
If you were thinking of jobs to net money on betting markets, White House teleprompter operator might not be top of the list. But maybe it should be. CC-licensed photo by Rob Pegoraro on Flickr.
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A selection of 9 links for you. Just read the words. I’m @charlesarthur on Twitter. On Threads: charles_arthur. On Mastodon: https://newsie.social/@charlesarthur. On Bluesky: @charlesarthur.bsky.social. Observations and links welcome.
Generative AI is an engineering disaster • The Atlantic
Alex Reisner:
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The problem with generative AI, in the industry’s own jargon, is that it does not scale. The cost of growing from, say, a thousand users to a million is a key factor that venture capitalists examine when they evaluate start-ups. They want to see that the cost of adding each new user decreases over time, so that the company can support millions of users and make increasing profits. This is achieved partly through the careful engineering of computer systems that can efficiently handle more users who want to post photos, hail Ubers, or stream music.
With generative AI, the work of building efficient, scalable systems has not been done. And the problem is exacerbated by the ever-larger generative-AI models, which have grown from 175 billion parameters in 2020 to more than 1 trillion today, according to independent estimates (the actual sizes of the models powering products such as Claude and ChatGPT are secret). The large in large language model should not be a selling point. But the industry’s observation that bigger models tend to outperform smaller ones has given rise to a totemic belief in “scaling laws” that suggest any problem can be solved by simply making models bigger. “Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer,” OpenAI CEO Sam Altman wrote on his blog in September.
Yet the returns are diminishing. The bigger an AI model is, the less it improves with each added parameter, and so it must be made bigger at a faster rate just to sustain steady progress. I asked a few AI researchers whether they could name any other real-world software that scales so poorly. None of them could think of any. Even outside the world of software, it’s hard to find a comparable example, given that economy of scale is the principle that has made light bulbs, cars, and clothing so affordable. By economic and engineering measures, generative AI might be the worst technology ever deployed.
But with the massive investment behind the current bloated approach, there may not be much will to change. Ilya Sutskever, a co-founder and former chief scientist at OpenAI, said in a November interview that companies take the brute-force approach “because it gives you a very low-risk way of investing your resources.” It’s harder, he argued, to invest in research that would reengineer a product currently accruing trillion-dollar valuations. Those who suspect we are in an AI-driven bubble economy have pointed out that the profitability of these companies remains an open question, largely because of the high cost and inefficiency of the technology.
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The point that generative AI doesn’t scale – even while they try to build it at bigger and bigger scale – is an overlooked one, and critical to the whole problem here. It just needs more, and more of everything, and that doesn’t leave any room for anything else. (Gift link.)
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Someone used AI to write an unauthorized biography of me. I don’t recommend reading it • The New York Times
Kashmir Hill:
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I went to Amazon to investigate. There it was. A biography of Kashmir Hill — title: “The Biography of Kashmir Hill” — had been released nearly a year earlier, in August 2025. My life story had a mottled brown cover and a publisher I’d never heard of before. It had no reviews until I wrote one, asking, as the subject of this work, if I could please speak to the author. The hardcover cost $26.99, which seemed a bit steep, but my editor splurged on a copy and I was forced to read it.
My biography is 90 pages long and should be shorter. It combines facts about me that are widely available on the internet, such as where I grew up, with generic insights that could be true of anyone, like a horoscope spread over dozens of pages. “You cannot understand Kashmir Hill without understanding her contradictions,” my biographer wrote, along with an excruciatingly long description of my elaborate coffee-making ritual. (Fact check: My husband does it.)
The book is flattering, fabricated and absolutely packed with em dashes. It bears all the signs of AI slop. I clicked on the author, one John Crane Miller. His bio page described him as a “seasoned biographer and cultural analyst,” and his portrait was a widely used stock photo of a white man in a suit speaking at a conference.
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She found an AI-assisted author, though not the right one:
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[Bill] Johns, who has long curly white hair and the bronzed skin of someone who spends a considerable amount of time outside, retired in 2024 from his work as a cybersecurity consultant. Divorced and living alone with two Shih Tzus, he suddenly had a lot of time on his hands. He was curious about A.I. and decided to experiment with it.
“Almost everyone I know says they want to write a book,” he said. “It’s a very romantic concept to sit down and toil, page after page and paragraph after paragraph, but it doesn’t make economic sense.”
It is hard to disagree with that, though I can’t say I agree with Mr. Johns’s solution: Have an A.I. chatbot do it instead. He spent a couple of weeks and $20 on ChatGPT to help him write about the history of hacking and published his first book, a whopping 651-pager, in March 2025.
Of course, that was possible only because OpenAI, the company that created ChatGPT, had ingested the work of those romantic toilers — Wikipedia editors, Reddit commenters, book authors and reporters like me. (I must mention here that The Times has an ongoing copyright lawsuit against OpenAI, though the AI firm says it is “without merit.”)
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He gets a few hundred dollars a month – what he characterises as “bar money”. A new tragedy of the commons.
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The phantom author • Spratz’s Substack
“An armed ramble”:
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So much of our experience and indeed our expectations of reading are comfortably anchored in the assumption that the author is another human being just like ourselves. What changes when this is no longer true?
I often can’t tell whether a piece of text was written by an AI or not, and strangely enough, that doesn’t seem to have any impact on my response. I have certainly read texts that make me laugh and others that moved me deeply, only to discover subsequently that they were AI generated. Even with that subsequent knowledge, re-reading them has still caused me to laugh or to be moved. Here’s a recent AI text that made me laugh: “‘I have made a grave mistake,’ said the king, staring at the hole in the garden where he had buried his dignity. ‘Unfortunately, it seems to have been a very spacious grave.’”
I was quite surprised when I first realised this. I had always thought that my response would be dictated by the authorship of the text and yet it wasn’t.
George Poulet thought that when we were reading, we were actually inhabiting the author’s consciousness. My experiences significantly undermine that claim. Perhaps our responses are co-created by the text and the reader; the text acts as a catalyst for the reader. Maybe there are as many responses as there are readers? This seems disturbingly isolating; forcing us to accept that our responses may be almost solipsistic. An isolating and emotionally bleak conclusion. Yet, there are shared responses. What does that mean?
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This is a deep question. On Substack, people are debating whether this Guardian article – which is a potted version of a book – is AI-written. I had read it before seeing those claims, and thought it was a little overwritten, but interesting. The idea it might be AI changes how one thinks about the real-world events described: they’d seemed outlandish anyway, but we know a chatbot can’t really discern normal from abnormal behaviour, so this heightens our suspicion.
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Moroccan intelligence insider reveals widespread use of Pegasus hacking software • The Guardian
Sam Jones, José Bautista and Hicham Mansouri:
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A former member of Morocco’s domestic intelligence service has helped to provide an unprecedented insight into how the north African state used hacking software – including Pegasus spyware – to target journalists, human rights defenders, French politicians and Spanish cabinet ministers and police officers.
Pegasus, which is manufactured by the Israel-based NSO Group, allows its operator to access everything on a target’s mobile phone, including emails, text messages and photographs. It can also activate the phone’s recorder and camera, turning it into a listening device.
Although NSO Group says Pegasus is sold only to governments to help them track criminals and terrorists, the spyware is alleged to have been used by several countries to target dissidents, journalists, diplomats and politicians.
Morocco has long denied using Pegasus to target critics at home or abroad, and has claimed that reporters who have investigated NSO Group were “incapable of proving [the country had] any relationship” with the company.
However, evidence from a whistleblower who worked for Morocco’s Direction Générale de la Surveillance du Territoire (DGST) for almost a decade suggests the country’s internal security services began using Pegasus in 2017 and went on to deploy it against domestic and foreign targets over the course of four years.
Testimony from the source, known by the pseudonym of Safir, forms the basis of a multiyear investigation by the Moroccan journalist Hicham Mansouri, which has led to a collaborative investigation between several media groups, with technical support from Amnesty International’s Security Lab.
The consortium, which was coordinated by Forbidden Stories and comprises 14 media organisations – including Le Monde, Haaretz, El Confidencial, Die Zeit and the Guardian – has also analysed material detailing Morocco’s surveillance practices, from leaked emails to targeting records relating to Pegasus and other spyware, and from victims’ testimony to internal training material.
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This is the problem with any sort of spyware like this. It won’t be used in the way demanded by the creator. It’ll be used any damn way someone with a licence wants to use it.
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These are the worst ChatGPT flyers you’ve sent us • 404 Media
Jason Koebler:
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Earlier this week, I somewhat stupidly asked our readers to send me examples of “ChatGPT flyers,” the AI-generated posters and advertisements that have taken over social media, bulletin boards, restaurant menus, store signage, business cards, and billboards around the world. I say stupidly, because I was flooded with so many terrible, brain-numbing signs for anything you could possibly imagine. I guess I got what I asked for. (Thank you, I love it).
404 Media readers were particularly passionate about their hatred for AI-designed signs. I got some of the best email responses to any story I’ve done here. Before I get into the AI flyer hall of shame, here’s some of what I heard:
“They look like absolute DOG SHIT. Like my cat’s litter box! I freaking HATE THEM. I have been posting to my Instagram begging people and businesses to stop using them. No one listens LOL. Thanks for this article. I am glad I’m not screaming into the void by myself.”
“thank you for writing this story. I’ve evangelically shared it with everyone I know, for whatever that’s worth. I had never seen a local group churn out an AI-generated flyer before this year, but in the last several months it’s gotten out of control. I’m sure you’re being inundated with lousy AI flyers. Sorry for adding to the deluge, but this is something that’s been bothering me for months.”
“This is a great article but also fuck you because you were absolutely right about ‘Once you notice a ChatGPT flyer, you will see them everywhere if you keep your eyes open.'”
Without further ado, here are some of the worst flyers we got. This represents just a small sampling of the overall number you sent me. In some cases I’ve provided more context from the person who sent it to me, and I’ve biased for ones that appeared in real life (i.e., were printed out) or that are particularly weird. Enjoy!
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Some of these are awful, some you.. would just go past thinking they’re incredibly overdone but don’t have any obvious spelling mistakes, unlike some of them which cannot have been proofread.
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Peter Thiel’s AI tribunal pivots to scoreboard model • Hollywood Reporter
Gary Baum:
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Objection has overruled itself. This spring, Peter Thiel’s high-profile new startup had sought to disrupt journalism by establishing a tribunal in which reporters would be dragooned into AI-powered arbitrations paid for by the unhappy subjects of their articles. Now, the company has been renamed The Primary, pivoting to a system in which journalists are ranked on a digital scoreboard by the expertise of a large language model.
Objection’s CEO is Aron D’Souza, the entrepreneur-provocateur behind Enhanced Games, known as the “steroid Olympics,” who first gained fame as the legal mastermind behind Thiel’s bid to secretly finance Hulk Hogan’s successful invasion of privacy suit against the media outlet Gawker, which the right-wing tech billionaire despised.
Objection’s first tribunal, in April, targeted The Hollywood Reporter for its 2021 coverage about an heir to the Sackler family, whose Purdue Pharma fortune was built off OxyContin. In an interview, D’Souza told THR that “many journalists are more powerful than billionaires,” explaining, “I can’t tell you how many billionaires and CEOs have called me in absolute tears about their lives being destroyed by one article.”
D’Souza and Objection’s CTO Kyle Grant-Talbot — who met at Oxford, where they first founded a laundry service in 2018 — acknowledged they’d found it difficult to build proprietary software that wouldn’t be accused of outputting slop justice. “The AI-based reasoning models are easy in comparison to adjudication,” D’Souza said. (Objection pivoted before issuing a verdict in THR‘s tribunal.)
D’Souza and Grant-Talbot since arrived at a solution for their quandary by determining, as Objection’s home page now reads, that “verdicts punish failure. They don’t fix the incentive. They do not solve the root cause.”
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So fact-checking and objectivity is a lot harder than billionaires thought? What an utter shock. “Journalists are more powerful than billionaires”. Really. Long time since a journalist bought a social media company or a newspaper. (Though, OK, The Onion was bought by a company led by a former NYT journalist.)
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White House teleprompter operator made more than $100K betting on Trump’s speeches, sources say • ABC News
Katherine Faulders, Aaron Katersky, Peter Charalambous, and Nicholas Kerr:
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President Donald Trump’s longtime teleprompter operator is believed to have made tens of thousands of dollars by placing bets on more than a dozen of Trump’s speeches on the prediction market Kalshi, federal investigators with the Commodity Futures Trading Commission found, sources familiar with the matter told ABC News.
Gabriel Perez, a technical assistant to the president who has been operating Trump’s teleprompter since 2016, is in talks with federal regulators to settle allegations he used his inside knowledge of the president’s speeches to win more than $100,000, the sources said.
According to the sources, Kalshi alerted its regulator, the Commodity Futures Trading Commission (CFTC), to the suspicious activity on its “Mentions” market, where users can bet on whether specific words, phrases or topics are uttered during a public speech.
“Our surveillance team promptly flagged and referred these trades to the CFTC, and we are cooperating and assisting regulators,” Kalshi’s head of enforcement, Bobby DeNault, said in a statement provided to ABC News.
White House Press Secretary Karoline Leavitt told reporters Thursday afternoon, following ABC News’ report, that Perez has been put on unpaid administrative leave. Leavitt said she spoke with President Trump about it, and he thought it was a “disgrace” and made the decision himself to put Perez on unpaid leave.
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A part-hilarious element of this is that sometimes he was found to back out of bets he had made when Trump skipped over things that were in the teleprompter script. The best part is this, though:
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“The White House has strict ethics guidelines that we expect all staffers and officials to follow,” said White House spokesperson Davis Ingle when contacted by ABC News.
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Those guidelines being: don’t do it for small amounts. Seven figures minimum, or what’s the point?
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When eyeing a predator, horses keep a poker face as their hearts race • EurekAlert!
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Horses know a predator when they see one – even if it’s only on a video screen they’re watching in a stall, with no sounds, smells or previous experience providing context to what they’re viewing, a new study suggests.
And though sensors indicated the horses’ heart rates increased when they were looking at wolves on the screen, they otherwise kept a poker face. They didn’t bob their heads or swish their tails, and their gaze wasn’t fixed in a way that would indicate their brain was processing a threat, results showed.
“Rather than just spooking, horses show remarkable cognitive restraint when evaluating a potential threat,” said lead author Zeynep Benderlioglu, a senior lecturer in evolution, ecology and organismal biology at The Ohio State University. “And not all fear or stress will result in overt behavior. They’re not in fight-or-flight mode, but they’re assessing, and they’re doing it in a remarkably fast way. But their hearts are racing at the same time.”
The findings are relevant to horse and human welfare, Benderlioglu said: riders and handlers may not be able to tell when a horse is agitated.
“This visual recognition means horses may be experiencing an internal state of agitation while remaining physically still,” she said. “Understanding this disconnect is vital for ensuring both rider safety and the welfare of a horse that is processing a threat, especially if that threat is a canid – any dog.”
The research was published on July 15, 2026 in the journal PLOS One.
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Business Insider’s big bet against aggregation • Nieman Journalism Lab
Andrew Deck:
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It’s a Tuesday morning news meeting at Business Insider’s headquarters in New York’s Financial District. More than a dozen editors have gathered in the conference room, while several more chime in remotely on Zoom.
[BI editor-in-chief Jamie] Heller is shouting out senior correspondent Hugh Langley, who recently ran a feature on Google employees protesting the Pentagon’s use of the company’s AI products. It was a follow-up to his exclusive on leaked internal messages showing that Google is “leaning more” into national security contracts.
“He had a scoop, he had a follow-on spot, he had a discourse piece, and then another spot. It’s an example of how the work should flow,” said Heller, who joined Business Insider in September 2024 after more than 20 years at The Wall Street Journal.
Today, editors are discussing how best to frame their coverage of AI-related layoffs. Coinbase, the crypto exchange, has just cut several hundred employees in its attempt to become “AI-native.” Editors in London have been on the news for hours, and are handing off coverage to their New York counterparts. Heller is pushing for an exclusive.
“Have we called them for an interview?” she asks.
Business Insider says that since Heller joined the organization, the amount of “original content” it publishes has more than doubled. In 2024, the company says, about 40% of its content was scoops, exclusives, and other original stories. Today, that content makes up more than 80% of its output, as the publication has made a concerted effort to move away from news aggregation and break its own news. Last year, the newsroom landed 788 scoops, the most it’s ever recorded annually, former CEO Barbara Peng wrote in a recent memo.
Business Insider is trying to overhaul its editorial strategy as the digital news industry reckons with major traffic declines. Google’s AI Overviews and chatbot products like ChatGPT are killing traditional search traffic. Social platforms like Facebook and X have deprioritized news links.
In May 2025, Business Insider laid off 21% of its staff. “We must be structured to endure extreme traffic drops outside our control,” Peng wrote in a memo to staff that month. “We’re reducing our overall company to a size where we can absorb that volatility.”
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Original news? At a news outlet? What a radical concept. Everything old is new again.
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| • 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








