THE ATLANTIC – Technology | Internet & Technology

Last summer, a friend called bearing bad news: Her two-year relationship was finished. In between insisting that she was, in fact, totally fine, and that everything was probably for the best, she told me that her (now ex-) partner had accused her of cheating.My friend had not, to be clear, slept with anybody else, or gone on any illicit dates. But her partner, consumed by suspicion when it came to my friend’s platonic relationships, had gone through my friend’s phone and stumbled upon old messages that were too affectionate, too “flirty.” She broke up with my friend that night.Some people might feel sympathetic toward my friend’s ex. Others might find the entire ordeal, to use the technical term, absurd. Whatever the stance, a growing number of mental-health influencers are giving language to the debate: What my friend did, they say, was “micro-cheating.”As with plain old infidelity, micro-cheating is tricky to define; behavior that is fair game to one person might be egregious treachery to another. Many people have attempted to catalog it anyway. According to a number of lifestyle publications, a micro-cheater could be someone who, while in a relationship, maintains an active Hinge profile or sends explicit pictures to another person. Or, they could have done something that might otherwise seem banal: “liking” someone else’s Instagram post, perhaps, or messaging a colleague about something other than work. In a Vogue article advising readers on how to properly recognize a micro-cheater, a couples therapist concluded that micro-cheating could be anything, really: “a glance, a laugh, or non-sexual touching that’s too familiar or intimate.”[Read: Why happy people cheat]Whether something amounts to cheating is ultimately up to the people in a relationship to decide. But with micro-cheating, the general consensus seems to be that the cheating has nothing to do with a glaring physical transgression. (The prefix, micro, does a lot of work here.) It is defined by subtlety and generally takes place digitally. For some of my friends, the celebrities a romantic partner follows can be just as big a dealbreaker as parenting or financial choices—following Instagram models, in their calculus, fundamentally reveals as much about long-term compatibility as a poker addiction. To catch micro-cheaters, people often hunt for indiscretions: scrolling through the entire list of accounts that their partner follows, or watching for a partner’s single like on another person’s Instagram post. What appear to be gray-area online behaviors, the… [TheTopNews] Read More.

On March 10, the journalist Emanuel Fabian reported on a missile that had been launched from Iran. The warhead hit an open area outside Jerusalem, which Fabian confirmed by speaking with rescue services and reviewing footage of the explosion. He wrote a short post on The Times of Israel’s live blog and moved on.Meanwhile, gamblers had wagered millions on the unfolding events of the conflict. Fabian’s post became the subject of a major dispute on Polymarket, a popular prediction market where people can bet on the outcome of almost anything. The site had allowed users to guess when Iran would initiate “a drone, missile, or air strike on Israel’s soil”: More than $14 million was riding on whether such an attack had happened March 10.[Read: America is slow-walking into a Polymarket disaster]People started reaching out asking Fabian to change his article. Some argued that Israel Defense Forces had not officially mentioned such an attack occurring on that day, and others said that the explosion he had reported was the result of a missile being intercepted, which according to Polymarket’s terms wouldn’t count as a strike “on Israel’s soil.” Confident in his reporting, Fabian did not amend the text.And then he began receiving threats. “You will discover enemies who will be willing to pay anything to make your life miserable—within the framework of the law,” one person wrote to Fabian before adding, “As far as I know, there are also some people who don’t really care about the law, and you’re going to make them lose about 50 times what you’ll ever make.” Much as athletes have faced threats and harassment from fans with money riding on a game, prediction markets are now creating incentives for gamblers to target all manner of people with inside information or some influence over major events. Polymarket did not respond to my request for comment, but wrote on X: “This behavior violates our Terms of Service & has no place on our platform. We’ve banned the accounts for all involved & will pass their info to the relevant authorities.”[Read: A technology for a low-trust society]Prediction markets like Polymarket post online using the language of news wires and position themselves as a new and unbiased source of information, yet this story suggests that these sites are having the opposite effect: They make it harder for news gatherers to report the truth. Yesterday, Fabian spoke with me… [TheTopNews] Read More.

In a certain, strange way, generative AI peaked with OpenAI’s GPT-2 seven years ago. Little known to anyone outside of tech circles, GPT-2 excelled at producing unexpected answers. It was creative. “You could be like, ‘Continue this story: The man decided to take a shower,’ and GPT-2 would be like, ‘And in the shower, he was eating his lemon and thinking about his wife,’” Katy Gero, a poet and computer scientist who has been experimenting with language models since 2017, told me. “The models won’t do that anymore.”AI leaders boast about their models’ superhuman technical abilities. The technology can predict protein structures, create realistic videos, and build apps with a single prompt. But these executives and researchers also readily admit that they have not yet released a model that writes well. OpenAI CEO Sam Altman has predicted that large language models will soon be capable of “fixing the climate, establishing a space colony, and the discovery of all of physics,” but in an October interview with the economist Tyler Cowen, he guessed that even future models—an eventual GPT-6 or GPT-7—might be able to extrude only something equivalent to “a real poet’s okay poem.”Today’s AI-generated prose is riddled with flaws. Chatbots produce meaningless metaphors, endless “it’s not this, but that” constructions, and a cloyingly sycophantic tone—and, of course, they overuse my beloved em dash. (Only starting with GPT-5.1, released in November, could ChatGPT reliably follow instructions to avoid the beleaguered punctuation mark.) I wanted to understand why this is—why large language models, which, after all, have memorized centuries of great literature, can demonstrate incredible emergent abilities yet totally fail to produce a single essay that I’d want to read.[Read: Would limitlessness make us better writers?]So I talked with people who would know: people who work at LLM companies, AI-data vendors, academic computer-science departments, and AI-writing start-ups. (Some spoke with me under the condition of anonymity because their employers barred them from speaking publicly about their work.) What I learned is that modern LLMs are built in a way that is antagonistic to great writing; they are engineered to be rule-following teacher’s pets that always have the right answer in hand. In many respects, they’ve come a long way from GPT-2, but they’ve also lost something that made them looser and more compelling.LLMs begin their lives as indiscriminate readers. During the pretraining phase, they ingest something like the entire internet—Reddit posts, YouTube… [TheTopNews] Read More.

The smell was strange. Sharp. Chemical. Wrong. The concrete wall was too close. My glasses were gone. One of my kids was standing on the sidewalk next to our car—not crying, just confused.The seat belt had held. The crumple zone had crumpled. The airbag had fired. Everything designed to protect bodies had done its job. But the car, a Tesla Model X, was totaled.One Sunday last fall, my kids and I were on a drive we’d done hundreds of times, winding through the residential streets of the Bay Area to drop my son off at his Boy Scouts meeting. The Tesla was in Full Self-Driving mode, driving perfectly—until it wasn’t.What happened next, I’ve had to piece together. My memory is hazy, and some of it comes from one of my sons, who watched the whole thing unfold from the back seat. The car was making a turn. Something felt off—the steering wheel jerked one way, then the other, and the car decelerated in a way I didn’t expect. I turned the wheel to take over. I don’t know exactly what the system was doing, or why. I only know that somewhere in those seconds, we ended up colliding with a wall.You might think I’d have known what to do in this situation. I used to run the self-driving-car division at Uber, trying to build a future in which technology protects us from accidents. I had thought about edge cases, failure modes, the brittleness hiding behind smooth performance. My team trained human drivers on when and how to intervene if a self-driving car made a mistake. In the two years I ran the division, we had no injuries in our early pilot programs.With my own Tesla, I started out using Full Self-Driving as the default setting only on highways. That’s where it makes sense: You have clear lane markers and predictable traffic patterns. Then, one day, I tried it on a local road, and it worked well enough to become a habit.Despite the accident, we were lucky. I walked away with a stiff neck, a concussion, a few days of headaches, and some memories I can’t shake. The kids climbed out unharmed. Still, you could say I was crushed in what the researcher Madeleine Clare Elish calls the moral crumple zone. Some parts of a car are specifically designed to absorb damage in a crash, to protect the people inside. But… [TheTopNews] Read More.

From the comfort of my desk, I can see it all. A series of webcam feeds show me the sun setting over Tel Aviv and southern Lebanon. A map of the world, flecked with red dots, indicates that most of Europe and the Middle East are on “high alert.” I toggle a button on the map’s control panel, and the globe is instantly latticed with the locations of undersea fiber-optic cables. Below the map, a live feed of Bloomberg TV is running with the chyron Oil Extends Rout on Stockpile Talks. I scroll down and am greeted by walls of headlines, grouped into categories such as “World News” and “Intel Feed.” A “country instability” meter clocks Iran at 100 percent, while a different widget informs me that the world’s “strategic risk overview” remains “stable” at 50, whatever that means.   I am looking at World Monitor, a website that turns any browser into a makeshift situation room, and I love it. Built to look like a cross between a Bloomberg terminal and a big screen at U.S. Strategic Command, the site aims to display as much information about world events as possible in an assortment of real-time feeds. This is information overload presented as intelligence.World Monitor was built over a single weekend in January by Elie Habib, an engineer based in the United Arab Emirates whose day job is as CEO of Anghami, one of the Middle East’s largest music-streaming services. “I wanted to extract the signal from the noise,” he told me recently. But what he really built, by his own admission, is a noise machine. Right now, the site pulls in more than 100 different streams of data, including stock prices, prediction markets, satellite movements, weather alerts, major-airport flight data, fire outbreaks, and the operational status of cloud services such as Cloudflare and AWS. The information is all real, but what exactly a person ought to do with it is unclear.When Habib posted about the project on X, he was shocked by the response. At one point, tens of thousands of people were using the site at the same time; more than 2 million people accessed it in the first 20 days. Habib’s inbox filled with requests for new features as well as messages from venture capitalists looking to spin up World Monitor into a full-time business. Via GitHub, where Habib has made the code for World Monitor open-source and… [TheTopNews] Read More.