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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