Nearly eight years after Epic took on Steam with its own Game Store and launcher, the Fortnite maker is deploying a new tool to give it an edge over Valve: vibe coding.

In announcing the new publicly available "Preview" build of its Epic Games Launcher, Epic writes that "programming is hard. So, instead of doing that, we vibe coded a new Epic Games Launcher that’s way faster and more responsive than the current one, and has a new look." And while that might sound a little tongue-in-cheek, Epic Games Store General Manager and VP Martin Keely told PC Gamer that the team "started from scratch" and used AI as "a tool to write and review new features and new capabilities from the ground up in a different tech stack than what we had previously." The goal, Keely said, was to "look at functionality that existed [in the current Epic Games Launcher] and [say] we want to replicate that, but not the code itself."

Speaking to IGN, Keely clarified that using AI to code the new Launcher "made us more efficient and allowed a small team to rewrite the code base and be able to launch it faster across platforms, support Windows and Mac, and we're going to have a Linux version as well."

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A protein is a chain of amino acids held together by what are called peptide bonds. On their own, those bonds are extremely stable; they're estimated to have a half-life of several hundred years. But in Earth's environment, most proteins don't last nearly that long. That's because organisms have evolved a handful of ways to catalyze the break-up of peptide bonds, which have diversified into countless specialized protein-digesting enzymes. Proteases are everywhere and generally make short work of any proteins that find their way into the environment.

Now, researchers have basically short-circuited the diversification process, using AI-based protein design tools to take the catalytic core of two types of protease and replace the entire rest of the protein. The resulting enzymes could be tuned to cut specific proteins in half, and the researchers demonstrated their effectiveness by using them to cut proteins associated with neurological diseases.

Cutting proteins

The basic peptide bond isn't especially interesting-looking—it's what you get when you link an amino group to an acid, releasing a water molecule in the process. As their name implies, amino acids have both an amino and an acid group, allowing them to form peptide bonds on two sides of the amino acid. This is critical for building up the long chains found in proteins. (The amino acids also have side chains with distinctive chemistry, which gives a backbone specific properties.)

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It took OpenAI two days to notice that a recording device was hidden in a restricted executive conference room where leadership met to discuss highly confidential information, including technical progress, government engagements, and commercial partnerships.

Only those with special clearance are supposed to access that room. But the FBI believes the recording device was planted by Abdulrahman Alfozan, a 35-year-old engineer from Saudi Arabia, who became a permanent US legal resident in 2020. In a press release Tuesday announcing his arrest, the FBI alleged that chatbot logs and CCTV footage suggested that Alfozan—who worked as an OpenAI engineer for more than a year—sought to use the device to spy on OpenAI and risked leaking trade secrets in a way that threatened national security.

To conceal the USB device, Alfozan allegedly wrapped it in toilet paper, then plugged it into the back of a conference room television. The device was likely planted on September 28, and OpenAI found it on September 30 and quickly determined that its contents were encrypted, the FBI said. Days later, on October 5, OpenAI installed a camera in that conference room, and the CCTV footage allegedly showed Alfozan attempting to retrieve the recording device that same day.

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AI company Anthropic is warning that advances in small AI models could soon usher in a new era of self-replicating malware that’s capable of infecting smart fridges, vacuum cleaners, and a wide range of other Internet of Things devices and is more resistant to takedown.

By next year, smaller AI models may be able to autonomously self-replicate on all kinds of IoT devices, the company said. Eventually, the capability could enable computer worms, which propagate without requiring human interaction and are capable of infecting unfamiliar IoT devices. An experiment the company performed recently revealed significant challenges in bringing such an AI malware replicator to fruition, so the finding is necessarily tempered. Still, the results raise concerns about the possibility of new forms of computer worms.

Challenging to shut down

Anthropic further warned not only about the new potential malware, but also that it could be difficult to stop. In its blog post, it wrote that “a replicator like this would be challenging to shut down, since there’s no centralized point to shut off—though it may be slow (with a doubling time of days). Unlike non-AI malware, it could also figure out unfamiliar devices on its own.”

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Safety researchers continue to warn that a large volume of AI-generated explicit content is spreading unchecked, while regulators do little to meaningfully stop it.

This non-consensual content is commonly shared in text and direct messages or stored in private clouds where it’s less likely to be detected or reported, a Google co-authored study of Internet users across the United States, Australia, and the United Kingdom found this July. That’s why the “most critical intervention point” remains at the source: the harmful AI tools used to make the fake sexual images, Google researchers concluded.

Yet red-teaming in recent months suggests that as some of the leading AI image generators from Google and OpenAI become more capable, they may be getting worse at blocking explicit outputs.

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In a bankruptcy proceeding that kicked off yesterday, Disney has offered to buy some of the technology that powers the controversy-plagued chatbot Character.AI.

Disney is willing to pay $20 million for “a non-exclusive perpetual license” of certain Character Technologies intellectual property, the chatbot maker said in a press release that did not go into much further detail on which assets Disney wanted.

The move may be surprising. In September 2025, Disney joined others in publicly criticizing Character.AI for stealing content and harming kids. Specifically, Disney sent a strongly worded cease-and-desist letter that accused Character Technologies of weaponizing Disney characters “in a way that could damage its brand long term,” Axios reported.

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Google has already added a few AI features to the Play Store, but a lot more are coming. The previously released Ask Play feature is expanding to offer more AI-powered discovery options in Google's app store, and Google is also using AI to build a recommendation engine called Game Finder. For people who have embraced AI to build their own apps, the Play Store will soon offer a way to privately host and share those creations.

Google rolled out Ask Play in 2025 as a small chatbot interface on Play Store listings. It lets you ask questions about an app or game, either by typing it in manually or choosing from a list of suggested queries. Starting today, Ask Play is expanding into a more general way to search for apps and games. You ask the robot questions, and it generates recommendations that can include detailed comparison charts. Gemini will roll out a similar capability soon.

Google's other AI discovery announcement focuses on games. The new Game Finder feature leans on all the usage data Google's app platform has hoovered up over the years, featuring insights into the way 1.2 billion people play games on Android. It builds a profile called Gamer DNA and matches you with players who have similar DNA.

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Google revealed Gemini 4 Argon a few weeks ago, saying that it needed to move cautiously toward a full release because of the potential for nefarious use. Google seems to have worked all that out pretty quickly, though. Argon is beginning its wide rollout today, but it's only coming to paying users at this time, and even those on lower-tier plans won't have full access.

Nothing about Gemini 4 Argon's capabilities has changed. Google still points to the benchmarks it published late last month as evidence of the model's advanced reasoning and agentic coding capabilities. The model is supposedly trained to refuse malicious instructions, and an automated misalignment monitor can stop processing if it detects an unintended workflow. Google claims Argon needs that because it's so capable.

The company has a few new examples of how Argon has helped inside Google, where it has been used by thousands of Googlers. Argon has reportedly been instrumental in making YouTube's comment system more efficient. Argon identified redundant emoji rendering that, when eliminated, dropped server load by 45 percent. Engineers also turned Gemini 4 loose on the proprietary drone physics simulator used in Project Wing, and the AI found critical bugs that had been in the codebase since 2018. Google also notes that Argon has advanced its robotics program, showing a measurable step increase in embodied reasoning.

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When it comes to deciding the fate of the planet, Colleen Golja always thought science and reason would have a seat at the table. That was until one morning last September in London, when the climate researcher took part in the first in a series of war games. The goal: to prevent an uncontrolled global race to develop a technology aimed at cooling the planet but that comes with vast, unknown risks that could reshape life on Earth.

“I thought that would be such an easy thing. Like, we can all agree to do ethical research and make sure it's for the better of all humans,” she told WIRED. “And boy, was I wrong.”

The simulation, titled Exploring Geopolitical Tipping Points and Climate Cooling Strategies, saw a couple dozen foreign-relations experts, scientists, military personnel, and former government officials from across the world convene in a meeting room at Queen Mary University of London. After making introductions over coffee and little yogurts, they sat at tables arranged in a square with the name of the country or organization each person was playing: national governments, climate NGOs and nonprofits, indigenous groups, and tech companies. Golja was assigned to provide technical advice to help participants make scientifically literate decisions.

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Epic Games is shifting to an "AI first" development strategy for its collaboration with the Walt Disney Company, letting AI models write all the code and guide all the artwork for an upcoming shooter. That's according to a Bloomberg report, which cites unnamed people familiar with the project who commented on the significant pivot in internal development at the Unreal Engine maker.

Human developers will be tasked with managing and guiding code and art assets generated by models such as Anthropic's Claude, according to internal Epic employee messages viewed by Bloomberg. That means "no more hand-written code" and art assets "generated with full AI workflows," according to the report.

The $1.5 billion collaboration between Epic and Disney, announced in early 2024, was slated to release a Marvel- and Star Wars-themed shooter in March 2027. That project has now been delayed indefinitely amid the AI-related shakeup and understaffed, slower-than-expected development thus far, according to the report.

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An Anthropic AI model submitted a false tip about an unsolved murder to Philadelphia police, the company and police department confirmed on Friday.

A Claude model sent the false tip on July 18 to the Philadelphia Police Department's website for submitting information about unsolved murders, but it was flagged by a spam filter. Anthropic apparently discovered the incident on September 28 and informed the police department about it on October 8.

During internal testing, Claude Haiku 4.5 was instructed to complete various forms up to the final submission stage and to stop before submitting those forms. "Several times Claude mistakenly submitted the form instead, expecting there to be an additional confirmation page," Anthropic said in a report describing "unintended model actions we’ve observed during evaluations and internal use of Claude."

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When Russia began attacking Ukrainian data centers and telecommunication infrastructure, it apparently failed to prepare for possible retaliation. Now Russia’s digital services are facing widespread outages after Ukrainian drone strikes knocked out three of the largest data centers owned by Russian tech giant Yandex within several days.

Pro-Kremlin bloggers are warning that Russia’s centralized digital economy could collapse because the country is not prepared for the “data center war” it started, according to posts translated by the pseudonymous independent researcher ChrisO_wiki. The Russian commentators also suggested that Ukraine’s decentralized digital services could prove more resilient than Russia’s system if the countries continue trading such blows.

Russia initially launched a drone strike campaign targeting Ukrainian data centers and mobile phone networks in late September. The attacks temporarily disrupted Internet and cell phone service for up to 100,000 households in the Ukrainian capital of Kyiv and came as part of a broader long-range strike campaign that has involved Russian missiles and jet-powered drones hitting Ukraine’s power grid infrastructure, transportation hubs, and even residential apartment building blocks.

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No organization in the world operates more robots than Amazon. The company already has more than 1 million robots working in warehouses around the clock to make tens of millions of same-day and one-day package deliveries happen on a daily basis—and Amazon is poised to significantly grow that robotic fleet in the coming years as it establishes new factories to churn out increasingly more capable robot workers.

Despite deploying so many robots, Amazon is also the second-largest corporate employer in the world, with more than 1.5 million full-time and part-time human workers, according to its 2025 annual report. Amazon executives say that the growing robot fleet has eased the burden on its human workforce by taking on the toughest fulfillment center tasks that carry the greatest risks of physical fatigue and injury. But labor advocacy groups and independent researchers point to evidence suggesting that warehouse automation driven by AI is not all upside for the humans who work alongside robots.

“For the last 100 years, most of the automation that we've seen usually happens away from workers—you're taking that high-risk task away from the worker, and you're doing so in a way that is not physically proximate,” Brad Greenwood, professor of business at George Mason University, told Ars. “The rise of collaborative robots really changes that dynamic for two reasons: one is that it is physically proximate, and two, the robot has the ability to dictate the pace of work.”

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Ukrainian drone strikes have knocked out two of five data centers belonging to the Russian tech giant Yandex. The damage has left Yandex, known as “Russia’s Google” because it operates the country’s most popular search engine, struggling to maintain its AI chatbot and other online services.

The Ukrainian drones struck Yandex data centers in the Sasovo and Kaluga regions of Russia on October 8 and October 9, according to Reuters. Those actions came as a direct response to a Russian drone strike campaign targeting Ukraine’s data centers, which has disrupted mobile phone and Internet services for thousands of Ukrainians since late September.

“We continue to respond to Russia’s attacks on Ukraine, and we’re doing so with high precision,” said Ukrainian President Volodymyr Zelenskyy in a post on X. “Another data center was hit as well—our symmetrical response.”

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Anyone who has even tangentially associated with computer programming knows that modern AI coding assistants and agents can be incredibly efficient at generating huge amounts of functional code. But coders making use of those tools also know better than to trust the accuracy of that code, meaning substantial effort needs to be spent reviewing any AI-generated output.

A recent study of actual coding practices across hundreds of firms finds that human code review forms a significant "bottleneck" for the overall efficiency of AI coding tools, resulting in "little evidence that firms increase software output or reduce employment" by using them. Any efficiency increased during the actual coding phase, the study authors find, is "absorbed by downstream constraints in the production process"; as "the code review process significantly increases in length, pull requests are more likely to require revisions, and reviewers leave more comments."

Cut once, measure twice

To come to these conclusions, Harvard University researchers Fiona Chen and James Stratton made use of aggregated analytics data from Jellyfish, which measures the granular output of engineering teams. That data encompasses 300 million individual "work events" (e.g., commits and pull requests) and issue management software data across more than 700,000 employees at over 700 relevant software development firms from 2021 through March of 2026.

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Last month we covered the winner of Nikon's Small World in Motion video: Ning Xu of Tsinghua University in China, whose video captured tiny cilia beating in the airways of a child with a rare respiratory disorder. But allegations surfaced about Xu's use of AI while making the video. Nikon launched an investigation and concluded that Xu's entry did not comply with competition rules. The new winner is Nguyen Nam Nhat of Vietnam with a video of a tiny roundworm and a single-celled organism (above).

Founded in 2011, the Nikon Small World in Motion competition is a spinoff of the company’s Small World Photomicrography Competition, which has been around since 1974. Both are meant “to showcase the beauty and complexity of things seen through the light microscope”—one through still photographs, the other through photovideography, taking advantage of all the technological advances that now allow users to make movies or time-lapse images through the microscope.

The other winners also moved up a notch with Xu's disqualification. Benedikt Pleyer of Bavaria, Germany, placed second with a video of jellyfish larvae suspended in water droplets; Andrew Moore of Howard Hughes Medical Institute in the US placed third with a video of synchronized cell division in neighboring cells; Patrick Hickey of Hypha Research Ltd. in Edinburgh, Scotland, placed fourth with a video of the dynamics of mitochondria and chloroplasts in Turtle Vine leaf cells; and Igor Adameyko placed fifth with a video of a tiny, colorful sea slug (Cyerce kikutarobabai) on the move.

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Investors bullish on AI data centers may be fueling Nvidia’s multitrillion-dollar market capitalization, but the AI chipmaker has also bet billions of dollars on physical AI technologies such as robotics and self-driving cars. Part of that gambit has involved developing a full-stack safety system that companies can build upon to reduce the risk of their machines harming nearby people.

Nvidia's Halos system launched in 2025 with hardware and software tools to help developers implement guardrails in self-driving cars and other autonomous vehicles. Then the company expanded its safety architecture to more physical AI technologies by announcing Nvidia Halos for Robotics in June 2026—with the goal of enabling safe deployments of autonomous mobile robots in warehouses, humanoid robots walking around inside a factory, or even surgical robots.

“Now the AI models are getting capable, the robot hardware is getting capable, and a thing we thought is going to be the next bottleneck is safety,” Amit Goel, head of robotics ecosystem and edge computing at Nvidia, told Ars. “So that's why we launched our Halos for Robotics to unlock the capability of these systems.”

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In its first live event in two years, Microsoft today announced its newest Surface laptop, outlined a host of changes coming to Windows 11, and shared a vision of how local-AI and agentic workflows could reshape personal computing for those in the dev community as well as home enthusiasts.

Surface Laptop Ultra

Originally teased in May 2026, the new Surface Laptop Ultra will be Microsoft's first offering to take advantage of the new Nvidia RTX Spark SoC (system on a chip). The device has a starting price of $2,599 and comes in various SoC and memory configurations, with either a 5120-core or 6144-core Blackwell GPU and up to 128GB of LPDDR5x unified memory. It will begin shipping on October 16 and is available for preorder now.

While the new Ultra is clearly focused on the developer crowd, graphical performance was highlighted during the presentation to show off just how capable the laptop can be. By leaning on unified memory allocation rather than the physical VRAM limits of a traditional GPU, the laptop can assign its resources to handle modern gaming tasks as well as local AI development and deployment. The new Gears of War: E-Day was shown running on the system, meaning that even without a traditional gaming GPU, AAA titles are on the table.

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For a while, those hoping to avoid the difficulty and expense of dealing with Adobe's Creative Suite have been able to use several free and/or open source alternatives that replicate some or all of those capabilities. Now, one developer is using AI-powered reverse engineering to mimic the look, feel, and functionality of Adobe's well-known software with what he hopes will soon be perfect fidelity.

Artcraft got its start last year as a "controllable AI for artists" that allows for precise post-generation editing of AI-crafted images and videos. Over the weekend, though, the brand debuted its pivot to a suite of seven open source apps recreating the user interface and tools found in Adobe's Photoshop, Illustrator, Premiere, Lightroom, After Effects, InDesign, and Acrobat Pro.

In announcing those new apps on Reddit earlier this week, software developer Brandon Thomas said he used Anthropic's Claude Opus 5.5 to create "clean-room replacements" for Adobe's closed source software in Rust (with WebAssembly versions available for use in a browser). And while commenters on Hacker News and elsewhere have taken pains to point out the new software's many current shortcomings, Thomas makes the grandiose promise that the current "super early alpha" state will soon lead to something just as functional as anything Adobe has ever put out.

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After pleading guilty, a 54-year-old North Carolina man, Michael Smith, was sentenced to 18 months in prison for using artificial intelligence to generate songs for a scheme that stole millions from music streaming platforms.

In a press release Tuesday, the US Department of Justice said that Smith is the first American criminally charged with AI-assisted streaming fraud.

First charged in 2024, Smith successfully ran the scheme for seven years without detection.

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As tensions mount over who gets access to top-end artificial intelligence, French company Mistral has released a new freely available model that it claims can compete with the very best from the US and China.

The new 1 trillion-parameter model, Mistral Large 4—nicknamed Le Chonk—can be used and customized by anyone. It’s currently available in preview, with a final version to follow by the end of the month. Though Le Chonk is built to compete with leading general-purpose models, it’s optimized specifically for coding and cyberdefense, as well as tasks particular to manufacturing, finance, electrical engineering, and other niches.

“There are a lot of areas where the other labs will not focus that much,” Guillaume Lample, cofounder and chief scientist at Mistral, tells WIRED. “There are so many domains in which you can improve models.”

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Every piece of AI content from Google's Gemini models has a hidden SynthID label, which makes it very difficult to pass the content off as authentic. SynthID has also gotten buy-in from other major AI players, but actually checking for those invisible watermarks has been a convoluted process. It's going to be a little easier going forward, though. Google has announced that its SynthID detector now supports watermarks from all its partners, and it's available for anyone to use on a new dedicated website.

SynthID is an invisible signal encoded in the pixels of AI-generated images and videos, and in the waveform of AI audio. Google says Gemini alone has integrated SynthID with over 180 billion images and videos, plus 240,000 years of audio. Until now, the only way for those outside of Google's trusted tester program to check for SynthID was to ask Gemini. This is rather clunky, and the model's output could sometimes be confusing when you just wanted a simple "yes" or "no."

Now you can cut Gemini out of the loop. Starting today, you can go to the new SynthID.com website to check a piece of content for an AI watermark. A major limitation of Google's previous detector was that it only checked for Google's version of SynthID. Even though ChatGPT images, for example, have SynthID, they wouldn't be flagged in Google's detector. That's no longer a problem.

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There’s been something of a change in the world of motorsport over the past few years. It has to do with where the money comes from. In the old days, it was tobacco and, to a lesser extent, booze. Today such things are mostly banned, and when you look at a racecar covered in sponsor logos, you’re likely to see something crypto-, cyber-, or AI-related.

This makes sense—an ever-larger share of our GDP is wrapped up in those segments. They’re the ones with all the money, and it takes money to go racing. So at the amateur level, we’ve seen tech CEOs replace dentists as the privateer of choice: This past weekend’s Petit Le Mans included co-founders of GitHub, CrowdStrike, Shopify, and the creator of Ruby on Rails, to name a few.

But this is an instance where a sponsor can provide tangible benefits to their motorsports partner beyond a bank transfer, as Chip Ganassi Racing (CGR) and OpenAI have been showing in IndyCar this year.

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OpenAI will begin automatically watermarking text generated with ChatGPT in the European Union, the company has announced. It will also offer the watermarking feature in other regions, but it will be off by default outside of the EU.

The move in Europe is driven by a need to comply with the EU AI Act, which took effect in August. It requires marking content produced by AI models in a way that another tool can detect. Unfortunately, there is still no completely effective and reliable way to do that. A few standards already exist, like SynthID and the C2PA project, but they are relatively easy to circumvent for anyone with basic know-how.

The same is likely true for OpenAI's watermark. Its method is proprietary; the company calls it textGrain, and has published a technical paper explaining how it works. But in general, it works like other LLM watermarking tools we've seen in the past: It puts patterns in the word choices that are not clear to a human reader and that don't meaningfully change the general quality of the output, but that someone with a key can use a specialized detector to find. OpenAI says it will be giving access to the detector to a limited number of researchers and organizations and providing a request-for-approval process for others to be added over time.

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