AI – Page 12

OnePlus is the latest smartphone maker to go all-in with AI

AI, Artificial Intelligence, OnePlus, smartphones, Tech / Beth Washington / May 27, 2025

OnePlus thrives on trends—if other smartphone makers are doing something, you can bet OnePlus is going to have a take. The company recently confirmed it’s ditching the storied alert slider in favor of an Apple-like shortcut button called the Plus Key, and that’s not the only trend it’ll chase with its latest phones. OnePlus has also announced an expanded collection of AI features for translation, photography, screen capture, and more. OnePlus isn’t breaking new ground here, but it is cherry-picking some of the more useful AI features we’ve seen on other phones.

The OnePlus approach covers most of the established AI use cases. There will be AI VoiceScribe, a feature that records and summarizes calls in popular messaging and video chat apps. Similarly, AI Call Assistant will record and summarize phone calls, a bit like Google’s Pixel phones. However, these two features are India-only for now.

Globally, OnePlus users will get AI Translation, which pulls together text, voice, camera, and screen translation into a single AI-powered app. AI Search, meanwhile, allows you to search for content on your phone and in OnePlus system apps in a “conversational” way. That suggests to us it’s basically another chatbot on your phone, like Motorola’s Ask and Search feature, which we didn’t love.

OnePlus also promises some AI smarts in the camera. AI Reframe will analyze what’s in your viewfinder and suggest different framing options. AI Best Face 2.0 (which will roll out later this summer) will analyze and correct things like closed eyes or “suboptimal expressions.” This sounds like a OnePlus version of Google’s Best Take, but we’re not complaining—that’s a great feature. The OnePlus can work with group shots of up to 20 people, and you can even feed it photos taken on other phones to fix everyone’s face.

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After Mr. Deepfakes shut down forever, one creator could face a $450K fine

AI, australia, deepfake porn, Deepfakes, defamation, nudify apps, Policy, take it down act / Mike M. / May 27, 2025

“Get an arrest warrant if you think you are right,” Rotondo reportedly told officials prior to the sanctions hearing, the Brisbane Times reported.

Later, in front of the judge, he unsuccessfully argued that he didn’t intend to out his victims by email. He claimed he didn’t know the court order was attached to the email or that it contained his victims’ names, The Guardian reported.

“The email I received had more than 80 pages of writing,” Rotondo said. “I didn’t read all the pages. I just forwarded the email.”

Eventually, Rotondo gave police his passwords to delete the images posted on Mr. Deepfakes. But the judge noted that Rotondo appeared resistant to removing deepfakes and continued creating an unknown number of deepfakes—which may include further charges from Queensland police that he possibly targeted “a number” of facilities and businesses on the day he allegedly hit the high school. He perhaps was motivated to leave the images online, as toxic Mr. Deepfakes uploaders could earn as much as $1,500 for convincing non-consensual deepfakes of public figures.

“The history of the matter suggests that, were he still at liberty and perhaps in another country, he would not have been so accommodating,” Derrington said.

Australia seeks to end “incalculable devastation”

Governments globally are grappling with a stark rise in non-consensual deepfake porn, with an ever-widening lens that targets not just the people who create and share images or the sites that host and sell them, but also the social media platforms that don’t catch and delete the harmful content. Earlier this month, the US passed a law threatening heavy fines and prison time for platforms that don’t remove the images when they’re reported. Under that law, the Take It Down Act, Wired reported that platforms risk roughly $50,000 in penalties per violation if deepfakes aren’t removed within 48 hours of receiving a report.

In Australia, Inman Grant wants to find a way to end the “lingering and incalculable devastation” that she said predominantly female victims must endure because it’s “shockingly” free and easy to use “thousands of open-source AI apps” to make deepfake porn.

Because Rotondo seems to represent the kind of unapologetic repeat deepfaker who digs his heels in to defend his AI-generated fake sex images, Inman Grant asked for the maximum penalties on Monday. The eSafety commission’s spokesperson told The Guardian that the request “reflected the seriousness of the breaches” and “the significant impacts on the women targeted.”

“The penalty will deter others from engaging in such harmful conduct,” the spokesperson said.

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Researchers cause GitLab AI developer assistant to turn safe code malicious

AI, Artificial Intelligence, Biz & IT, chatbots, large language models, Security / Beth Washington / May 24, 2025

Marketers promote AI-assisted developer tools as workhorses that are essential for today’s software engineer. Developer platform GitLab, for instance, claims its Duo chatbot can “instantly generate a to-do list” that eliminates the burden of “wading through weeks of commits.” What these companies don’t say is that these tools are, by temperament if not default, easily tricked by malicious actors into performing hostile actions against their users.

Researchers from security firm Legit on Thursday demonstrated an attack that induced Duo into inserting malicious code into a script it had been instructed to write. The attack could also leak private code and confidential issue data, such as zero-day vulnerability details. All that’s required is for the user to instruct the chatbot to interact with a merge request or similar content from an outside source.

AI assistants’ double-edged blade

The mechanism for triggering the attacks is, of course, prompt injections. Among the most common forms of chatbot exploits, prompt injections are embedded into content a chatbot is asked to work with, such as an email to be answered, a calendar to consult, or a webpage to summarize. Large language model-based assistants are so eager to follow instructions that they’ll take orders from just about anywhere, including sources that can be controlled by malicious actors.

The attacks targeting Duo came from various resources that are commonly used by developers. Examples include merge requests, commits, bug descriptions and comments, and source code. The researchers demonstrated how instructions embedded inside these sources can lead Duo astray.

“This vulnerability highlights the double-edged nature of AI assistants like GitLab Duo: when deeply integrated into development workflows, they inherit not just context—but risk,” Legit researcher Omer Mayraz wrote. “By embedding hidden instructions in seemingly harmless project content, we were able to manipulate Duo’s behavior, exfiltrate private source code, and demonstrate how AI responses can be leveraged for unintended and harmful outcomes.”

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Google Home is getting deeper Gemini integration and a new widget

AI, Artificial Intelligence, Google, Smart Home, Tech / Kelly Newman / May 24, 2025

As Google moves the last remaining Nest devices into the Home app, it’s also looking at ways to make this smart home hub easier to use. Naturally, Google is doing that by ramping up Gemini integration. The company has announced new automation capabilities with generative AI, as well as better support for third-party devices via the Home API. Google AI will also plug into a new Android widget that can keep you updated on what the smart parts of your home are up to.

The Google Home app is where you interact with all of Google’s smart home gadgets, like cameras, thermostats, and smoke detectors—some of which have been discontinued, but that’s another story. It also accommodates smart home devices from other companies, which can make managing a mixed setup feasible if not exactly intuitive. A dash of AI might actually help here.

Google began testing Gemini integrations in Home last year, and now it’s opening that up to third-party devices via the Home API. Google has worked with a few partners on API integrations before general availability. The previously announced First Alert smoke/carbon monoxide detector and Yale smart lock that are replacing Google’s Nest devices are among the first, along with Cync lighting, Motorola Tags, and iRobot vacuums.

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Google’s Will Smith double is better at eating AI spaghetti … but it’s crunchy?

AI, Ai video generator, Biz & IT, Deepfakes, Google, Google Veo, machine learning, Spaghetti, Veo, Veo 3, video synthesis, will smith / 9u50fv / May 24, 2025

On Tuesday, Google launched Veo 3, a new AI video synthesis model that can do something no major AI video generator has been able to do before: create a synchronized audio track. While from 2022 to 2024, we saw early steps in AI video generation, each video was silent and usually very short in duration. Now you can hear voices, dialog, and sound effects in eight-second high-definition video clips.

Shortly after the new launch, people began asking the most obvious benchmarking question: How good is Veo 3 at faking Oscar-winning actor Will Smith at eating spaghetti?

First, a brief recap. The spaghetti benchmark in AI video traces its origins back to March 2023, when we first covered an early example of horrific AI-generated video using an open source video synthesis model called ModelScope. The spaghetti example later became well-known enough that Smith parodied it almost a year later in February 2024.

Here’s what the original viral video looked like:

One thing people forget is that at the time, the Smith example wasn’t the best AI video generator out there—a video synthesis model called Gen-2 from Runway had already achieved superior results (though it was not yet publicly accessible). But the ModelScope result was funny and weird enough to stick in people’s memories as an early poor example of video synthesis, handy for future comparisons as AI models progressed.

AI app developer Javi Lopez first came to the rescue for curious spaghetti fans earlier this week with Veo 3, performing the Smith test and posting the results on X. But as you’ll notice below when you watch, the soundtrack has a curious quality: The faux Smith appears to be crunching on the spaghetti.

On X, Javi Lopez ran “Will Smith eating spaghetti” in Google’s Veo 3 AI video generator and received this result.

It’s a glitch in Veo 3’s experimental ability to apply sound effects to video, likely because the training data used to create Google’s AI models featured many examples of chewing mouths with crunching sound effects. Generative AI models are pattern-matching prediction machines, and they need to be shown enough examples of various types of media to generate convincing new outputs. If a concept is over-represented or under-represented in the training data, you’ll see unusual generation results, such as jabberwockies.

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Musk’s DOGE used Meta’s Llama 2—not Grok—for gov’t slashing, report says

AI, azure ai, department of government efficiency, doge, elon musk, grok, Llama 2, Meta, microsoft, Policy, xAI / Mike M. / May 24, 2025

Why didn’t DOGE use Grok?

It seems that Grok, Musk’s AI model, wasn’t available for DOGE’s task because it was only available as a proprietary model in January. Moving forward, DOGE may rely more frequently on Grok, Wired reported, as Microsoft announced it would start hosting xAI’s Grok 3 models in its Azure AI Foundry this week, The Verge reported, which opens the models up for more uses.

In their letter, lawmakers urged Vought to investigate Musk’s conflicts of interest, while warning of potential data breaches and declaring that AI, as DOGE had used it, was not ready for government.

“Without proper protections, feeding sensitive data into an AI system puts it into the possession of a system’s operator—a massive breach of public and employee trust and an increase in cybersecurity risks surrounding that data,” lawmakers argued. “Generative AI models also frequently make errors and show significant biases—the technology simply is not ready for use in high-risk decision-making without proper vetting, transparency, oversight, and guardrails in place.”

Although Wired’s report seems to confirm that DOGE did not send sensitive data from the “Fork in the Road” emails to an external source, lawmakers want much more vetting of AI systems to deter “the risk of sharing personally identifiable or otherwise sensitive information with the AI model deployers.”

A seeming fear is that Musk may start using his own models more, benefiting from government data his competitors cannot access, while potentially putting that data at risk of a breach. They’re hoping that DOGE will be forced to unplug all its AI systems, but Vought seems more aligned with DOGE, writing in his AI guidance for federal use that “agencies must remove barriers to innovation and provide the best value for the taxpayer.”

“While we support the federal government integrating new, approved AI technologies that can improve efficiency or efficacy, we cannot sacrifice security, privacy, and appropriate use standards when interacting with federal data,” their letter said. “We also cannot condone use of AI systems, often known for hallucinations and bias, in decisions regarding termination of federal employment or federal funding without sufficient transparency and oversight of those models—the risk of losing talent and critical research because of flawed technology or flawed uses of such technology is simply too high.”

Musk’s DOGE used Meta’s Llama 2—not Grok—for gov’t slashing, report says Read More »

In 3.5 years, Notepad.exe has gone from “barely maintained” to “it writes for you”

AI, copilot, microsoft, Tech, Windows, Windows 11, windows 11 24h2 / DJ Henderson / May 23, 2025

By late 2021, major updates for Windows’ built-in Notepad text editor had been so rare for so long that a gentle redesign and a handful of new settings were rated as a major update. New updates have become much more common since then, but like the rest of Windows, recent additions have been overwhelmingly weighted in the direction of generative AI.

In November, Microsoft began testing an update that allowed users to rewrite or summarize text in Notepad using generative AI. Another preview update today takes it one step further, allowing you to write AI-generated text from scratch with basic instructions (the feature is called Write, to differentiate it from the earlier Rewrite).

Like Rewrite and Summarize, Write requires users to be signed into a Microsoft Account, because using it requires you to use your monthly allotment of Microsoft’s AI credits. Per this support page, users without a paid Microsoft 365 subscription get 15 credits per month. Subscribers with Personal and Family subscriptions get 60 credits per month instead.

Microsoft notes that all AI features in Notepad can be disabled in the app’s settings, and obviously, they won’t be available if you use a local account instead of a Microsoft Account.

Microsoft is also releasing preview updates for Paint and Snipping Tool, two other bedrock Windows apps that hadn’t seen much by way of major updates before the Windows 11 era. Paint’s features are also mostly AI-related, including a “sticker generator” and an AI-powered smart select tool “to help you isolate and edit individual elements in your image.” A new “welcome experience” screen that appears the first time you launch the app will walk you through the (again, mostly AI-related) new features Microsoft has added to Paint in the last couple of years.

In 3.5 years, Notepad.exe has gone from “barely maintained” to “it writes for you” Read More »

New Claude 4 AI model refactored code for 7 hours straight

agentic AI, AI, AI assistants, Alex Albert, Anthropic, Anthropic Claude, Biz & IT, chatgpt, chatgtp, Claude, Claude 4, Claude 4 Opus, Claude 4 Sonnet, large language models, machine learning, openai / 9u50fv / May 22, 2025

Anthropic says Claude 4 beats Gemini on coding benchmarks; works autonomously for hours.

The Claude 4 logo, created by Anthropic. Credit: Anthropic

On Thursday, Anthropic released Claude Opus 4 and Claude Sonnet 4, marking the company’s return to larger model releases after primarily focusing on mid-range Sonnet variants since June of last year. The new models represent what the company calls its most capable coding models yet, with Opus 4 designed for complex, long-running tasks that can operate autonomously for hours.

Alex Albert, Anthropic’s head of Claude Relations, told Ars Technica that the company chose to revive the Opus line because of growing demand for agentic AI applications. “Across all the companies out there that are building things, there’s a really large wave of these agentic applications springing up, and a very high demand and premium being placed on intelligence,” Albert said. “I think Opus is going to fit that groove perfectly.”

Before we go further, a brief refresher on Claude’s three AI model “size” names (first introduced in March 2024) is probably warranted. Haiku, Sonnet, and Opus offer a tradeoff between price (in the API), speed, and capability.

Haiku models are the smallest, least expensive to run, and least capable in terms of what you might call “context depth” (considering conceptual relationships in the prompt) and encoded knowledge. Owing to the small size in parameter count, Haiku models retain fewer concrete facts and thus tend to confabulate more frequently (plausibly answering questions based on lack of data) than larger models, but they are much faster at basic tasks than larger models. Sonnet is traditionally a mid-range model that hits a balance between cost and capability, and Opus models have always been the largest and slowest to run. However, Opus models process context more deeply and are hypothetically better suited for running deep logical tasks.

A screenshot of the Claude web interface with Opus 4 and Sonnet 4 options shown. Credit: Anthropic

There is no Claude 4 Haiku just yet, but the new Sonnet and Opus models can reportedly handle tasks that previous versions could not. In our interview with Albert, he described testing scenarios where Opus 4 worked coherently for up to 24 hours on tasks like playing Pokémon while coding refactoring tasks in Claude Code ran for seven hours without interruption. Earlier Claude models typically lasted only one to two hours before losing coherence, Albert said, meaning that the models could only produce useful self-referencing outputs for that long before beginning to output too many errors.

In particular, that marathon refactoring claim reportedly comes from Rakuten, a Japanese tech services conglomerate that “validated [Claude’s] capabilities with a demanding open-source refactor running independently for 7 hours with sustained performance,” Anthropic said in a news release.

Whether you’d want to leave an AI model unsupervised for that long is another question entirely because even the most capable AI models can introduce subtle bugs, go down unproductive rabbit holes, or make choices that seem logical to the model but miss important context that a human developer would catch. While many people now use Claude for easy-going vibe coding, as we covered in March, the human-powered (and ironically-named) “vibe debugging” that often results from long AI coding sessions is also a very real thing. More on that below.

To shore up some of those shortcomings, Anthropic built memory capabilities into both new Claude 4 models, allowing them to maintain external files for storing key information across long sessions. When developers provide access to local files, the models can create and update “memory files” to track progress and things they deem important over time. Albert compared this to how humans take notes during extended work sessions.

Extended thinking meets tool use

Both Claude 4 models introduce what Anthropic calls “extended thinking with tool use,” a new beta feature allowing the models to alternate between simulated reasoning and using external tools like web search, similar to what OpenAI’s o3 and 04-mini-high AI models currently do in ChatGPT. While Claude 3.7 Sonnet already had strong tool use capabilities, the new models can now interleave simulated reasoning and tool calling in a single response.

“So now we can actually think, call a tool process, the results, think some more, call another tool, and repeat until it gets to a final answer,” Albert explained to Ars. The models self-determine when they have reached a useful conclusion, a capability picked up through training rather than governed by explicit human programming.

General Claude 4 benchmark results, provided by Anthropic. Credit: Anthropic

In practice, we’ve anecdotally found parallel tool use capability very useful in AI assistants like OpenAI o3, since they don’t have to rely on what is trained in their neural network to provide accurate answers. Instead, these more agentic models can iteratively search the web, parse the results, analyze images, and spin up coding tasks for analysis in ways that can avoid falling into a confabulation trap by relying solely on pure LLM outputs.

“The world’s best coding model”

Anthropic says Opus 4 leads industry benchmarks for coding tasks, achieving 72.5 percent on SWE-bench and 43.2 percent on Terminal-bench, calling it “the world’s best coding model.” According to Anthropic, companies using early versions report improvements. Cursor described it as “state-of-the-art for coding and a leap forward in complex codebase understanding,” while Replit noted “improved precision and dramatic advancements for complex changes across multiple files.”

In fact, GitHub announced it will use Sonnet 4 as the base model for its new coding agent in GitHub Copilot, citing the model’s performance in “agentic scenarios” in Anthropic’s news release. Sonnet 4 scored 72.7 percent on SWE-bench while maintaining faster response times than Opus 4. The fact that GitHub is betting on Claude rather than a model from its parent company Microsoft (which has close ties to OpenAI) suggests Anthropic has built something genuinely competitive.

Software engineering benchmark results, provided by Anthropic. Credit: Anthropic

Anthropic says it has addressed a persistent issue with Claude 3.7 Sonnet in which users complained that the model would take unauthorized actions or provide excessive output. Albert said the company reduced this “reward hacking behavior” by approximately 80 percent in the new models through training adjustments. An 80 percent reduction in unwanted behavior sounds impressive, but that also suggests that 20 percent of the problem behavior remains—a big concern when we’re talking about AI models that might be performing autonomous tasks for hours.

When we asked about code accuracy, Albert said that human code review is still an important part of shipping any production code. “There’s a human parallel, right? So this is just a problem we’ve had to deal with throughout the whole nature of software engineering. And this is why the code review process exists, so that you can catch these things. We don’t anticipate that going away with models either,” Albert said. “If anything, the human review will become more important, and more of your job as developer will be in this review than it will be in the generation part.”

Pricing and availability

Both Claude 4 models maintain the same pricing structure as their predecessors: Opus 4 costs $15 per million tokens for input and $75 per million for output, while Sonnet 4 remains at $3 and $15. The models offer two response modes: traditional LLM and simulated reasoning (“extended thinking”) for complex problems. Given that some Claude Code sessions can apparently run for hours, those per-token costs will likely add up very quickly for users who let the models run wild.

Anthropic made both models available through its API, Amazon Bedrock, and Google Cloud Vertex AI. Sonnet 4 remains accessible to free users, while Opus 4 requires a paid subscription.

The Claude 4 models also debut Claude Code (first introduced in February) as a generally available product after months of preview testing. Anthropic says the coding environment now integrates with VS Code and JetBrains IDEs, showing proposed edits directly in files. A new SDK allows developers to build custom agents using the same framework.

A screenshot of “Claude Plays Pokemon,” a custom application where Claude 4 attempts to beat the classic Game Boy game. Credit: Anthropic

Even with Anthropic’s future riding on the capability of these new models, when we asked about how they guide Claude’s behavior by fine-tuning, Albert acknowledged that the inherent unpredictability of these systems presents ongoing challenges for both them and developers. “In the realm and the world of software for the past 40, 50 years, we’ve been running on deterministic systems, and now all of a sudden, it’s non-deterministic, and that changes how we build,” he said.

“I empathize with a lot of people out there trying to use our APIs and language models generally because they have to almost shift their perspective on what it means for reliability, what it means for powering a core of your application in a non-deterministic way,” Albert added. “These are general oddities that have kind of just been flipped, and it definitely makes things more difficult, but I think it opens up a lot of possibilities as well.”

Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.

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Gemini 2.5 is leaving preview just in time for Google’s new $250 AI subscription

AI, Artificial Intelligence, Gemini, Google, Tech / 9u50fv / May 21, 2025

Deep Think graphs I/O — Deep Think is more capable of complex math and coding. Credit: Ryan Whitwam

Both 2.5 models have adjustable thinking budgets when used in Vertex AI and via the API, and now the models will also include summaries of the “thinking” process for each output. This makes a little progress toward making generative AI less overwhelmingly expensive to run. Gemini 2.5 Pro will also appear in some of Google’s dev products, including Gemini Code Assist.

Gemini Live, previously known as Project Astra, started to appear on mobile devices over the last few months. Initially, you needed to have a Gemini subscription or a Pixel phone to access Gemini Live, but now it’s coming to all Android and iOS devices immediately. Google demoed a future “agentic” capability in the Gemini app that can actually control your phone, search the web for files, open apps, and make calls. It’s perhaps a little aspirational, just like the Astra demo from last year. The version of Gemini Live we got wasn’t as good, but as a glimpse of the future, it was impressive.

There are also some developments in Chrome, and you guessed it, it’s getting Gemini. It’s not dissimilar from what you get in Edge with Copilot. There’s a little Gemini icon in the corner of the browser, which you can click to access Google’s chatbot. You can ask it about the pages you’re browsing, have it summarize those pages, and ask follow-up questions.

Google AI Ultra is ultra-expensive

Since launching Gemini, Google has only had a single $20 monthly plan for AI features. That plan granted you access to the Pro models and early versions of Google’s upcoming AI. At I/O, Google is catching up to AI firms like OpenAI, which have offered sky-high AI plans. Google’s new Google AI Ultra plan will cost $250 per month, more than the $200 plan for ChatGPT Pro.

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Adobe to automatically move subscribers to pricier, AI-focused tier in June

adobe, AI, generative ai, Software, subscriptions, Tech / 9u50fv / May 20, 2025

Subscribers to Adobe’s multi-app subscription plan, Creative Cloud All Apps, will be charged more starting on June 17 to accommodate for new generative AI features.

Adobe’s announcement, spotted by MakeUseOf, says the change will affect North American subscribers to the Creative Cloud All Apps plan, which Adobe is renaming Creative Cloud Pro. Starting on June 17, Adobe will automatically renew Creative Cloud All Apps subscribers into the Creative Cloud Pro subscription, which will be $70 per month for individuals who commit to an annual plan, up from $60 for Creative Cloud All Apps. Annual plans for students and teachers plans are moving from $35/month to $40/month, and annual teams pricing will go from $90/month to $100/month. Monthly (non-annual) subscriptions are also increasing, from $90 to $105.

Further, in an apparent attempt to push generative AI users to more expensive subscriptions, as of June 17, Adobe will give single-app subscribers just 25 generative AI credits instead of the current 500.

Current subscribers can opt to move down to a new multi-app plan called Creative Cloud Standard, which is $55/month for annual subscribers and $82.49/month for monthly subscribers. However, this tier limits access to mobile and web app features, and subscribers can’t use premium generative AI features.

Creative Cloud Standard won’t be available to new subscribers, meaning the only option for new customers who need access to many Adobe apps will be the new AI-heavy Creative Cloud Pro plan.

Adobe’s announcement explained the higher prices by saying that the subscription tier “includes all the core applications and new AI capabilities that power the way people create today, and its price reflects that innovation, as well as our ongoing commitment to deliver the future of creative tools.”

Like today’s Creative Cloud All Apps plan, Creative Cloud Pro will include Photoshop, Illustrator, Premiere Pro, Lightroom, and access to Adobe’s web and mobile apps. AI features include unlimited usage of image and vector features in Adobe apps, including Generative Fill in Photoshop, Generative Remove in Lightroom, Generative Shape Fill in Illustrator, and 4K video generation with Generative Extend in Premiere Pro.

Adobe to automatically move subscribers to pricier, AI-focused tier in June Read More »

Chicago Sun-Times prints summer reading list full of fake books

AI, Biz & IT, Chicago Sun-Times, confabulations, machine learning / Kelly Newman / May 20, 2025

Photo of the Chicago Sun-Times “Summer reading list for 2025” supplement. Credit: Rachel King / Bluesky

Novelist Rachael King initially called attention to the error on Bluesky Tuesday morning. “The Chicago Sun-Times obviously gets ChatGPT to write a ‘summer reads’ feature almost entirely made up of real authors but completely fake books. What are we coming to?” King wrote.

So far, community reaction to the list has been largely negative online, but others have expressed sympathy for the publication. Freelance journalist Joshua J. Friedman noted on Bluesky that the reading list was “part of a ~60-page summer supplement” published on May 18, suggesting it might be “transparent filler” possibly created by “the lone freelancer apparently saddled with producing it.”

The staffing connection

The reading list appeared in a 64-page supplement called “Heat Index,” which was a promotional section not specific to Chicago. Buscaglia told 404 Media the content was meant to be “generic and national” and would be inserted into newspapers around the country. “We never get a list of where things ran,” he said.

The publication error comes two months after the Chicago Sun-Times lost 20 percent of its staff through a buyout program. In March, the newspaper’s nonprofit owner, Chicago Public Media, announced that 30 Sun-Times employees—including 23 from the newsroom—had accepted buyout offers amid financial struggles.

A March report on the buyout in the Sun-Times described the staff reduction as “the most drastic the oft-imperiled Sun-Times has faced in several years.” The departures included columnists, editorial writers, and editors with decades of experience.

Melissa Bell, CEO of Chicago Public Media, stated at the time that the exits would save the company $4.2 million annually. The company offered buyouts as it prepared for an expected expiration of grant support at the end of 2026.

Even with those pressures in the media, one Reddit user expressed disapproval of the apparent use of AI in the newspaper, even in a supplement that might not have been produced by staff. “As a subscriber, I am livid! What is the point of subscribing to a hard copy paper if they are just going to include AI slop too!?” wrote Reddit user xxxlovelit, who shared the reading list. “The Sun Times needs to answer for this, and there should be a reporter fired.”

This article was updated on May 20, 2025 at 11: 02 AM to include information on Marco Buscaglia from 404 Media.

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Zero-click searches: Google’s AI tools are the culmination of its hubris

AI, Artificial Intelligence, Features, Google, search / Mike M. / May 20, 2025

Google’s first year with AI search was a wild ride. It will get wilder.

Google is constantly making changes to its search rankings, but not all updates are equal. Every few months, the company bundles up changes into a larger “core update.” These updates make rapid and profound changes to search, so website operators watch them closely.

The March 2024 update was unique. It was one of Google’s largest core updates ever, and it took over a month to fully roll out. Nothing has felt quite the same since. Whether the update was good or bad depends on who you ask—and maybe who you are.

It’s common for websites to see traffic changes after a core update, but the impact of the March 2024 update marked a seismic shift. Google says the update aimed to address spam and AI-generated content in a meaningful way. Still, many publishers say they saw clicks on legitimate sites evaporate, while others have had to cope with unprecedented volatility in their traffic. Because Google owns almost the entire search market, changes in its algorithm can move the Internet itself.

In hindsight, the March 2024 update looks like the first major Google algorithm update for the AI era. Not only did it (supposedly) veer away from ranking AI-authored content online, but it also laid the groundwork for Google’s ambitious—and often annoying—desire to fuse AI with search.

A year ago, this ambition surfaced with AI Overviews, but now the company is taking an even more audacious route, layering in a new chat-based answer service called “AI Mode.” Both of these technologies do at least two things: They aim to keep you on Google properties longer, and they remix publisher content without always giving prominent citations.

Smaller publishers appear to have borne the brunt of the changes caused by these updates. “Google got all this flak for crushing the small publishers, and it’s true that when they make these changes, they do crush a lot of publishers,” says Jim Yu, CEO of enterprise SEO platform BrightEdge. Yu explains that Google is the only search engine likely to surface niche content in the first place, and there are bound to be changes to sites at the fringes during a major core update.

Google’s own view on the impact of the March 2024 update is unsurprisingly positive. The company said it was hoping to reduce the appearance of unhelpful content in its search engine results pages (SERPs) by 40 percent. After the update, the company claimed an actual reduction of closer to 45 percent. But does it feel like Google’s results have improved by that much? Most people don’t think so.

What causes this disconnect? According to Michael King, founder of SEO firm iPullRank, we’re not speaking the same language as Google. “Google’s internal success metrics differ from user perceptions,” he says. “Google measures user satisfaction through quantifiable metrics, while external observers rely on subjective experiences.”

Google evaluates algorithm changes with various tests, including human search quality testers and running A/B tests on live searches. But more than anything else, success is about the total number of searches (5 trillion of them per year). Google often makes this number a centerpiece of its business updates to show investors that it can still grow.

However, using search quantity to measure quality has obvious problems. For instance, more engagement with a search engine might mean that quality has decreased, so people try new queries (e.g., the old trick of adding “Reddit” to the end of your search string). In other words, people could be searching more because they don’t like the results.

Jim Yu suggests that Google is moving fast and breaking things, but it may not be as bad as we think. “I think they rolled things out faster because they had to move a lot faster than they’ve historically had to move, and it ends up that they do make some real mistakes,” says Yu. “[Google] is held to a higher standard, but by and large, I think their search quality is improving.”

According to King, Google’s current search behavior still favors big names, but other sites have started to see a rebound. “Larger brands are performing better in the top three positions, while lesser-known websites have gained ground in positions 4 through 10,” says King. “Although some websites have indeed lost traffic due to reduced organic visibility, the bigger issue seems tied to increased usage of AI Overviews”—and now the launch of AI Mode.

Yes, the specter of AI hangs over every SERP. The unhelpful vibe many people now get from Google searches, regardless of the internal metrics the company may use, may come from a fundamental shift in how Google surfaces information in the age of AI.

The AI Overview hangover

In 2025, you can’t talk about Google’s changes to search without acknowledging the AI-generated elephant in the room. As it wrapped up that hefty core update in March 2024, Google also announced a major expansion of AI in search, moving the “Search Generative Experience” out of labs and onto Google.com. The feature was dubbed “AI Overviews.”

The AI Overview box has been a fixture on Google’s search results page ever since its debut a year ago. The feature uses the same foundational AI model as Google’s Gemini chatbot to formulate answers to your search queries by ingesting the top 100 (!) search results. It sits at the top of the page, pushing so-called blue link content even farther down below the ads and knowledge graph content. It doesn’t launch on every query, and sometimes it answers questions you didn’t ask—or even hallucinates a totally wrong answer.

And it’s not without some irony that Google’s laudable decision to de-rank synthetic AI slop comes at the same time that Google heavily promotes its own AI-generated content right at the top of SERPs.

AI Overview on phone — AI Overviews appear right at the top of many search results. Credit: Google

What is Google getting for all of this AI work? More eyeballs, it would seem. “AI is driving more engagement than ever before on Google,” says Yu. BrightEdge data shows that impressions on Google are up nearly 50 percent since AI Overviews launched. Many of the opinions you hear about AI Overviews online are strongly negative, but that doesn’t mean people aren’t paying attention to the feature. In its Q1 2025 earnings report, Google announced that AI Overviews is being “used” by 1.5 billion people every month. (Since you can’t easily opt in or opt out of AI Overviews, this “usage” claim should be taken with a grain of salt.)

Interestingly, the impact of AI Overviews has varied across the web. In October 2024, Google was so pleased with AI Overviews that it expanded them to appear in more queries. And as AI crept into more queries, publishers saw a corresponding traffic drop. Yu estimates this drop to be around 30 percent on average for those with high AI query coverage. For searches that are less supported in AI Overviews—things like restaurants and financial services—the traffic change has been negligible. And there are always exceptions. Yu suggests that some large businesses with high AI Overview query coverage have seen much smaller drops in traffic because they rank extremely well as both AI citations and organic results.

Lower traffic isn’t the end of the world for some businesses. Last May, AI Overviews were largely absent from B2B queries, but that turned around in a big way in recent months. BrightEdge estimates that 70 percent of B2B searches now have AI answers, which has reduced traffic for many companies. Yu doesn’t think it’s all bad, though. “People don’t click through as much—they engage a lot more on the AI—but when they do click, the conversion rate for the business goes up,” Yu says. In theory, serious buyers click and window shoppers don’t.

But the Internet is not a giant mall that exists only for shoppers. It is, first and foremost, a place to share and find information, and AI Overviews have hit some purveyors of information quite hard. At launch, AI Overviews were heavily focused on “What is” and “How to” queries. Such “service content” is a staple of bloggers and big media alike, and these types of publishers aren’t looking for sales conversions—it’s traffic that matters. And they’re getting less of it because AI Overviews “helpfully” repackages and remixes their content, eliminating the need to click through to the site. Some publishers are righteously indignant, asking how it’s fair for Google to remix content it doesn’t own, and to do so without compensation.

But Google’s intentions don’t end with AI Overviews. Last week, the company started an expanded public test of so-called “AI Mode,” right from the front page. AI Mode doesn’t even bother with those blue links. It’s a chatbot experience that, at present, tries to answer your query without clearly citing sources inline. (On some occasions, it will mention Reddit or Wikipedia.) On the right side of the screen, Google provides a little box with three sites linked, which you can expand to see more options. To the end user, it’s utterly unclear if those are “sources,” “recommendations,” or “partner deals.”

Perhaps more surprisingly, in our testing, not a single AI Mode “sites box” listed a site that ranked on the first page for the same query on a regular search. That is, the links in AI Mode for “best foods to eat for a cold” don’t overlap at all with the SERP for the same query in Google Search. In fairness, AI Mode is very new, and its behavior will undoubtedly change. But the direction the company is headed seems clear.

Google’s real goal is to keep you on Google or other Alphabet properties. In 2019, Rand Fishkin noticed that Google’s evolution from search engine to walled garden was at a tipping point. At that time—and for the first time—more than half of Google searches resulted in zero click-throughs to other sites. But data did show large numbers of clicks to Google’s own properties, like YouTube and Maps. If Google doesn’t intend to deliver a “zero-click” search experience, you wouldn’t know it from historical performance data or the new features the company develops.

You also wouldn’t know it from the way AI Overviews work. They do cite some of the sources used in building each output, and data suggests people click on those links. But are the citations accurate? Is every source used for constructing an AI Overview cited? We don’t really know, as Google is famously opaque about how its search works. We do know that Google uses a customized version of Gemini to support AI Overviews and that Gemini has been trained on billions and billions of webpages.

When AI Overviews do cite a source, it’s not clear how those sources came to be the ones cited. There’s good reason to be suspicious here: AI Overview’s output is not great, as witnessed by the numerous hallucinations we all know and love (telling people to eat rocks, for instance). The only thing we know for sure is that Google isn’t transparent about any of this.

No signs of slowing

Despite all of that, Google is not slowing down on AI in search. More recent core updates have only solidified this new arrangement with an ever-increasing number of AI-answered queries. The company appears OK with its current accuracy problems, or at the very least, it’s comfortable enough to push out AI updates anyway. Google appears to have been caught entirely off guard by the public launch of ChatGPT, and it’s now utilizing its search dominance to play catch-up.

To make matters even more dicey, Google isn’t even trying to address the biggest issue in all this: The company’s quest for zero-click search harms the very content creators upon which the company has built its empire.

For its part, Google has been celebrating its AI developments, insisting that content producers don’t know what’s best for them, refuting any concerns with comments about search volume increases and ever-more-complex search query strings. The changes must be working!

Google has been building toward this moment for years. The company started with a list of 10 blue links and nothing else, but little by little, it pushed the links down the page and added more content that keeps people in the Google ecosystem. Way back in 2007, Google added Universal Search, which allowed it to insert content from Google Maps, YouTube, and other services. In 2009, Rich Snippets began displaying more data from search results on SERPs. In 2012, the Knowledge Graph began extracting data from search results to display answers in the search results. Each change kept people on Google longer and reduced click-throughs, all the while pushing the search results down the page.

AI Overviews, and especially AI Mode, are the logical outcome of Google’s yearslong transformation from an indexer of information to an insular web portal built on scraping content from around the web. Earlier in Google’s evolution, the implicit agreement was that websites would allow Google to crawl their pages in exchange for sending them traffic. That relationship has become strained as the company has kept more traffic for itself, reducing click-throughs to websites even as search volume continues to increase. And locking Google out isn’t a realistic option when the company controls almost the entire search market.

Even when Google has taken a friendlier approach, business concerns could get in the way. During the search antitrust trial, documents showed that Google initially intended to let sites opt out of being used for AI training for its search-based AI features—but these sites would still be included in search results. The company ultimately canned that idea, leaving site operators with the Pyrrhic choice of participating in the AI “revolution” or becoming invisible on the web. Google now competes with, rather than supports, the open web.

When many of us look at Google’s search results today, the vibe feels off. Maybe it’s the AI, maybe it’s Google’s algorithm, or maybe the Internet just isn’t what it once was. Whatever the cause, the shift toward zero-click search that began more than a decade ago was made clear by the March 2024 core update, and it has only accelerated with the launch of AI Mode. Even businesses that have escaped major traffic drops from AI Overviews could soon find that Google’s AI-only search can get much more overbearing.

The AI slop will continue until morale improves.

Ryan Whitwam is a senior technology reporter at Ars Technica, covering the ways Google, AI, and mobile technology continue to change the world. Over his 20-year career, he’s written for Android Police, ExtremeTech, Wirecutter, NY Times, and more. He has reviewed more phones than most people will ever own. You can follow him on Bluesky, where you will see photos of his dozens of mechanical keyboards.

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