Automated Tire, Inc. unveils SmartBay, an AI-powered robotic tire change platform that handles mounting, balancing and inspections with minimal human intervention.

ID.me is a private identity verification company used across U.S. government sites. Here's what to know about its security, privacy tradeoffs and common scams to avoid.

Delivering much information about the scale of what's coming, documentary also follows Gawdat's campaign to get the programs with empathy A nother day, another warning about AI; vis-a-vis the reality we all know, this has roughly the same reassuring effect as a plane fuselage ripping off mid-flight. Starting off with familiar criticisms, such as putting the world out of work and handing over power to tech barons, Alex Holmes and Lina Zilinskaite's film blasts an concentrated stream of AI concerns in its 83-minute runtime. By the time it is talking about current efforts to create computers out of human brain cells, potentially integrable into our own craniums, and implying this might be a good thing, it is (ironically) hard to know how to process all of this. The Cassandra at the film's centre is Mo Gawdat, former chief business officer at Google X, now a touring cautionary voice trying to get the world to listen about the perils of AI. Once overseeing advanced projects for the tech giants, his biggest moonshot lies ahead: to introduce a moral dimension into a tech race that looks increasingly like the frenzied season finale of late capitalism. He talks about feeling parental pride in watching Google's AI-driven robotic arms learn to grasp objects, as children do.

The configuration process is outdated. Google Home did not recognize the projector on my network. Ultrashort-throw (UST) projectors offer more flexibility than traditional (long-throw) models. No one can ever step in front of one and block the projection, since the unit doesn't require distance and can sit up close to the screen rather than at the back of the room. This also lets all your streaming gear, a soundbar, and a game console connect close to the screen.

Ahead of the hit show's finale, cocreators Paul W. Downs and Lucia Aniello talk about media consolidation, the perils of censorship, and why they find AI "deeply disturbing." If you're a WIRED reader who uses AI in any creative context, I'd suggest staying far, far away from anyone involved in the TV show . In an interview earlier this year, actor Hannah Einbinder (who plays young comedy writer Ava Daniels on the show) described AI creators as "losers," "not artists," and "not special." In a wide-ranging conversation for ahead of the series finale on HBO Max, Paul W. Downs and Lucia Aniello were resolute about the value of human creativity--and what can be lost when AI enters the picture. If their work on is any indication, Downs and Aniello (along with their third cocreator, Jen Statsky) would be wise to stick with the tough, tiring, absolutely-no-shortcuts approach they take to making entertainment. Across five excellent seasons--if you haven't seen the show, I really do recommend it-- has been praised for its sharp writing and wit, and its thoughtful portrayal of Deborah Vance and Ava's complex, constantly evolving relationship. The show has also acted as something of a mirror for the real-world entertainment industry, weaving in plotlines that tackle everything from media consolidation to corporate censorship to, yes, artificial intelligence. The show's cast and creators have been on a media whirlwind as it all comes to an end. When they came knocking on WIRED's door, we jumped at the chance to chat, and I was lucky enough to spend an hour with Downs and Aniello--both WIRED subscribers, much to my delight--earlier this month. KATIE DRUMMOND: Lucia Aniello and Paul Downs, who I just learned are married, congratulations and welcome to . You should have been there. You should have been there. Ugh, why didn't we bring you? We are going to renew for our 10-year at the same place though. Lucia was born in Italy, so it was closer to a lot of family. And you were married in what year? You have time to find your look. A major priority for me in my life is perfecting my look. We do work at Condé Nast, and my boss is Anna Wintour.

Digg is back again and has taken on yet another form: A website that aggregates news about artificial intelligence. Digg's job is to find that signal and bring it to you. AI is just the beginning, he said, calling it the noisiest, fastest-moving space on the internet. He promised that more verticals are coming, but he didn't say when Digg will start aggregating news about other topics. At the moment, the website follows 1,000 people directly involved in AI research, investing and media, built from X's social graph.

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For screenwriters like me--and job seekers all over--AI gig work is the new waiting tables. In eight months, I've done 20 of these soul-crushing contracts for five different platforms. My name on the platform is ri611. I work as an AI trainer. I assess whether a chatbot's tone is natural or flat, affected or annoying. I identify patterns in pictures of furniture; search the internet for group photos of strangers whom I'll eliminate from the portrait, one by one. I trawl through bizarre videos so I can annotate and time-stamp the barking of a dog, the moment a stranger walks past a window, the precise millisecond a balloon pops. I generate anime sex scenes and decapitate young women, coax LLMs into giving me recipes for bombs made of household items, and generate invites to a reprise of January 6 at the White House, all as part of a red team whose purpose is to test safety precautions and probe weaknesses. I work for companies with names like Mercor and Outlier and Task-ify and Turing and Handshake and Micro1. In my "other" career, I am a Hollywood writer and showrunner. I create prime-time TV, usually featuring a middle-class white lady having the worst day of her life, with some salt-of-the-earth police interference to raise the stakes. You can find my shows on Paramount and Hulu and the BBC.

The classic multi-armed bandit (MAB) problem tackles the challenge of accruing maximum reward while making decisions under uncertainty. However, in applications, often the goal is to minimize cost subject to a constraint on the minimum permissible reward, an objective captured by multi-armed bandits with cost-subsidy (MAB-CS). Of interest to this paper is the setting where the quality (reward) constraint is specified relative to the unknown best reward and the cost of each arm is known. We characterize the expected sub-optimal samples required by any policy by proving instance-dependent lower bounds that offer new insight into the problem and are a strict generalization of prior bounds. Then, we propose an algorithm called Cost-Ordered Feasibility (COF) that leverages our insight and intelligently combine samples from all arms to gauge the feasibility of a cheap arm. Thereafter, we analyze COF to establish instance-dependent upper bounds on its expected cumulative cost and quality regret, i.e., relative to the cheapest feasible arm. Finally, we empirically validate the merits of COF, comparing it to baselines from the literature through extensive simulation experiments on the MovieLens and Goodreads datasets as well as representative synthetic instances. Not only does our paper develop qualitatively better theoretical regret upper bounds, but COF also convincingly demonstrates improved empirical performance.

Flytrex has partnered with Little Caesars to deliver full pizza orders by drone in Wylie, Texas, with food arriving in roughly four and a half minutes.