Enlarge / A Google robot controlled by RT-2. (credit: Google)

On Friday, Google DeepMind announced Robotic Transformer 2 (RT-2), a "first-of-its-kind" vision-language-action (VLA) model that uses data scraped from the Internet to enable better robotic control through plain language commands. The ultimate goal is to create general-purpose robots that can navigate human environments, similar to fictional robots like WALL-E or C-3PO.

When a human wants to learn a task, we often read and observe. In a similar way, RT-2 utilizes a large language model (the tech behind ChatGPT) that has been trained on text and images found online. RT-2 uses this information to recognize patterns and perform actions even if the robot hasn't been specifically trained to do those tasks—a concept called generalization.

For example, Google says that RT-2 can allow a robot to recognize and throw away trash without having been specifically trained to do so. It uses its understanding of what trash is and how it is usually disposed to guide its actions. RT-2 even sees discarded food packaging or banana peels as trash, despite the potential ambiguity.

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Security researchers have unearthed a rare malware find: malicious Android apps that use optical character recognition to steal credentials displayed on phone screens.

The malware, dubbed CherryBlos by researchers from security firm Trend Micro, has been embedded into at least four Android apps available outside of Google Play, specifically on sites promoting money-making scams. One of the apps was available for close to a month on Google Play but didn’t contain the malicious CherryBlos payload. The researchers also discovered suspicious apps on Google Play that were created by the same developers, but they also didn’t contain the payload.

Advanced techniques

The apps took great care to conceal their malicious functionality. They used a paid version of commercial software known as Jiagubao to encrypt code and code strings to prevent analysis that can detect such functionality. They also featured techniques to ensure the app remained active on phones that had installed it. When users opened legitimate apps for Binance and other cryptocurrency services, CherryBlos overlaid windows that mimicked those of the legitimate apps. During withdrawals, CherryBlos replaced the wallet address the victim selected to receive the funds with an address controlled by the attacker.

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Meta's new Twitter competitor, Threads, is looking for ways to keep users interested after more than half of the people who signed up for the text-based platform stopped actively using the app, Meta CEO Mark Zuckerberg reportedly told employees in a company town hall yesterday. Threads launched on July 5 and signed up over 100 million users in less than five days, buoyed by user frustration with Elon Musk-owned Twitter.

"Obviously, if you have more than 100 million people sign up, ideally it would be awesome if all of them or even half of them stuck around. We're not there yet," Zuckerberg told employees yesterday, according to Reuters, which listened to audio of the event.

Third-party data suggests that Threads may have lost many more than half of its active users. Daily active users for Threads on Android dropped from 49 million on July 7 to 23.6 million on July 14, and then to 12.6 million on July 23, web analytics company SimilarWeb reported.

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Enlarge / Several examples of images generated using Stable Diffusion XL 1.0. (credit: Stable Diffusion)

On Wednesday, Stability AI released Stable Diffusion XL 1.0 (SDXL), its next-generation open weights AI image synthesis model. It can generate novel images from text descriptions and produces more detail and higher-resolution imagery than previous versions of Stable Diffusion.

As with Stable Diffusion 1.4, which made waves last August with an open source release, anyone with the proper hardware and technical know-how can download the SDXL files and run the model locally on their own machine for free.

Local operation means that there is no need to pay for access to the SDXL model, there are few censorship concerns, and the weights files (which contain the neutral network data that makes the model function) can be fine-tuned to generate specific types of imagery by hobbyists in the future.

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A US senator is calling on the Justice Department to hold Microsoft responsible for “negligent cybersecurity practices” that enabled Chinese espionage hackers to steal hundreds of thousands of emails from cloud customers, including officials in the US Departments of State and Commerce.

“Holding Microsoft responsible for its negligence will require a whole-of-government effort,” Ron Wyden (D-Ore.) wrote in a letter. It was sent on Thursday to the heads of the Justice Department, Cybersecurity and Infrastructure Security Agency, and the Federal Trade Commission.

Bending over backward

Wyden’s remarks echo those of other critics who say Microsoft is withholding key details about a recent hack. In disclosures involving the incident so far, Microsoft has bent over backwards to avoid saying its infrastructure—including the Azure Active Directory, a supposedly fortified part of Microsoft’s cloud offerings that large organizations use to manage single sign-on and multifactor authentication—was breached. The critics have said that details Microsoft has disclosed so far lead to the inescapable conclusion that vulnerabilities in code for Azure AD and other cloud offerings were exploited to pull off the successful hack.

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Enlarge / An AI-generated image of a slot machine in a desert. (credit: Midjourney)

On Thursday, OpenAI quietly pulled its AI Classifier, an experimental tool designed to detect AI-written text. The decommissioning, first noticed by Decrypt, occurred with no major fanfare and was announced through a small note added to OpenAI's official AI Classifier webpage:

As of July 20, 2023, the AI classifier is no longer available due to its low rate of accuracy. We are working to incorporate feedback and are currently researching more effective provenance techniques for text, and have made a commitment to develop and deploy mechanisms that enable users to understand if audio or visual content is AI-generated.

Released on January 31 amid clamor from educators about students potentially using ChatGPT to write essays and schoolwork, OpenAI's AI Classifier always felt like a performative Band-Aid on a deep wound. From the beginning, OpenAI admitted that its AI Classifier was not "fully reliable," correctly identifying only 26 percent of AI-written text as "likely AI-written" and incorrectly labeling human-written works 9 percent of the time.

As we've pointed out on Ars, AI writing detectors such as OpenAI's AI Classifier, Turnitin, and GPTZero simply don't work with enough accuracy to rely on them for trustworthy results. The methodology behind how they work is speculative and unproven, and the tools are currently routinely used to falsely accuse students of cheating.

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It has been a tough year for PC companies and companies that make PC components. Companies like Intel, AMD, and Nvidia have all reported big drops in revenue from the hardware that they sell to consumers (though the hardware they sell to other businesses is often doing better).

Microsoft contributed another data point to that trend today, with fourth-quarter 2023 financial results that showed modest growth (revenue up 8 percent year over year, from $51.9 billion to $56.2 billion), but no thanks to its consumer software and hardware businesses.

Revenue from the company's More Personal Computing division, which encompasses Windows licenses, Surface PCs and other accessories, Xbox hardware and software and services, and ad revenue, was down 4 percent year over year. This decrease was driven mostly by a drop in sales of Windows licenses to PC makers (down 12 percent because of "PC market weakness") and by reduced hardware sales (down 20 percent, though the company didn't say how much of this drop came from its accessory business and how much came from Surface PCs). Microsoft makes its own PCs and PC accessories and sells the software that most other PC makers use on their hardware, so when the entire PC ecosystem is doing poorly, Microsoft gets hit twice.

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Elon Musk's decision to rebrand Twitter as "X" wouldn't be complete without a change to the company's official Twitter account. The @X handle was already taken by a user who registered it over 16 years ago, but that wasn't much of an obstacle—Twitter simply took over the username and offered its longtime owner some merchandise but no monetary compensation.

San Francisco-based photographer Gene X Hwang was @X on Twitter from March 2007 until yesterday. "They just took it essentially—kinda what I thought might happen," Hwang told The Telegraph. "They did send an email saying it is the property of 'x' essentially."

Hwang confirmed to Ars today that "there was no financial compensation" offered to him. The company offered "to switch the @x account and its history/followers etc to a new handle once I select one that is available," Hwang told us. "They also offered some merch and to meet with the management team as well."

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Enlarge (credit: OpenAI)

On Tuesday, OpenAI released an official ChatGPT app for Android, now available in the Google Play Store in four countries: the US, India, Bangladesh, and Brazil, with more coming soon. As a client for OpenAI's language model family, the GPT-3.5 and GPT-4 models run on the cloud and provide results to your Android device. It also integrates OpenAI's Whisper model for speech recognition.

ChatGPT, launched in November, is a conversational AI language model interface. As an AI assistant, it can help with summarization, text composition, and analysis. OpenAI bills its use cases as a way to seek "instant answers," "tailored advice," "creative inspiration," "professional input," and "learning opportunities."

A series of images showing OpenAI's proposed uses of the ChatGPT Android app, taken from the Google Play Store. (credit: OpenAI)

However, as we've noted in the past, ChatGPT is occasionally prone to confabulation (that is, making things up)—especially the GPT-3.5 model—so it's not entirely trustworthy as a factual reference. It can come in handy as a way to analyze data you provide yourself, though, so long as you're familiar with the subject matter and can validate the results.

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Enlarge / The four companies say they launched the Frontier Model Forum to ensure "the safe and responsible development of frontier AI models." (credit: Financial Times)

Four of the world’s most advanced artificial intelligence companies have formed a group to research increasingly powerful AI and establish best practices for controlling it, as public anxiety and regulatory scrutiny over the impact of the technology increases.

On Wednesday, Anthropic, Google, Microsoft, and OpenAI launched the Frontier Model Forum, with the aim of “ensuring the safe and responsible development of frontier AI models.”

In recent months, the US companies have rolled out increasingly powerful AI tools that produce original content in image, text, or video form by drawing on a bank of existing material. The developments have raised concerns about copyright infringement, privacy breaches and that AI could ultimately replace humans in a range of jobs.

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Enlarge / Welcome aboard the orbital HQ, readers! (credit: Aurich Lawson | Getty Images)

Welcome back to our series on how Ars Technica is hosted and run! Last week, in part one, we cracked open the (virtual) doors to peek inside the Ars (virtual) data center. We talked about our Amazon Web Services setup, which is primarily built around ECS containers being spun up as needed to handle web traffic, and we walked through the ways that all of our hosting services hook together and function as a whole.

This week, we shift our focus to a different layer in the stack—the applications we run on those services and how they work in the cloud. Those applications, after all, are what you come to the site for; you’re not here to marvel at a smoothly functioning infrastructure but rather to actually read the site. (I mean, I’m guessing that’s why you come here. It’s either that or everyone is showing up hoping I’m going to pour ketchup on myself and launch myself down a Slip-'N-Slide, but that was a one-time thing I did a long time ago when I was young and needed the money.)

How traditional WordPress hosting works

Although I am, at best, a casual sysadmin, having hung up my pro spurs a decade and change ago, I do have some relevant practical experience hosting WordPress. I’m currently the volunteer admin for a half-dozen WordPress sites, including Houston-area weather forecast destination Space City Weather (along with its Spanish-language counterpart Tiempo Ciudad Espacial), the Atlantic hurricane-focused blog The Eyewall, my personal blog, and a few other odds and ends.

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Enlarge (credit: AMD)

A recently disclosed bug in many of AMD's newer consumer, workstation, and server processors can cause the chips to leak data at a rate of up to 30 kilobytes per core per second, writes Tavis Ormandy, a member of Google's Project Zero security team. Executed properly, the so-called "Zenbleed" vulnerability (CVE-2023-20593) could give attackers access to encryption keys and root and user passwords, along with other sensitive data from any system using a CPU based on AMD's Zen 2 architecture.

The bug allows attackers to swipe data from a CPU's registers. Modern processors attempt to speed up operations by guessing what they'll be asked to do next, called "speculative execution." But sometimes the CPU guesses wrong; Zen 2 processors don't properly recover from certain kinds of mispredictions, which is the bug that Zenbleed exploits to do its thing.

The bad news is that the exploit doesn't require physical hardware access and can be triggered by loading JavaScript on a malicious website (according to networking company Cloudflare). The good news is that, at least for now, there don't seem to be any cases of this bug being exploited in the wild yet, though this could change quickly now that the vulnerability has been disclosed, and the bug requires precise timing to exploit.

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For more than 25 years, a technology used for critical data and voice radio communications around the world has been shrouded in secrecy to prevent anyone from closely scrutinizing its security properties for vulnerabilities. But now it’s finally getting a public airing thanks to a small group of researchers in the Netherlands who got their hands on its viscera and found serious flaws, including a deliberate backdoor.

The backdoor, known for years by vendors that sold the technology but not necessarily by customers, exists in an encryption algorithm baked into radios sold for commercial use in critical infrastructure. It’s used to transmit encrypted data and commands in pipelines, railways, the electric grid, mass transit, and freight trains. It would allow someone to snoop on communications to learn how a system works, then potentially send commands to the radios that could trigger blackouts, halt gas pipeline flows, or reroute trains.

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Enlarge / An AI-generated image of a chatbot in front of library shelves. (credit: Benj Edwards / Stable Diffusion)

On Thursday, OpenAI announced a new beta feature for ChatGPT that allows users to provide custom instructions that the chatbot will consider with every submission. The goal is to prevent users from having to repeat common instructions between chat sessions.

The feature is currently available in beta for ChatGPT Plus subscription members, but OpenAI says it will extend availability to all users over the coming weeks. As of this writing, the feature is not yet available in the UK and EU.

The Custom Instructions feature functions by letting users set their individual preferences or requirements that the AI model will then consider when generating responses. Instead of starting each conversation anew, ChatGPT can now be instructed to remember specific user preferences across multiple interactions.

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Enlarge / AlmaLinux lets you build applications that work with Red Hat Enterprise Linux but can't promise the exact same bug environment. That's different from how they started, but it's also a chance to pick a new path forward. (credit: AlmaLinux OS)

I asked benny Vasquez, chair of the AlmaLinux OS Foundation, how she would explain the recent Red Hat Enterprise Linux source code controversy to somebody at a family barbecue—somebody who, in other words, might not have followed the latest tech news quite so closely.

"Most of my family barbecues are going to be explaining that Linux is an operating system," Vasquez said. "Then explaining what an operating system is."

It is indeed tricky to explain all the pieces—Red Hat, Red Hat Enterprise Linux, CentOS, CentOS Stream, Fedora, RHEL, Alma, Rocky, upstreams, downstreams, source code, and the GPL—to anyone who isn't familiar with Red Hat's quirky history, and how it progressed to the wide but disparate ecosystem it has today. And, yes, Linux in general. But Vasquez was game to play out my thought experiment.

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Enlarge / A Z16 Mainframe.

Mainframe computers are often seen as ancient machines—practically dinosaurs. But mainframes, which are purpose-built to process enormous amounts of data, are still extremely relevant today. If they’re dinosaurs, they’re T-Rexes, and desktops and server computers are puny mammals to be trodden underfoot.

It’s estimated that there are 10,000 mainframes in use today. They’re used almost exclusively by the largest companies in the world, including two-thirds of Fortune 500 companies, 45 of the world’s top 50 banks, eight of the top 10 insurers, seven of the top 10 global retailers, and eight of the top 10 telecommunications companies. And most of those mainframes come from IBM.

In this explainer, we’ll look at the IBM mainframe computer—what it is, how it works, and why it’s still going strong after over 50 years.

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Enlarge (credit: Aurich Lawson / Ars Technica)

Organizations that have yet to patch a 9.8-severity vulnerability in network devices made by Zyxel have emerged as public nuisance No. 1 as a sizable number of them continue to be exploited and wrangled into botnets that wage DDoS attacks.

Zyxel patched the flaw on April 25. Five weeks later, Shadowserver, an organization that monitors Internet threats in real time, warned that many Zyxel firewalls and VPN servers had been compromised in attacks that showed no signs of stopping. The Shadowserver assessment at the time was: “If you have a vulnerable device exposed, assume compromise.”

On Wednesday—12 weeks since Zyxel delivered a patch and seven weeks since Shadowserver sounded the alarm—security firm Fortinet published research reporting a surge in exploit activity being carried out by multiple threat actors in recent weeks. As was the case with the active compromises Shadowserver reported, the attacks came overwhelmingly from variants based on Mirai, an open source application hackers use to identify and exploit common vulnerabilities in routers and other Internet of Things devices.

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Enlarge / A World of Warcraft illustration from the Zleague.gg article on "Glorbo." (credit: Zleague.gg)

On Thursday, a Reddit user named kaefer_kriegerin posted a fake announcement on the World of Warcraft subreddit about the introduction of "Glorbo" to the game. Glorbo isn't real, but the post successfully exposed a website that scrapes Reddit for news in an automated fashion with little human oversight.

Not long after the trick post appeared, an article about Glorbo surfaced on "The Portal," a gaming news content mill run by Z League, a company that offers cash prizes for playing in gaming tournaments. The Z League article mindlessly regurgitates the Reddit post and adds nonsensical details. Its author, "Lucy Reed" (likely a fictitious name for a bot), authored over 80 articles that same day.

A screenshot of the bot-written article about "Glorbo" that appeared on Z League's website before being taken down. (credit: Ars Technica)

Members of the World of Warcraft subreddit recently noticed that this kind of automated content scraping of Reddit has been taking place, prompting several of them to try to game the bots and get their posts featured on sites like The Portal.

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"When checking the system this morning, I noticed your account logged in for over 20 hours," begins a December 1998 email from the president of my dial-up Internet service provider (ISP) at the time. "Our service is unlimited, but we ask that you actually be using the connection while logged in."

Today, when it seems like everyone is online 24/7 through smartphones and broadband, I'd be weird if I wasn't online for 20 hours straight. But 1998 in Raleigh, North Carolina, was different. In an age of copper telephone lines and dial-up modems, Internet access wasn't usually an always-on situation for a home user in the US. Each occupied telephone line meant another ISP customer couldn't use it—and no one could call you, either.

But I'm getting ahead of myself—why do I have an email from 1998?

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Two years ago, ransomware crooks breached hardware-maker Gigabyte and dumped more than 112 gigabytes of data that included information from some of its most important supply-chain partners, including Intel and AMD. Now researchers are warning that the leaked information revealed what could amount to critical zero-day vulnerabilities that could imperil huge swaths of the computing world.

The vulnerabilities reside inside firmware that Duluth, Georgia-based AMI makes for BMCs (baseboard management controllers). These tiny computers soldered into the motherboard of servers allow cloud centers, and sometimes their customers, to streamline the remote management of vast fleets of computers. They enable administrators to remotely reinstall OSes, install and uninstall apps, and control just about every other aspect of the system—even when it's turned off. BMCs provide what’s known in the industry as “lights-out” system management.

Lights-out forever

Researchers from security firm Eclypsium analyzed AMI firmware leaked in the 2021 ransomware attack and identified vulnerabilities that had lurked for years. They can be exploited by any local or remote attacker with access to an industry-standard remote-management interface known as Redfish to execute malicious code that will run on every server inside a data center.

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