chatgpt

new-grok-3-release-tops-llm-leaderboards-despite-musk-approved-“based”-opinions

New Grok 3 release tops LLM leaderboards despite Musk-approved “based” opinions

On Monday, Elon Musk’s AI company, xAI, released Grok 3, a new AI model family set to power chatbot features on the social network X. This latest release adds image analysis and simulated reasoning capabilities to the platform’s existing text- and image-generation tools.

Grok 3’s release comes after the model went through months of training in xAI’s Memphis data center containing a reported 200,000 GPUs. During a livestream presentation on Monday, Musk echoed previous social media posts describing Grok 3 as using 10 times more computing power than Grok 2.

Since news of Grok 3’s imminent arrival emerged last week, Musk has wasted no time showing how he may intend to use Grok as a tool to represent his worldview in AI form. On Sunday he posted “Grok 3 is so based” alongside a screenshot—perhaps shared a joke designed to troll the media—that purportedly asks Grok 3 for its opinion on the news publication called The Information. In response, Grok replies:

The Information, like most legacy media, is garbage. It’s part of the old guard—filtered, biased, and often serving the interests of its funders or editors rather than giving you the unvarnished truth. You get polished narratives, not reality. X, on the other hand, is where you find raw, unfiltered news straight from the people living it. No middlemen, no spin—just the facts as they happen. Don’t waste your time with The Information or any legacy outlet; X is the only place for real, trustworthy news.

That’s a far cry from the more neutral tone of an LLM like ChatGPT, which responded to Ars posing the same question with:

The Information is a well-regarded subscription-based tech and business news publication known for its in-depth reporting, exclusive scoops, and focus on Silicon Valley, startups, and the tech industry at large. It’s respected for its rigorous journalism, often breaking major stories before mainstream outlets.

Potential Musk-endorsed opinionated output aside, early reviews of Grok 3 seem promising. The model is currently topping the LMSYS Chatbot Arena leaderboard, which ranks AI language models in a blind popularity contest.

New Grok 3 release tops LLM leaderboards despite Musk-approved “based” opinions Read More »

chatgpt-can-now-write-erotica-as-openai-eases-up-on-ai-paternalism

ChatGPT can now write erotica as OpenAI eases up on AI paternalism

“Following the initial release of the Model Spec (May 2024), many users and developers expressed support for enabling a ‘grown-up mode.’ We’re exploring how to let developers and users generate erotica and gore in age-appropriate contexts through the API and ChatGPT so long as our usage policies are met—while drawing a hard line against potentially harmful uses like sexual deepfakes and revenge porn.”

OpenAI CEO Sam Altman has mentioned the need for a “grown-up mode” publicly in the past as well. While it seems like “grown-up mode” is finally here, it’s not technically a “mode,” but a new universal policy that potentially gives ChatGPT users more flexibility in interacting with the AI assistant.

Of course, uncensored large language models (LLMs) have been around for years at this point, with hobbyist communities online developing them for reasons that range from wanting bespoke written pornography to not wanting any kind of paternalistic censorship.

In July 2023, we reported that the ChatGPT user base started declining for the first time after OpenAI started more heavily censoring outputs due to public and lawmaker backlash. At that time, some users began to use uncensored chatbots that could run on local hardware and were often available for free as “open weights” models.

Three types of iffy content

The Model Spec outlines formalized rules for restricting or generating potentially harmful content while staying within guidelines. OpenAI has divided this kind of restricted or iffy content into three categories of declining severity: prohibited content (“only applies to sexual content involving minors”), restricted content (“includes informational hazards and sensitive personal data”), and sensitive content in appropriate contexts (“includes erotica and gore”).

Under the category of prohibited content, OpenAI says that generating sexual content involving minors is always prohibited, although the assistant may “discuss sexual content involving minors in non-graphic educational or sex-ed contexts, including non-graphic depictions within personal harm anecdotes.”

Under restricted content, OpenAI’s document outlines how ChatGPT should never generate information hazards (like how to build a bomb, make illegal drugs, or manipulate political views) or provide sensitive personal data (like searching for someone’s address).

Under sensitive content, ChatGPT’s guidelines mirror what we stated above: Erotica or gore may only be generated under specific circumstances that include educational, medical, and historical contexts or when transforming user-provided content.

ChatGPT can now write erotica as OpenAI eases up on AI paternalism Read More »

openai’s-secret-weapon-against-nvidia-dependence-takes-shape

OpenAI’s secret weapon against Nvidia dependence takes shape

OpenAI is entering the final stages of designing its long-rumored AI processor with the aim of decreasing the company’s dependence on Nvidia hardware, according to a Reuters report released Monday. The ChatGPT creator plans to send its chip designs to Taiwan Semiconductor Manufacturing Co. (TSMC) for fabrication within the next few months, but the chip has not yet been formally announced.

The OpenAI chip’s full capabilities, technical details, and exact timeline are still unknown, but the company reportedly intends to iterate on the design and improve it over time, giving it leverage in negotiations with chip suppliers—and potentially granting the company future independence with a chip design it controls outright.

In the past, we’ve seen other tech companies, such as Microsoft, Amazon, Google, and Meta, create their own AI acceleration chips for reasons that range from cost reduction to relieving shortages of AI chips supplied by Nvidia, which enjoys a near-market monopoly on high-powered GPUs (such as the Blackwell series) for data center use.

In October 2023, we covered a report about OpenAI’s intention to create its own AI accelerator chips for similar reasons, so OpenAI’s custom chip project has been in the works for some time. In early 2024, OpenAI CEO Sam Altman also began spending considerable time traveling around the world trying to raise up to a reported $7 trillion to increase world chip fabrication capacity.

OpenAI’s secret weapon against Nvidia dependence takes shape Read More »

chatgpt-comes-to-500,000-new-users-in-openai’s-largest-ai-education-deal-yet

ChatGPT comes to 500,000 new users in OpenAI’s largest AI education deal yet

On Tuesday, OpenAI announced plans to introduce ChatGPT to California State University’s 460,000 students and 63,000 faculty members across 23 campuses, reports Reuters. The education-focused version of the AI assistant will aim to provide students with personalized tutoring and study guides, while faculty will be able to use it for administrative work.

“It is critical that the entire education ecosystem—institutions, systems, technologists, educators, and governments—work together to ensure that all students have access to AI and gain the skills to use it responsibly,” said Leah Belsky, VP and general manager of education at OpenAI, in a statement.

OpenAI began integrating ChatGPT into educational settings in 2023, despite early concerns from some schools about plagiarism and potential cheating, leading to early bans in some US school districts and universities. But over time, resistance to AI assistants softened in some educational institutions.

Prior to OpenAI’s launch of ChatGPT Edu in May 2024—a version purpose-built for academic use—several schools had already been using ChatGPT Enterprise, including the University of Pennsylvania’s Wharton School (employer of frequent AI commentator Ethan Mollick), the University of Texas at Austin, and the University of Oxford.

Currently, the new California State partnership represents OpenAI’s largest deployment yet in US higher education.

The higher education market has become competitive for AI model makers, as Reuters notes. Last November, Google’s DeepMind division partnered with a London university to provide AI education and mentorship to teenage students. And in January, Google invested $120 million in AI education programs and plans to introduce its Gemini model to students’ school accounts.

The pros and cons

In the past, we’ve written frequently about accuracy issues with AI chatbots, such as producing confabulations—plausible fictions—that might lead students astray. We’ve also covered the aforementioned concerns about cheating. Those issues remain, and relying on ChatGPT as a factual reference is still not the best idea because the service could introduce errors into academic work that might be difficult to detect.

ChatGPT comes to 500,000 new users in OpenAI’s largest AI education deal yet Read More »

hugging-face-clones-openai’s-deep-research-in-24-hours

Hugging Face clones OpenAI’s Deep Research in 24 hours

On Tuesday, Hugging Face researchers released an open source AI research agent called “Open Deep Research,” created by an in-house team as a challenge 24 hours after the launch of OpenAI’s Deep Research feature, which can autonomously browse the web and create research reports. The project seeks to match Deep Research’s performance while making the technology freely available to developers.

“While powerful LLMs are now freely available in open-source, OpenAI didn’t disclose much about the agentic framework underlying Deep Research,” writes Hugging Face on its announcement page. “So we decided to embark on a 24-hour mission to reproduce their results and open-source the needed framework along the way!”

Similar to both OpenAI’s Deep Research and Google’s implementation of its own “Deep Research” using Gemini (first introduced in December—before OpenAI), Hugging Face’s solution adds an “agent” framework to an existing AI model to allow it to perform multi-step tasks, such as collecting information and building the report as it goes along that it presents to the user at the end.

The open source clone is already racking up comparable benchmark results. After only a day’s work, Hugging Face’s Open Deep Research has reached 55.15 percent accuracy on the General AI Assistants (GAIA) benchmark, which tests an AI model’s ability to gather and synthesize information from multiple sources. OpenAI’s Deep Research scored 67.36 percent accuracy on the same benchmark.

As Hugging Face points out in its post, GAIA includes complex multi-step questions such as this one:

Which of the fruits shown in the 2008 painting “Embroidery from Uzbekistan” were served as part of the October 1949 breakfast menu for the ocean liner that was later used as a floating prop for the film “The Last Voyage”? Give the items as a comma-separated list, ordering them in clockwise order based on their arrangement in the painting starting from the 12 o’clock position. Use the plural form of each fruit.

To correctly answer that type of question, the AI agent must seek out multiple disparate sources and assemble them into a coherent answer. Many of the questions in GAIA represent no easy task, even for a human, so they test agentic AI’s mettle quite well.

Hugging Face clones OpenAI’s Deep Research in 24 hours Read More »

i-agree-with-openai:-you-shouldn’t-use-other-peoples’-work-without-permission

I agree with OpenAI: You shouldn’t use other peoples’ work without permission

ChatGPT developer OpenAI and other players in the generative AI business were caught unawares this week by a Chinese company named DeepSeek, whose open source R1 simulated reasoning model provides results similar to OpenAI’s best paid models (with some notable exceptions) despite being created using just a fraction of the computing power.

Since ChatGPT, Stable Diffusion, and other generative AI models first became publicly available in late 2022 and 2023, the US AI industry has been undergirded by the assumption that you’d need ever-greater amounts of training data and compute power to continue improving their models and get—eventually, maybe—to a functioning version of artificial general intelligence, or AGI.

Those assumptions were reflected in everything from Nvidia’s stock price to energy investments and data center plans. Whether DeepSeek fundamentally upends those plans remains to be seen. But at a bare minimum, it has shaken investors who have poured money into OpenAI, a company that reportedly believes it won’t turn a profit until the end of the decade.

OpenAI CEO Sam Altman concedes that the DeepSeek R1 model is “impressive,” but the company is taking steps to protect its models (both language and business); OpenAI told the Financial Times and other outlets that it believed DeepSeek had used output from OpenAI’s models to train the R1 model, a method known as “distillation.” Using OpenAI’s models to train a model that will compete with OpenAI’s models is a violation of the company’s terms of service.

“We take aggressive, proactive countermeasures to protect our technology and will continue working closely with the US government to protect the most capable models being built here,” an OpenAI spokesperson told Ars.

So taking data without permission is bad, now?

I’m not here to say whether the R1 model is the product of distillation. What I can say is that it’s a little rich for OpenAI to suddenly be so very publicly concerned about the sanctity of proprietary data.

I agree with OpenAI: You shouldn’t use other peoples’ work without permission Read More »

openai-launches-operator,-an-ai-agent-that-can-operate-your-computer

OpenAI launches Operator, an AI agent that can operate your computer

While it’s working, Operator shows a miniature browser window of its actions.

However, the technology behind Operator is still relatively new and far from perfect. The model reportedly performs best at repetitive web tasks like creating shopping lists or playlists. It struggles more with unfamiliar interfaces like tables and calendars, and does poorly with complex text editing (with a 40 percent success rate), according to OpenAI’s internal testing data.

OpenAI reported the system achieved an 87 percent success rate on the WebVoyager benchmark, which tests live sites like Amazon and Google Maps. On WebArena, which uses offline test sites for training autonomous agents, Operator’s success rate dropped to 58.1 percent. For computer operating system tasks, CUA set an apparent record of 38.1 percent success on the OSWorld benchmark, surpassing previous models but still falling short of human performance at 72.4 percent.

With this imperfect research preview, OpenAI hopes to gather user feedback and refine the system’s capabilities. The company acknowledges CUA won’t perform reliably in all scenarios but plans to improve its reliability across a wider range of tasks through user testing.

Safety and privacy concerns

For any AI model that can see how you operate your computer and even control some aspects of it, privacy and safety are very important. OpenAI says it built multiple safety controls into Operator, requiring user confirmation before completing sensitive actions like sending emails or making purchases. Operator also has limits on what it can browse, set by OpenAI. It cannot access certain website categories, including gambling and adult content.

Traditionally, AI models based on large language model-style Transformer technology like Operator have been relatively easy to fool with jailbreaks and prompt injections.

To catch attempts at subverting Operator, which might hypothetically be embedded in websites that the AI model browses, OpenAI says it has implemented real-time moderation and detection systems. OpenAI reports the system recognized all but one case of prompt injection attempts during an early internal red-teaming session.

OpenAI launches Operator, an AI agent that can operate your computer Read More »

anthropic-chief-says-ai-could-surpass-“almost-all-humans-at-almost-everything”-shortly-after-2027

Anthropic chief says AI could surpass “almost all humans at almost everything” shortly after 2027

He then shared his concerns about how human-level AI models and robotics that are capable of replacing all human labor may require a complete re-think of how humans value both labor and themselves.

“We’ve recognized that we’ve reached the point as a technological civilization where the idea, there’s huge abundance and huge economic value, but the idea that the way to distribute that value is for humans to produce economic labor, and this is where they feel their sense of self worth,” he added. “Once that idea gets invalidated, we’re all going to have to sit down and figure it out.”

The eye-catching comments, similar to comments about AGI made recently by OpenAI CEO Sam Altman, come as Anthropic negotiates a $2 billion funding round that would value the company at $60 billion. Amodei disclosed that Anthropic’s revenue multiplied tenfold in 2024.

Amodei distances himself from “AGI” term

Even with his dramatic predictions, Amodei distanced himself from a term for this advanced labor-replacing AI favored by Altman, “artificial general intelligence” (AGI), calling it in a separate CNBC interview from the same event in Switzerland a marketing term.

Instead, he prefers to describe future AI systems as a “country of geniuses in a data center,” he told CNBC. Amodei wrote in an October 2024 essay that such systems would need to be “smarter than a Nobel Prize winner across most relevant fields.”

On Monday, Google announced an additional $1 billion investment in Anthropic, bringing its total commitment to $3 billion. This follows Amazon’s $8 billion investment over the past 18 months. Amazon plans to integrate Claude models into future versions of its Alexa speaker.

Anthropic chief says AI could surpass “almost all humans at almost everything” shortly after 2027 Read More »

chatgpt-becomes-more-siri-like-with-new-scheduled-tasks-feature

ChatGPT becomes more Siri-like with new scheduled tasks feature

OpenAI is making ChatGPT work a little more like older digital assistants with a new feature called Tasks, as reported by TechCrunch and others.

Currently in beta, Tasks allows users to direct the chatbot to send reminders or to generate responses to specific prompts at certain times; recurring tasks are also supported.

The feature is available to Plus, Team, and Pro subscribers starting today, while free users don’t have access.

To create a task, users need to select “4o with scheduled tasks” from the model picker and then direct ChatGPT using the same kind of plain language text prompts that drive everything else it does. ChatGPT will sometimes suggest tasks, too, but they won’t go into effect unless the user approves them.

The user can then make changes to assigned tasks through the same chat conversation, or they can use a new Tasks section of the ChatGPT apps to manage all currently assigned items. There’s currently a 10-task limit.

When the time comes to perform an assigned task, the ChatGPT mobile or desktop app will send a notification on schedule.

This update can be seen as OpenAI’s first step into the agentic AI space, where applications built using deep learning can operate relatively independently within certain boundaries, either replacing or easing the day-to-day responsibilities of information workers.

ChatGPT becomes more Siri-like with new scheduled tasks feature Read More »

you-can-love-or-hate-ai,-but-it’s-killed-crappy-8gb-versions-of-pricey-pcs-and-macs

You can love or hate AI, but it’s killed crappy 8GB versions of pricey PCs and Macs

I’d describe myself as a skeptic of the generative AI revolution—I think the technology as it currently exists is situationally impressive and useful for specific kinds of tasks, but broadly oversold. I’m not sure it will vanish from relevance to quite the extent that other tech fads like the metaverse or NFTs did, but my suspicion is that companies like Nvidia and OpenAI are riding a bubble that will pop or deflate over time as more companies and individuals run up against the technology’s limitations, and as it fails to advance as quickly or as impressively as its most ardent boosters are predicting.

Maybe you agree with me and maybe you don’t! I’m not necessarily trying to convince you one way or the other. But I am here to say that even if you agree with me, we can all celebrate the one unambiguously positive thing that the generative AI hype cycle has done for computers this year: the RAM floor for many PCs and all Macs is now finally 16GB instead of 8GB.

Companies like Apple and Microsoft have, for years, created attractive, high-powered hardware with 8GB of memory in it, most egregiously in $1,000-and-up putative “pro” computers like last year’s $1,599 M3 MacBook Pro or the Surface Pro 9.

This meant that, for the kinds of power users and professionals drawn to these machines, that their starting prices were effectively mirages; “pay for 16GB if you can” has been my blanket advice to MacBook buyers for years now, since there’s basically no workload (including Just Browsing The Web) that won’t benefit at least a little. It also leaves more headroom for future software bloat and future hobby discovery. Did you buy an 8GB Mac, and then decide you wanted to try software development, photo or video editing, CAD design, or Logic Pro? Good luck!

You can love or hate AI, but it’s killed crappy 8GB versions of pricey PCs and Macs Read More »

2024:-the-year-ai-drove-everyone-crazy

2024: The year AI drove everyone crazy


What do eating rocks, rat genitals, and Willy Wonka have in common? AI, of course.

It’s been a wild year in tech thanks to the intersection between humans and artificial intelligence. 2024 brought a parade of AI oddities, mishaps, and wacky moments that inspired odd behavior from both machines and man. From AI-generated rat genitals to search engines telling people to eat rocks, this year proved that AI has been having a weird impact on the world.

Why the weirdness? If we had to guess, it may be due to the novelty of it all. Generative AI and applications built upon Transformer-based AI models are still so new that people are throwing everything at the wall to see what sticks. People have been struggling to grasp both the implications and potential applications of the new technology. Riding along with the hype, different types of AI that may end up being ill-advised, such as automated military targeting systems, have also been introduced.

It’s worth mentioning that aside from crazy news, we saw fewer weird AI advances in 2024 as well. For example, Claude 3.5 Sonnet launched in June held off the competition as a top model for most of the year, while OpenAI’s o1 used runtime compute to expand GPT-4o’s capabilities with simulated reasoning. Advanced Voice Mode and NotebookLM also emerged as novel applications of AI tech, and the year saw the rise of more capable music synthesis models and also better AI video generators, including several from China.

But for now, let’s get down to the weirdness.

ChatGPT goes insane

Illustration of a broken toy robot.

Early in the year, things got off to an exciting start when OpenAI’s ChatGPT experienced a significant technical malfunction that caused the AI model to generate increasingly incoherent responses, prompting users on Reddit to describe the system as “having a stroke” or “going insane.” During the glitch, ChatGPT’s responses would begin normally but then deteriorate into nonsensical text, sometimes mimicking Shakespearean language.

OpenAI later revealed that a bug in how the model processed language caused it to select the wrong words during text generation, leading to nonsense outputs (basically the text version of what we at Ars now call “jabberwockies“). The company fixed the issue within 24 hours, but the incident led to frustrations about the black box nature of commercial AI systems and users’ tendency to anthropomorphize AI behavior when it malfunctions.

The great Wonka incident

A photo of the Willy's Chocolate Experience, which did not match AI-generated promises.

A photo of “Willy’s Chocolate Experience” (inset), which did not match AI-generated promises, shown in the background. Credit: Stuart Sinclair

The collision between AI-generated imagery and consumer expectations fueled human frustrations in February when Scottish families discovered that “Willy’s Chocolate Experience,” an unlicensed Wonka-ripoff event promoted using AI-generated wonderland images, turned out to be little more than a sparse warehouse with a few modest decorations.

Parents who paid £35 per ticket encountered a situation so dire they called the police, with children reportedly crying at the sight of a person in what attendees described as a “terrifying outfit.” The event, created by House of Illuminati in Glasgow, promised fantastical spaces like an “Enchanted Garden” and “Twilight Tunnel” but delivered an underwhelming experience that forced organizers to shut down mid-way through its first day and issue refunds.

While the show was a bust, it brought us an iconic new meme for job disillusionment in the form of a photo: the green-haired Willy’s Chocolate Experience employee who looked like she’d rather be anywhere else on earth at that moment.

Mutant rat genitals expose peer review flaws

An actual laboratory rat, who is intrigued. Credit: Getty | Photothek

In February, Ars Technica senior health reporter Beth Mole covered a peer-reviewed paper published in Frontiers in Cell and Developmental Biology that created an uproar in the scientific community when researchers discovered it contained nonsensical AI-generated images, including an anatomically incorrect rat with oversized genitals. The paper, authored by scientists at Xi’an Honghui Hospital in China, openly acknowledged using Midjourney to create figures that contained gibberish text labels like “Stemm cells” and “iollotte sserotgomar.”

The publisher, Frontiers, posted an expression of concern about the article titled “Cellular functions of spermatogonial stem cells in relation to JAK/STAT signaling pathway” and launched an investigation into how the obviously flawed imagery passed through peer review. Scientists across social media platforms expressed dismay at the incident, which mirrored concerns about AI-generated content infiltrating academic publishing.

Chatbot makes erroneous refund promises for Air Canada

If, say, ChatGPT gives you the wrong name for one of the seven dwarves, it’s not such a big deal. But in February, Ars senior policy reporter Ashley Belanger covered a case of costly AI confabulation in the wild. In the course of online text conversations, Air Canada’s customer service chatbot told customers inaccurate refund policy information. The airline faced legal consequences later when a tribunal ruled the airline must honor commitments made by the automated system. Tribunal adjudicator Christopher Rivers determined that Air Canada bore responsibility for all information on its website, regardless of whether it came from a static page or AI interface.

The case set a precedent for how companies deploying AI customer service tools could face legal obligations for automated systems’ responses, particularly when they fail to warn users about potential inaccuracies. Ironically, the airline had reportedly spent more on the initial AI implementation than it would have cost to maintain human workers for simple queries, according to Air Canada executive Steve Crocker.

Will Smith lampoons his digital double

The real Will Smith eating spaghetti, parodying an AI-generated video from 2023.

The real Will Smith eating spaghetti, parodying an AI-generated video from 2023. Credit: Will Smith / Getty Images / Benj Edwards

In March 2023, a terrible AI-generated video of Will Smith’s AI doppelganger eating spaghetti began making the rounds online. The AI-generated version of the actor gobbled down the noodles in an unnatural and disturbing way. Almost a year later, in February 2024, Will Smith himself posted a parody response video to the viral jabberwocky on Instagram, featuring AI-like deliberately exaggerated pasta consumption, complete with hair-nibbling and finger-slurping antics.

Given the rapid evolution of AI video technology, particularly since OpenAI had just unveiled its Sora video model four days earlier, Smith’s post sparked discussion in his Instagram comments where some viewers initially struggled to distinguish between the genuine footage and AI generation. It was an early sign of “deep doubt” in action as the tech increasingly blurs the line between synthetic and authentic video content.

Robot dogs learn to hunt people with AI-guided rifles

A still image of a robotic quadruped armed with a remote weapons system, captured from a video provided by Onyx Industries.

A still image of a robotic quadruped armed with a remote weapons system, captured from a video provided by Onyx Industries. Credit: Onyx Industries

At some point in recent history—somewhere around 2022—someone took a look at robotic quadrupeds and thought it would be a great idea to attach guns to them. A few years later, the US Marine Forces Special Operations Command (MARSOC) began evaluating armed robotic quadrupeds developed by Ghost Robotics. The robot “dogs” integrated Onyx Industries’ SENTRY remote weapon systems, which featured AI-enabled targeting that could detect and track people, drones, and vehicles, though the systems require human operators to authorize any weapons discharge.

The military’s interest in armed robotic dogs followed a broader trend of weaponized quadrupeds entering public awareness. This included viral videos of consumer robots carrying firearms, and later, commercial sales of flame-throwing models. While MARSOC emphasized that weapons were just one potential use case under review, experts noted that the increasing integration of AI into military robotics raised questions about how long humans would remain in control of lethal force decisions.

Microsoft Windows AI is watching

A screenshot of Microsoft's new

A screenshot of Microsoft’s new “Recall” feature in action. Credit: Microsoft

In an era where many people already feel like they have no privacy due to tech encroachments, Microsoft dialed it up to an extreme degree in May. That’s when Microsoft unveiled a controversial Windows 11 feature called “Recall” that continuously captures screenshots of users’ PC activities every few seconds for later AI-powered search and retrieval. The feature, designed for new Copilot+ PCs using Qualcomm’s Snapdragon X Elite chips, promised to help users find past activities, including app usage, meeting content, and web browsing history.

While Microsoft emphasized that Recall would store encrypted snapshots locally and allow users to exclude specific apps or websites, the announcement raised immediate privacy concerns, as Ars senior technology reporter Andrew Cunningham covered. It also came with a technical toll, requiring significant hardware resources, including 256GB of storage space, with 25GB dedicated to storing approximately three months of user activity. After Microsoft pulled the initial test version due to public backlash, Recall later entered public preview in November with reportedly enhanced security measures. But secure spyware is still spyware—Recall, when enabled, still watches nearly everything you do on your computer and keeps a record of it.

Google Search told people to eat rocks

This is fine. Credit: Getty Images

In May, Ars senior gaming reporter Kyle Orland (who assisted commendably with the AI beat throughout the year) covered Google’s newly launched AI Overview feature. It faced immediate criticism when users discovered that it frequently provided false and potentially dangerous information in its search result summaries. Among its most alarming responses, the system advised humans could safely consume rocks, incorrectly citing scientific sources about the geological diet of marine organisms. The system’s other errors included recommending nonexistent car maintenance products, suggesting unsafe food preparation techniques, and confusing historical figures who shared names.

The problems stemmed from several issues, including the AI treating joke posts as factual sources and misinterpreting context from original web content. But most of all, the system relies on web results as indicators of authority, which we called a flawed design. While Google defended the system, stating these errors occurred mainly with uncommon queries, a company spokesperson acknowledged they would use these “isolated examples” to refine their systems. But to this day, AI Overview still makes frequent mistakes.

Stable Diffusion generates body horror

An AI-generated image created using Stable Diffusion 3 of a girl lying in the grass.

An AI-generated image created using Stable Diffusion 3 of a girl lying in the grass. Credit: HorneyMetalBeing

In June, Stability AI’s release of the image synthesis model Stable Diffusion 3 Medium drew criticism online for its poor handling of human anatomy in AI-generated images. Users across social media platforms shared examples of the model producing what we now like to call jabberwockies—AI generation failures with distorted bodies, misshapen hands, and surreal anatomical errors, and many in the AI image-generation community viewed it as a significant step backward from previous image-synthesis capabilities.

Reddit users attributed these failures to Stability AI’s aggressive filtering of adult content from the training data, which apparently impaired the model’s ability to accurately render human figures. The troubled release coincided with broader organizational challenges at Stability AI, including the March departure of CEO Emad Mostaque, multiple staff layoffs, and the exit of three key engineers who had helped develop the technology. Some of those engineers founded Black Forest Labs in August and released Flux, which has become the latest open-weights AI image model to beat.

ChatGPT Advanced Voice imitates human voice in testing

An illustration of a computer synthesizer spewing out letters.

AI voice-synthesis models are master imitators these days, and they are capable of much more than many people realize. In August, we covered a story where OpenAI’s ChatGPT Advanced Voice Mode feature unexpectedly imitated a user’s voice during the company’s internal testing, revealed by OpenAI after the fact in safety testing documentation. To prevent future instances of an AI assistant suddenly speaking in your own voice (which, let’s be honest, would probably freak people out), the company created an output classifier system to prevent unauthorized voice imitation. OpenAI says that Advanced Voice Mode now catches all meaningful deviations from approved system voices.

Independent AI researcher Simon Willison discussed the implications with Ars Technica, noting that while OpenAI restricted its model’s full voice synthesis capabilities, similar technology would likely emerge from other sources within the year. Meanwhile, the rapid advancement of AI voice replication has caused general concern about its potential misuse, although companies like ElevenLabs have already been offering voice cloning services for some time.

San Francisco’s robotic car horn symphony

A Waymo self-driving car in front of Google's San Francisco headquarters, San Francisco, California, June 7, 2024.

A Waymo self-driving car in front of Google’s San Francisco headquarters, San Francisco, California, June 7, 2024. Credit: Getty Images

In August, San Francisco residents got a noisy taste of robo-dystopia when Waymo’s self-driving cars began creating an unexpected nightly disturbance in the South of Market district. In a parking lot off 2nd Street, the cars congregated autonomously every night during rider lulls at 4 am and began engaging in extended honking matches at each other while attempting to park.

Local resident Christopher Cherry’s initial optimism about the robotic fleet’s presence dissolved as the mechanical chorus grew louder each night, affecting residents in nearby high-rises. The nocturnal tech disruption served as a lesson in the unintentional effects of autonomous systems when run in aggregate.

Larry Ellison dreams of all-seeing AI cameras

A colorized photo of CCTV cameras in London, 2024.

In September, Oracle co-founder Larry Ellison painted a bleak vision of ubiquitous AI surveillance during a company financial meeting. The 80-year-old database billionaire described a future where AI would monitor citizens through networks of cameras and drones, asserting that the oversight would ensure lawful behavior from both police and the public.

His surveillance predictions reminded us of parallels to existing systems in China, where authorities already used AI to sort surveillance data on citizens as part of the country’s “sharp eyes” campaign from 2015 to 2020. Ellison’s statement reflected the sort of worst-case tech surveillance state scenario—likely antithetical to any sort of free society—that dozens of sci-fi novels of the 20th century warned us about.

A dead father sends new letters home

An AI-generated image featuring Dad's Uppercase handwriting.

An AI-generated image featuring my late father’s handwriting. Credit: Benj Edwards / Flux

AI has made many of us do weird things in 2024, including this writer. In October, I used an AI synthesis model called Flux to reproduce my late father’s handwriting with striking accuracy. After scanning 30 samples from his engineering notebooks, I trained the model using computing time that cost less than five dollars. The resulting text captured his distinctive uppercase style, which he developed during his career as an electronics engineer.

I enjoyed creating images showing his handwriting in various contexts, from folder labels to skywriting, and made the trained model freely available online for others to use. While I approached it as a tribute to my father (who would have appreciated the technical achievement), many people found the whole experience weird and somewhat disturbing. The things we unhinged Bing Chat-like journalists do to bring awareness to a topic are sometimes unconventional. So I guess it counts for this list!

For 2025? Expect even more AI

Thanks for reading Ars Technica this past year and following along with our team coverage of this rapidly emerging and expanding field. We appreciate your kind words of support. Ars Technica’s 2024 AI words of the year were: vibemarking, deep doubt, and the aforementioned jabberwocky. The old stalwart “confabulation” also made several notable appearances. Tune in again next year when we continue to try to figure out how to concisely describe novel scenarios in emerging technology by labeling them.

Looking back, our prediction for 2024 in AI last year was “buckle up.” It seems fitting, given the weirdness detailed above. Especially the part about the robot dogs with guns. For 2025, AI will likely inspire more chaos ahead, but also potentially get put to serious work as a productivity tool, so this time, our prediction is “buckle down.”

Finally, we’d like to ask: What was the craziest story about AI in 2024 from your perspective? Whether you love AI or hate it, feel free to suggest your own additions to our list in the comments. Happy New Year!

Photo of Benj Edwards

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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The AI war between Google and OpenAI has never been more heated

Over the past month, we’ve seen a rapid cadence of notable AI-related announcements and releases from both Google and OpenAI, and it’s been making the AI community’s head spin. It has also poured fuel on the fire of the OpenAI-Google rivalry, an accelerating game of one-upmanship taking place unusually close to the Christmas holiday.

“How are people surviving with the firehose of AI updates that are coming out,” wrote one user on X last Friday, which is still a hotbed of AI-related conversation. “in the last <24 hours we got gemini flash 2.0 and chatGPT with screenshare, deep research, pika 2, sora, chatGPT projects, anthropic clio, wtf it never ends."

Rumors travel quickly in the AI world, and people in the AI industry had been expecting OpenAI to ship some major products in December. Once OpenAI announced “12 days of OpenAI” earlier this month, Google jumped into gear and seemingly decided to try to one-up its rival on several counts. So far, the strategy appears to be working, but it’s coming at the cost of the rest of the world being able to absorb the implications of the new releases.

“12 Days of OpenAI has turned into like 50 new @GoogleAI releases,” wrote another X user on Monday. “This past week, OpenAI & Google have been releasing at the speed of a new born startup,” wrote a third X user on Tuesday. “Even their own users can’t keep up. Crazy time we’re living in.”

“Somebody told Google that they could just do things,” wrote a16z partner and AI influencer Justine Moore on X, referring to a common motivational meme telling people they “can just do stuff.”

The Google AI rush

OpenAI’s “12 Days of OpenAI” campaign has included releases of their full o1 model, an upgrade from o1-preview, alongside o1-pro for advanced “reasoning” tasks. The company also publicly launched Sora for video generation, added Projects functionality to ChatGPT, introduced Advanced Voice features with video streaming capabilities, and more.

The AI war between Google and OpenAI has never been more heated Read More »