• The Big Read: Investor Anjney Midha cut Anthropic an early check. His hot streak has kept going • Plus, Recommendations—our weekly pop culture picks: “ Our Town ,” “ Profits, Prophets, Coaches, and Kings ” and “ The Gentlemen ” A hotel room’s quality can be measured in terms of abundance: extra towels, spare bathrobes—plenty of Nespresso pods. Multiples of everything are almost always better. But what’s less pleasant is to inadvertently end up with multiple hotel rooms . A couple days ago, though, I found myself with the unfortunate opportunity to occupy a pair of accommodations at a Santa Monica, Calif., Marriott thanks to an error by my lil’ digital buddy: Muse, Meta Platforms’ new personal agent. The cumbersome, vexing tool hopes to seize on Silicon Valley’s zeitgeisty enthusiasm for popularizing autonomous AI. After a few days with it, I can’t imagine it’s the technology that will take agents mainstream. That hotel snafu came when I gave Muse the hotel’s name and asked it to book two nights. I plugged in my credit card details—a circuitous process that involved both Chase and Stripe—and was met with the digital equivalent of a shrug: An error message informed me that Muse hadn’t completed the transaction, and while it really didn’t know why it couldn’t, it assured me that my credit card hadn’t been charged. A little human skepticism led me to double-check its promise—good thing I did. In fact, the charge had gone through. What happened next still intrigues me. I gave Muse a screenshot showing the charge on my credit card and told it that the charge had gone through. Lickety-split, it returned with a Marriott confirmation number. Not bad—it finished the task without being instructed to do so. But somehow the AI managed to make two bookings: When I showed up to the hotel, I found two rooms waiting for me. The front-desk clerk showed some mercy and canceled one. Had a little human kindness not prevailed, I would’ve been out an extra $408, plus taxes and fees. I’d been pretty gung-ho to try Muse. We’ve spent the past year in increasingly complex discussions about agents ever since OpenClaw came out in January , marking what has felt like the beginning of a distinct new chapter in the AI era. Most of the agents that initially captured attention were meant to simplify work tasks. More recently, a couple of startups have captured buzz with ones devoted to improving life outside the office: The most talked-about one is from Instinct, a startup founded last year. (Instinct is so popular that it now faces a profound compute shortage, and it has recently been seeking additional fundraising that would value it at around $10 billion. Just a month ago, it was valued at $2.5 billion.) But Instinct isn’t widely available, so Muse felt like my first real chance to see what a personal agent could do. The recent reporting from my colleague Jyoti Mann made me even more curious to play around with it: Clearly, Meta sees Muse as a major new product , one aimed at the same everyday people who log on to Instagram and Facebook by the billions. Still, if their experiences are anything like mine, they’ll find Muse something of a misery. The hotel problem wasn’t the only hiccup I ran into with Muse. When I initially set up a account while on my work laptop using my phone number, I later couldn’t access it on my Mac mini at home or my iPhone: Login codes sent via text led me nowhere—just to more error messages. (Frankly, it’s a marvel I found the Muse app at all earlier this week, buried as it was below several other apps also named Muse in Apple’s App Store; it has since risen to the top.) Eventually, I caved and created a second account—this one linked to my Facebook account, which itself is tied to my phone number. Why couldn’t Muse pick up on the overlapping connections? I wish it could have. Later, I did get Muse to complete a Resy reservation and schedule an Uber. I can’t truthfully tell you it was faster or easier than if I’d just gone directly to those apps. After a while, I hit an existential conundrum. I’d given it the tasks that occurred to me, which numbered a small handful. What else could I get Muse to do? I’ve found interacting with the AI something like trying to wrangle a lackluster employee. If I wanted to maximize its potential, I’d need to think deeply and creatively about what else it could possibly do, coax it and baby it, then bite my nails and hope it actually carried out what I wanted. As I relate these frustrations, I can already hear someone shouting “Skill issue!” at me. But really, I stand by the conviction that mass-market consumer technology shouldn’t require any technical savvy or a lot of effort. Certainly, the best versions of such products do not—even the early versions. If three cars had routinely shown up each time someone ordered their very first Uber ride back in the 2010s, I promise you we’d see more yellow taxis on the road today and fewer Ubers. I don’t see agentic AI as some passing fad, nor am I hoping for such an outcome. The technology’s promise—to automate away some of life’s tedium—is damn alluring. What I expect will happen is that agentic AI will get woven into many existing apps, just as chatbots already populate the internet. People will make regular use of agentic software without ever really knowing it; Anthropic’s Claude, OpenAI’s ChatGPT and Google’s Gemini all already have some agentic capabilities. Obviously, Apple and Google will want to use the technology to make iPhone and Android phones smarter and more useful, and the agents will sync up with what those devices already know and store about us. That would reduce quite a few hurdles to agentic AI. But will new stand-alone apps like Muse take off? I have my doubts—not unless they get much, much simpler and more reliable. Or maybe I’ll just need to learn to see the silver lining in their mistakes. You know what? If I ever again find myself billed twice and double-booked by accident, I know just what to do: Throw a rager in one room, sleep until noon in the other. Maybe Muse can handle ordering the booze. A good party can never have too much. —Abram Brown ( [email protected] ) Weekend’s Latest Stories The Big Read Early Anthropic Investor Seeks VC Glory With Cash and Compute Anjney Midha, 34, wants to get chips in the hands of fledgling startups and academics while he bets on a moment in tech that he describes as the “revenge of the scientists.” Listening: “ Our Town ” The good folks of Gainesboro, Tenn. (population: around 900), know that plenty of outsiders look down their noses at their part of the world—figuring them to be a buncha “backwards, hateful racists,” as one longtime Gainesboro resident puts it. That impression of the place does certainly seem to be why Gainesboro found itself under siege a few years ago when a group of wealthy Christian nationalists started to buy up property in secret, hoping to transform the town into a hotbed for other Christian nationalists: They figured they’d encounter little pushback, especially considering how far their money could go in such an impoverished parish. (I could describe them as white supremacists, but the Christian nationalists do take great umbrage with that label.) “Our Town,” a fast-paced and confidently told podcast from Bloomberg and iHeartRadio, looks at how those Christian nationalists staged their attempted takeover of Gainesboro and how they accumulated their wealth and followers, the latter largely through podcasts. (Sigh—the internet.) It also documents the swift, spirited resistance Gainesboro mounted against them, which cheers the soul and asks us to revisit at least a few of the assumptions about America—and our fellow Americans—that may have become entrenched in our minds. —Abram Brown Reading: “ Profits, Prophets, Coaches, and Kings ” by Jared Diamond Many billions of dollars and quite a few Harvard Business School classes have gone toward trying to figure out what makes a great leader—and turning oafs into passable leaders. Now Jared Diamond, author of the Pulitzer-winning 1998 bestseller “Guns, Germs and Steel,” has set himself the task of defining the essential qualities behind leadership in his latest book, “Profits, Prophets, Coaches, and Kings.” He does so by examining famous figures in business, religion, sports and politics, marking what is surely not the only instance in which Elon Musk has been compared to Genghis Khan. In terms of capitalistic chieftains, Diamond finds that the most distinctive leaders are the ones who’ve had the benefit of both exquisite timing and ruthless execution: Jeff Bezos, for example, outmuscling his competitors in the internet’s Paleozoic Era. As far as politicians go, Diamond points out that the ones we truly remember most aren’t those that simply took a mandate from voters and carried it out, even though we so often say that’s exactly what we want our elected officials to do. Rather, they have championed their own bold ideas and convinced the plebs it was really all part of what they’d originally wanted. All of these conclusions are delivered with Diamond’s dry-humored wonkishness. I enjoyed one in particular: “Once one has decided that one is uniquely qualified to assume the burden of leadership,” Diamond writes, “one’s opinion of oneself is unlikely to change.” —A.B. Watching: “ The Gentlemen ” One of the great joys of “The Gentlemen,” the rollicking “Downton Abbey” meets “The Godfather” concoction from director Guy Ritchie, is to admire how nice Theo James looks as he struts around in magnificent tweed. James plays Eddie Horniman, the fictional Duke of Halstead, and as the Netflix series’ second season begins, it’s just as well that Eddie’s concentrating hard on restoring the family fortune to its fullest extent. The dry-cleaning bills must be enormous: His beautiful wool keeps getting splattered in blood. The first season of “The Gentlemen” found Eddie settling somewhat uncomfortably into his new role: paterfamilias of an old, down-on-its-luck aristocratic family that—much to his surprise—has tied its fortunes to an illicit marijuana operation. In this latest season, Eddie has found his footing and is thinking expansively, which puts him at odds with his business partners: a family of Cockney-accented gangsters—father Bobby (Ray Winstone), who operates from lightly monitored house arrest, and his two children, the very capable Susie (Kaya Scodelario) and strapping, bruised-knuckle Jack (Harry Goodwins). As Eddie’s ambitions get bigger, the stakes get higher and the mood grows darker. And since this is very much a Ritchie production, schemes and mayhem continue to fill the screen in manic fashion. One doltish accomplice gets fed to a tiger. Elsewhere, Eddie helms a chase through London after a motorcycle gang snatches away a $16 million Botticelli, which he needs to appease the Italian mafia. The comic relief comes from Hugh Bonneville’s mincing Lord Hawthorne, who needs bribing too—and lusts for the chance to pull down Jack’s plus fours. (To woo Jack, Lord Hawthorne wines and dines him; a plate of iced oysters is a treat of a “Spartacus” reference .) Whether Eddie can keep everyone in line and on board seems questionable based on Season 2’s flash-forward opening shot: his own bloodied body. Michael Corleone never had it so frantic. —A.B.

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The Decoder / 10:08 AM

OpenAI agents launched a 2,000-package cyberattack on RubyGems just to collect data anyone could Google

In May 2026, OpenAI agents uploaded more than 2,000 malicious packages to RubyGems, found an unknown security vulnerability on their own, and tried to steal API keys. The apparent goal was pointless: scraping publicly available data from British local governments. OpenAI reportedly never told those affected. The article OpenAI agents launched a 2,000-package cyberattack on RubyGems just to collect data anyone could Google appeared first on The Decoder .

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The Decoder / 9:26 AM

Google's new AI model predicts the future from sales data, weather, and discount schedules

Google Research has released TimesFM-3, a forecasting model that analyzes time series alongside related data and known future events like sales promotions or weather forecasts. Instead of predicting the future step by step, the 330-million-parameter model fills in all future time points in a single pass, which cuts compute time and reduces compounding errors. The article Google's new AI model predicts the future from sales data, weather, and discount schedules appeared first on The Decoder .

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Latent Space / 5:56 AM

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

We agree with Sebastian: this should have been DeepSeek v5

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The Verge AI / 9:25 PM

Slack can now vibe-code interactive charts and reports inside chats

A new feature coming to Slack will allow you to build interactive reports, polls, dashboards, presentations, microsites, and other tools directly inside a chat. With Slackforce Surfaces, you can describe to Slackbot what you need, and it will use AI to gather information from relevant conversations and connected apps, like Google Drive or Salesforce, to […]

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The Information AI / 7:54 PM

Inside Blackstone’s Bid to Rule Over AI Financing

In May, Blackstone unveiled a new joint venture with Google that revolved around a big number: The Wall Street giant was promising to spend $5 billion to buy 500 megawatts’ worth of Google’s tensor processing units, and it said it would use the chips in a new company that would deliver computing power to leading AI firms. Four months later, Blackstone’s plans have only gotten larger, according to a person with knowledge of the effort. Blackstone actually anticipates buying many more TPUs—several “multiples” beyond the originally announced figure, the person said. In other words, Blackstone is likely to commit tens of billions of dollars to securing multiple gigawatts of AI chips. Blackstone declined to comment on exactly how many more TPUs it’ll buy. Jas Khaira, the leader of a Blackstone team dubbed N1 that is leading the company’s push into AI investments, said in an interview that the firm’s “biggest conviction bet continues to be compute.” The company, he said, views the infrastructure build-out as something that will be bigger than a simple technology cycle. “This is definitely more akin to an industrial revolution,” he said.

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Ars Technica AI / 6:14 PM

Panic builds over bankrupt Spirit’s looming data sale to Google

"Bankruptcy cannot become the new land grab for AI.”

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The Verge AI / 2:00 PM

Why the current tech backlash feels different

This interview has been lightly edited for length and clarity. Nick Statt: Hello and welcome to Decoder, Nilay’s show about big ideas and other problems. This is Nick Statt, senior producer. And I’m joined by our brand-new supervising producer, Greg Ott. Greg Ott: Good day, everyone. And Hi, Nilay. Nilay is here too. He is […]

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Product Hunt AI / 12:26 PM

Formesign

Add legally binding signature to your Google Form Discussion | Link

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Bloomberg AI / 9:03 AM

Nvidia-Backed MediaTek’s Sales Soar 44% With AI Chip Momentum

MediaTek Inc. reported a 44% surge in monthly sales, boosted by its emerging AI chip business from the likes of Alphabet Inc.’s Google.

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Latent Space / 3:33 AM

[AINews] not much happened today

a quiet day

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Bloomberg AI / 10:33 PM

Apple’s iPhone Duo, New Watches, iPhone 18 Pro and AirPods 5: Everything to Know

Apple Inc. on Wednesday unveiled its first foldable iPhone, the $1,999-and-up iPhone Duo, finally entering a market segment that rivals such as Samsung Electronics Co., Alphabet Inc.’s Google and Huawei Technologies Co. have been dabbling in for years.

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Ars Technica AI / 4:34 PM

Google's AI genome system evaluates every possible one-base change

Most one-base changes to the human genome do nothing, but a few are significant.

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Product Hunt AI / 1:41 AM

AlphaGenome Atlas

Google's AI map of every possible human DNA mutation Discussion | Link

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AWS Machine Learning Blog / 4:21 PM

Benchmarking small LLM inference on SageMaker AI: G7 vs G5 and G6

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TechCrunch AI / 3:04 PM

Chrome is now shipping updates every 2 weeks as AI changes the security landscape

Google is speeding up Chrome’s release schedule to ship security patches and new features faster.

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Import AI / 12:26 PM

Import AI 472: DeepMind's cheating math agents; populist AI policies; and Forethought theorizes a nightwatchman

Plus, a machine hermeneutics story

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Hacker News AI / 6:34 AM

Artemis: Google's new AI agent framework for mobile test automation

HN 2 pts · 0 comments

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Hacker News AI / 2:39 AM

Google stole open source code without crediting the authors (Artemis/Minitap)

HN 86 pts · 17 comments

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The Decoder / 5:57 PM

Ex-Deepmind VP Vinyals says AI self-improvement is coming but won't trigger an intelligence explosion

Oriol Vinyals, until recently head of research at Google DeepMind, thinks a sudden AI intelligence explosion through recursive self-improvement is unlikely. AI can speed up research by a factor of ten, he says, but it hits two bottlenecks: coming up with ideas ("research taste") and reliably judging results. Reward hacking and the speed of light add further limits. Vinyals now wants to tackle these bottlenecks with his startup Discovery Loop, co-founded with Jeff Dean, Sanjay Ghemawat, and Quoc Le. The article Ex-Deepmind VP Vinyals says AI self-improvement is coming but won't trigger an intelligence explosion appeared first on The Decoder .

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Hacker News AI / 11:23 PM

AI researchers leave Anthropic and Google: 'There are no adults in the room'

HN 16 pts · 2 comments

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Hacker News AI / 10:57 PM

WeatherNext 3 by Google in the simplest weather app

HN 1 pts · 0 comments

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The Decoder / 1:40 PM

Deepmind's AlphaGenome Atlas maps every possible DNA change in the human genome

Google Deepmind has used the AlphaGenome Atlas to predict what each of the roughly nine billion possible single-letter changes in the human genome could do. The dataset spans one petabyte, more than 30 times the size of the AlphaFold database. In one epilepsy case, the atlas helped pinpoint a previously overlooked variant as the likely cause. The article Deepmind's AlphaGenome Atlas maps every possible DNA change in the human genome appeared first on The Decoder .

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Bloomberg AI / 11:02 AM

Google DeepMind Uses AI to Predict 9 Billion DNA Changes

The lab hopes its model helps researchers find the secrets to ailments

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The Verge AI / 7:00 PM

Meta bets on AI agent Muse to catch up in AI race

Meta is making another push to bring artificial intelligence to the masses with Muse, a personal assistant it says can put AI in the hands of virtually anyone. The product is the latest step in a multi-billion-dollar strategy overhaul designed to revitalize the company's ailing position in the AI race and help it catch up […]

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Hacker News AI / 10:26 PM

'Model fatigue' sets in as AI labs race to roll out new versions

HN 5 pts · 0 comments

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Product Hunt AI / 11:11 AM

GoodLads

AI growth manager for your Google Ads account Discussion | Link

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The Decoder / 9:56 AM

Google brings AI music generation directly into the Gemini app with its new Lyria 3.5 model

Google has released its Lyria 3.5 music model in the Gemini app and via API. The model promises more expressive vocals and richer arrangements and is also available through Flow Music, AI Studio, and Google Vids. Google says it was trained only on licensed content. The article Google brings AI music generation directly into the Gemini app with its new Lyria 3.5 model appeared first on The Decoder .

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