subsidiary of Leonardo S.p.A. — one of the largest aerospace, defense, and security conglomerates in the world, headquartered in Rome, Italy. Recent public market estimates place Leonardo S.p.A.'s market capitalization at approximately €29.76 billion — roughly $32 billion USD. For context that is nearly four times Flock Safety's valuation. [...]

What is ELSAG — and why SignalTrace is more dangerous than it sounds. 

ELSAG is Leonardo's license plate recognition product line — the company's core law enforcement technology that has been deployed across American communities for over two decades. ELSAG cameras are what you think of when you picture a standard license plate reader. Fixed cameras on poles. Mobile units mounted on patrol vehicles. Solar powered. Cellular connected. Reading plates and logging vehicle data. 

ELSAG is already deployed in all fifty states. Virginia State Police is a documented customer. Leonardo holds statewide procurement contracts in New York, Maryland, New Mexico, Ohio, and Pennsylvania among others, and is listed on the federal GSA schedule available to agencies nationwide. Their cameras are already on street poles and patrol vehicles across the country — quietly, routinely, and largely without public awareness. 

SignalTrace is not a new camera. It is not a new company. It is an upgrade — a sensor that clips directly onto ELSAG cameras already in the field and adds a new layer of data collection on top of the license plate reading that was already happening. The same pole. The same hardware. A new sensor attached to it that now also sweeps up every electronic device signal in every passing vehicle. 

That is precisely what makes it so significant. The deployment barrier is almost zero. Any law enforcement agency that already has Leonardo ELSAG cameras can add SignalTrace capability without purchasing new infrastructure, without a new procurement process, and — depending on how their existing contract is written — potentially without returning to their city council for approval. Sound familiar? It should. It is the exact same function creep mechanism that allowed Flock Safety to add video streaming, vehicle fingerprinting, and AI people search to cameras that were originally sold as simple plate readers. 

The infrastructure goes in first. The capabilities expand later. The public finds out last — if at all. [...]

The data retention problem. 

With Flock we at least know the default data retention period is 30 days — though the contract language grants Flock a perpetual license to use that data regardless. With SignalTrace the situation is more opaque. Leonardo's product materials state that all data collected may be uploaded to the EOC server and archived for future queries and analysis — with no published retention limit. How long does Leonardo store your electronic fingerprint? Who has access to it? Can it be shared with other agencies or federal entities? Can it be purchased by data brokers? Leonardo's materials do not answer these questions. That silence is itself an answer. 

The retail and private deployment problem. 

Leonardo is actively marketing SignalTrace to shopping malls, retail centers, and private businesses — not just law enforcement. Their materials describe deploying SignalTrace in parking lots and inside shopping centers to track individuals involved in organized retail crime. By identifying and correlating electronic devices carried by suspects, retailers can gain critical insights into criminal patterns. 

That means SignalTrace sensors could be on private property you visit every day — your grocery store parking lot, your shopping mall, your workplace — operated by a private company with no law enforcement oversight, no warrant requirement, no public accountability, and no notification to you. Your electronic fingerprint captured every time you park your car. Stored indefinitely. Shared with whoever the private operator decides to share it with. 

The no-plate-needed problem — and what it means for pedestrians. 

The implication of being able to track a vehicle by its electronic fingerprint without reading the plate goes further than most people realize. Deliberately obscuring your plate — which some people do to avoid surveillance — provides zero protection against SignalTrace. The sensor does not need the plate. It reads your phone. 

More critically — the sensor does not know or care whether the device it is reading is inside a vehicle or in the pocket of a pedestrian walking past the pole. A person walking down the sidewalk past a SignalTrace-equipped camera is emitting the same Bluetooth and Wi-Fi signals as a person driving past in a car. The system's sensors capture signals from whatever passes within range. Whether that includes pedestrian device capture is not addressed in Leonardo's public materials. The fact that it is not addressed is worth noting. [...]

SignalTrace does not aggregate your vehicle's movements. It aggregates your personal electronic identity — every device you carry, every signal you emit — and ties it permanently to a location, a timestamp, and a plate number. It does not track your car. It tracks you. Personally. Individually. Every time you pass a sensor, whether you are suspected of anything or not. 

by BlackBetty (Anonymous), X |  Read more:

Image: Natasha Eliya/Michigan Daily via

[ed. Public service announcement. Are they actually able to do this with the weak signal of wifi and Bluetooth? Wouldn't be surprised. See also: SignalTrace just weaponized your AirPods against license plate readers nationwide (Cambridge Analytica).]