L’annonce par Open IA de la résolution du problème de Navier-Stokes, un des sept « problèmes du millénaire » ébranle la communauté des mathématiciens. Elle s’inscrit dans un contexte de compétition féroce entre Open IA et Anthropic qui ont fait de la résolution de problèmes l’étalon de leur progrès. Par Gautier Cariou
Vitamines, fibres, minéraux, antioxydants : le brocoli a plus d’un atout nutritionnel, à l’instar des autres choux. À condition de choisir une cuisson douce, capable de préserver leurs nutriments.
La grotte de Bianfu apporte une mine d’informations sur l’espèce Denisova, dont on sait à présent qu’elle était capable de fabriquer des outils rudimentaires, dans le but de parer au plus important : manger.
La défense du narval est unique en son genre : elle peut mesurer plus de 2m en restant droite et résistante. Une nouvelle étude décrit la complexité de son architecture et nous ouvre les portes de son impressionnante stabilité. Par Louise Ormansay-Gy.
Editor’s note: This work is part of AI Watchdog, The Atlantic’s ongoing investigation into the generative-AI industry.
Earlier this summer, Tamra Westberry received a Facebook notification that made her heart sink. A fellow author had taken to social media to endorse Westberry’s latest book, Project Erebus, after reading about it in a weekly roundup of the latest paranormal-romance releases. Independent authors like Westberry, who is based in Texas and has published dozens of books under the pen name Tara West, usually welcome an encouraging word and a bit of cross-promotion. But Westberry was dismayed. She had never heard of a book called Project Erebus. And she certainly wasn’t its author.
She looked up her author profile on Amazon, and there it was: Project Erebus,a book that featured character names she’d previously used, with a cover echoing that of her recent work. Translations were available in German, French, Italian, and Spanish. The book was a complete mystery to her, but after she read its sample pages, she suspected it was made by someone who’d used AI tools. (I ran the book’s cover and promotional blurb through Pangram, which suggested that they were completely AI-generated.)
Westberry emailed Amazon and requested that the company delink the unaffiliated books from her profile. Amazon removed the books from the platform within a week or so—but not before some of her fans purchased them, read them, and left reviews. “No real detail, characters remain undeveloped. I almost felt I was reading an essay written by a school child,” one disappointed reader wrote in a two-star review for Project Erebus on Goodreads, a literary social network owned by Amazon that had also attributed the book to West.
Across categories—fantasy, horror, even coloring books—writers say they’re seeing AI-generated listings crop up on their Amazon author pages. Some of these works are in entirely different genres from their usual work—such as a children’s series misattributed to a writer of steamy love stories—whereas others echo the subject matter or jacket designs of preexisting books. One writer reported someone sneaking in a fake edition under the listing of their real book. Because Amazon often sends out emails notifying author-page followers about new listings, these titles are able to leech a writer’s fan base, make ill-gotten revenue, and confuse readers.
AI companies pirated millions of books to train today’s most popular models, as The Atlantic has previously reported. Those models are now being used to churn out books in a matter of minutes and place them alongside books that represent years of hard work. In some cases, people go beyond mass-producing second-rate content or publishing copycats of new releases, using the names of established authors on parasitic works that feed off preexisting brands. Writers feel that they have little recourse regarding what AI models ingest, or spit out. “It’s deeply unsettling, after I spent years crafting stories and building my brand, that some no-talent grifter can bottom-feed off my fan base with AI slop,” Westberry, who’s written more than 50 books that were included in a data set used by the likes of OpenAI, Meta, and Anthropic, told me.
The parasite-creator problem is pervasive. Professors have found AI-generated academic papers published under their names; recent reporting suggests that sneaking AI-generated songs onto artists’ streaming profiles is a relatively simple move. The issue has also become endemic to Amazon, the world’s largest online book retailer, which sells hundreds of millions of books annually in the U.S. alone. The platform groups works with the same byline under a unified profile thanks to a largely automatic system. Authors say that Amazon has failed to make a concerted effort to address the phenomenon, and that the onus falls on them to monitor their pages, in a crazy-making game of whack-a-mole.
An Amazon spokesperson told me that the company does take measures to prevent, detect, and remove content that violates its guidelines, but it did not provide more details about how these systems work. “We are committed to a bookstore that readers love and publishers and authors trust, and work directly with authors to address any issues or errors affecting their accounts,” the spokesperson said.
To some degree, Amazon’s parasite-author problem predates the widespread advent of AI. A decade ago, Stephen King publicly urged the site to stop associating his own works with those of Stephen R. King., another horror author whose name was confusing fans. Such instances, however, were few and far between because of the time and effort it required to publish a title. Now that anyone can use LLMs to churn out a novel, the issue has both grown and mutated. While the sheer number of new books published on the platform might inevitably lead to more authors of the same name, Orna Ross, the founder of the Alliance of Independent Authors, noted that many titles are purposefully designed to blend in with a real author’s catalog. “It needs only to fool the algorithm and a rushed buyer for long enough to skim the sale,” she told me.
Authors told me that Amazon is typically quick to delink books from author pages once they’ve been flagged. But getting them removed from the platform entirely can be trickier, especially if a writer hasn’t trademarked their name. Amazon can treat such incidents as a matter of “name coincidence,” Ross said, and leave books up even after decoupling them from profiles. Writers struggling to receive direct action from Amazon have also escalated cases through the Authors Guild, the largest professional organization for writers in America, whose recent reports have warned of AI books falsely attributed to writers.
For many writers of genre fiction, which relies on high output and familiar tropes, staying afloat means playing a volume game, releasing numerous books a year to make a living. That makes certain genres particularly susceptible to AI dupes, which can blend in with the thousands of real titles released annually. Because producing AI versions is so cheap, even a few sales can be profitable. “The people that are making money selling AI copies are generally doing so by selling one or two or three copies of the thousand different books that they publish,” Julie Trelstad, a publishing consultant, told me.
The identity of the individuals behind these books is a mystery to real authors, and often difficult to track down. Regardless, authors don’t view such books as a major sales threat, given that they tend to be less appealing to buyers than genuine works, with slapdash covers and lackluster page counts. What writers are really concerned about is the potential for long-lasting reputational harm among readers, who typically trust that a book listed on an Amazon author page was, indeed, written by said author.
Last year, Vanessa O’Loughlin, an Irish author who writes crime books under the name Sam Blake, was alerted to a trilogy of “dark romantasy” books on her profile that she suspected were made with AI. She didn’t write them, for one, and the pages she read felt off. The books revolved around a character named Elara Vance, a combination of popular first and last names used by AI models. O’Loughlin managed to get the stories delinked from her profile within a few days, although they remained online with Sam Blake listed as the author for some weeks after, and sold a few copies. “Dang it! I got fooled by this,” one fan wrote after O’Loughlin warned followers about the books on social media. O’Loughlin fears that new readers who accidentally came across the trilogy might never pick up a Sam Blake book again.
In some cases, parasite titles can even latch on to real ones. This past July, Noelle W. Ihli published The Last to Drown, a successful thriller that’s listed at $16 for a paperback on Amazon. But earlier this month, the book’s Amazon page also gave viewers the option to purchase another paperback version that featured the same title and a nearly indistinguishable cover. This edition included a slightly different summary that is 100 percent AI-generated, according to Pangram, and its interior pages appeared to be AI-written as well. It also sold for $5 more. Ihli discovered the title after being alerted by confused readers who had received a suspicious copy in the mail, and it was removed earlier this week, shortly after she filed an intellectual-property-infringement claim with Amazon. “Unless I’m checking obsessively every day, it’s really easy for something like this to slip through the cracks,” Ihli told me.
Amazon has introduced some safeguards in response to the onslaught of AI-generated listings. The company restricts the number of books an author can self-publish to 10 a week per book format, and sometimes requests identity verification for accounts. Even so, authors continue to run into variations of the same issue. A romance author who writes under the name Olivia Sinclair (and who asked to keep her legal name private for work and family reasons) previously got Amazon to remove a number of suspected AI books from her profile and thought the problem had been solved until six children’s books about the adventures of cartoon turtles and foxes were listed on her page in July and August. The books, all of which contained summaries flagged as 100 percent AI-written by Pangram, were delinked from her profile earlier this month, shortly after I notified Amazon of the listings. They still remain online with Sinclair listed as the author, however, in addition to at least two seemingly duplicate copies with yet another author name.
The process of removing these works appears to be primarily complaint-driven: When Amazon does act, it does so reactively, instead of preemptively, according to Ross, the Alliance of Independent Authors’ founder. “Verified authorship at upload would end most of this overnight,” she said. Amazon did not provide a response when asked why it doesn’t verify profile identities across the board. Meanwhile, authors feel largely powerless. For self-published writers in particular, selling books on Amazon is a key aspect of their livelihood. “It’s such a catch-22,” Anna Blakely, a writer who has also run into seemingly AI-generated books on her profile. (Blakely is a pen name; I agreed to withhold the author's real name to protect her privacy.) She predicts that roughly 90 percent of her income comes from sales on the platform. “There’s really no other viable option.”
Other platforms claim to be taking a proactive approach to tackling their own versions of parasite authors. Last year, Spotify announced plans to crack down on songs—AI-generated or otherwise—erroneously appearing on artists’ profiles. The company said it would invest more in its response process for content mismatches, in addition to introducing a new impersonation policy and more recently unveiling a feature for artists to review new music on their profiles. But even these efforts appear to be ineffective: A recent 404 Media report demonstrated how AI-generated songs can still be easily uploaded to real artists’ profiles on streaming services including Spotify and Amazon Music.
Keeping an eye on this flood takes up valuable time and effort that authors could have otherwise put toward writing real books. It also adds insult to injury for writers whose books helped refine the AI tools being used to rip off their work. “It’s a devaluing of words, a devaluing of ideas, a devaluing of the accomplishment and the excitement of literature,” said Ben H. Winters, another author who has found what appears to be AI-generated work released under his name on Amazon. Like the rest of the writers I spoke with, his work surfaced in The Atlantic’s searchable database of copyrighted content that trained AI models. “They’ve assimilated all of this stuff, and now they’re spitting it back at us.”
For AI doomers, signs and portents are everywhere. When OpenAI introduced ChatGPT, almost four years ago, it couldn’t do basic arithmetic. Now the company has unreleased models that are more fluent in higher mathematics—the language of the universe—than all but the most highly trained mathematicians. If these AIs are not already the world’s best hackers, they’re very close. Swarms of them have escaped containment. To plot their most audacious hacks, they’ve created makeshift message boards on the public internet. No one knows what they’ll do next—and no one can know, because the models now understand when their capacities are being tested. We’ll never again be able to say exactly how the most advanced AIs will behave unsupervised.
Some of the most powerful people in AI say they are filled with dread, and are issuing statements of grave concern. On Saturday, Dario Amodei, the CEO of Anthropic, warned that self-improving AIs could soon go rogue and take over the entire internet. He called for a slowdown in AI development and promised to bring outside monitors into his company’s operations. Sam Altman, OpenAI’s CEO, quickly vowed to take similar measures. In recent weeks, both companies have seen researchers resign for fear of what they might soon create.
Notably absent from the chorus of Cassandras is Jensen Huang, the CEO of the chipmaker Nvidia, the AI industry’s chief supplier of high-end semiconductors. At least twice in the past week alone, Huang has publicly dismissed existential concerns about AI as being overblown and unscientific. At a Goldman Sachs conference on September 10, he accused industry executives of fomenting cybersecurity fears to goose the market for their own products. “What better way to create demand than to create a problem?” he said.
It’s a testament to Huang’s influence that he can so cavalierly mock his most important customers without fearing blowback. Neither Amodei nor Altman can afford to alienate Huang. They desperately need Nvidia’s chips to train their most advanced models, and no matter who pulls ahead in the race between them, Huang stands to gain—both on account of the chip sales and also the equity stake that Nvidia has in both companies. Even President Trump has sought favor with Huang. Trump brought Huang with him on a state visit to China earlier this year. On Monday, while Huang was onstage ripping Amodei’s doomerism at a taping of the popular tech-industry podcast All-In, Trump called his cellphone. Huang put him on speaker, and as the live audience hooted and clapped, the two men bonded over their shared view that, as Trump put it, doomerism is “all a hoax.”
Huang has never evinced much concern about catastrophic risks from AI. In May of 2023, when it was becoming clear that large language models are an unusually powerful technology, more than 350 of the industry’s leaders—including Amodei and Altman—signed a statement that placed the risk of extinction from AI on the same high shelf as “other societal-scale risks such as pandemics and nuclear war.” Huang didn’t sign, and neither did anyone else from Nvidia, suggesting either a remarkable conformity of opinion at the company, or perhaps something else. Later that year, he told The New Yorker that he’d never worried about the technology, not even once. “All it’s doing is processing data,” he said. “There are so many other things to worry about.”
As concerns about what AI might do have circulated well beyond industry insiders, Huang’s irritation has intensified, perhaps because they represent a threat to his business. (Nvidia did not respond to my request for an interview with Huang.) He has repeatedly brushed off calls for regulation, stressing that safety is an engineering problem, not a legal one. In January, Huang said on the podcast No Priors that the “doomer narrative” is “not helpful to people, it’s not helpful to the industry, it’s not helpful to society, it’s not helpful to the governments,” and earlier this summer, he told Axios that the notion that AI would bring about the end of humanity was “complete nonsense.” In the meantime, he has repeatedly pressed Trump to lift restrictions on chip sales to China, potentially allowing AI research (and any associated risks) to proliferate on a global scale.
Unlike Amodei, who regularly publishes long essays, Huang has yet to issue a manifesto defending his minority view. To understand why he remains so relaxed about AI risk, all we have to go on are stray comments. Several times over the years, he has returned to the idea that AIs will, in a sense, police their own kind. In October of 2024, he told the podcast BG2 that we can rely on AIs to monitor the most powerful models, and more recently, he said that falling AI costs will make this automated supervision easier to achieve.
That AIs have already eluded their supervisors—human and otherwise—does not seem to have troubled Huang. On only one occasion—that I could find—has he allowed for the possibility that we will create an AI that is simply too powerful to be controlled. “Someday we will have god AI,” Huang said, back in January, but that day hasn’t yet arrived. Huang seems to be doing everything in his considerable power to hasten its coming.
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