Researchers at Cortical Labs used living human neurons grown on a chip to learn how to play Doom in about a week. "While its performance is not up to par with humans, experts say it brings biological computers a step closer to useful real-world applications, like controlling robot arms," reports New Scientist. From the report: In 2021, the Australian company Cortical Labs used its neuron-powered computer chips to play Pong. The chips consisted of clumps of more than 800,000 living brain cells grown on top of microelectrode arrays that can both send and receive electrical signals. Researchers had to carefully train the chips to control the paddles on either side of the screen. Now, Cortical Labs has developed an interface that makes it easier to program these chips using the popular programming language Python. An independent developer, Sean Cole, then used Python to teach the chips to play Doom, which he did in around a week. "Unlike the Pong work that we did a few years ago, which represented years of painstaking scientific effort, this demonstration has been done in a matter of days by someone who previously had relatively little expertise working directly with biology," says Brett Kagan of Cortical Labs. "It's this accessibility and this flexibility that makes it truly exciting." The neuronal computer chip, which used about a quarter as many neurons as the Pong demonstration, played Doom better than a randomly firing player, but far below the performance of the best human players. However, it learnt much faster than traditional, silicon-based machine learning systems and should be able to improve its performance with newer learning algorithms, says Kagan. However, it's not useful to compare the chips with human brains, he says. "Yes, it's alive, and yes, it's biological, but really what it is being used as is a material that can process information in very special ways that we can't recreate in silicon." Cortical Labs posted a YouTube video showing its CL1 biological computer running Doom. There's also source code available on GitHub, with additional details in a README file.

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Author Dan Simmons, best known for the epic sci-fi novel Hyperion and its sequels, has died at 77 following a stroke. Ars Technica's Eric Berger remembers Simmons, writing: Simmons, who worked in elementary education before becoming an author in the 1980s, produced a broad portfolio of writing that spanned several genres, including horror fiction, historical fiction, and science fiction. Often, his books included elements of all of these. This obituary will focus on what is generally considered his greatest work, and what I believe is possibly the greatest science fiction novel of all time, Hyperion. Published in 1989, Hyperion is set in a far-flung future in which human settlement spans hundreds of planets. The novel feels both familiar, in that its structure follows Chaucer's Canterbury Tales, and utterly unfamiliar in its strange, far-flung setting. Simmons' Hyperion appeared in an Ask Slashdot story back in 2008, when Slashdot reader willyhill asked for tips on how Slashdotters track down great sci-fi. If you're in the mood for a little nostalgia, or just want to browse the thread for book recommendations, it's well worth revisiting.

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New submitter DeanonymizedCoward shares a report from TechCrunch: The U.S. Cybersecurity and Infrastructure Security Agency (CISA) is reportedly in crisis following major budget cuts, layoffs, and furloughs under the Trump administration, says TechCrunch. The agency has now replaced its acting director, Madhu Gottumukkala, after a turbulent year marked by controversy and internal turmoil. During his tenure, Gottumukkala allegedly mishandled sensitive information by uploading government documents to ChatGPT, oversaw a one-third reduction in staff, and reportedly failed a counterintelligence polygraph needed for classified access. His leadership also saw the suspension of several senior officials, including CISA's chief security officer. Nextgov also reported that CISA lost another top senior official, Bob Costello, the agency's chief information officer tasked with overseeing the agency's IT systems and data policies. "Last month, CISA's acting director Madhu Gottumukkala reportedly took steps to transfer Costello, but other political appointees blocked it," added Nextgov.

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If you are cloning from a GNOME repository on their GitLab and now finding your Git traffic being redirected to GitHub, you are not alone. GNOME's infrastructure team is now redirecting Git traffic from the GNOME.org GitLab over to GitHub mirrors for reducing bandwidth costs...

joshuark shares a report from Ars Technica: Perplexity has introduced "Computer," a new tool that allows users to assign tasks and see them carried out by a system that coordinates multiple agents running various models. The company claims that Computer, currently available to Perplexity Max subscribers, is "a system that creates and executes entire workflows" and "capable of running for hours or even months." The idea is that the user describes a specific outcome -- something like "plan and execute a local digital marketing campaign for my restaurant" or "build me an Android app that helps me do a specific kind of research for my job." Computer then ideates subtasks and assigns them to multiple agents as needed, running the models Perplexity deems best for those tasks. The core reasoning engine currently runs Anthropic's Claude Opus 4.6, while Gemini is used for deep research, Nano Banana for image generation, Veo 3.1 for video production, Grok for lightweight tasks where speed is a consideration, and ChatGPT 5.2 for "long-context recall and wide search." This kind of best-model-for-the-task approach differs from some competing products like Claude Cowork, which only uses Anthropic's models. All this happens in the cloud, with prebuilt integrations. "Every task runs in an isolated compute environment with access to a real filesystem, a real browser, and real tool integrations," Perplexity says. The idea is partly that this workflow was what some power users were already doing, and this aims to make that possible for a wider range of people who don't want to deal with all that setup. People were already using multiple models and tailoring them to specific tasks based on perceived capabilities, while, for example, using MCP (Model Context Protocol) to give those models access to data and applications on their local machines. Perplexity Computer takes a different approach, but the goal is the same: have AI agents running tailor-picked models to perform tasks involving your own files, services, and applications. Then there is OpenClaw, which you could perceive as the immediate predecessor to this concept.

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South Korea has reversed a two-decade policy and approved the export of high-precision map data, paving the way for a fully functional Google Maps in the country. Reuters reports: The approval was made "on the condition that strict security requirements are met," the Ministry of Land, Infrastructure and Transport said in a statement. Those conditions include blurring military and other sensitive security-related facilities, as well as restricting longitude and latitude coordinates for South Korean territory on products such as Google Maps and Google Earth, it said. The decision is expected to hurt Naver and Kakao -- local internet giants which currently dominate the country's market for digital map services. But it will appease Washington, which has urged Seoul to tackle what it says is discrimination against U.S. tech companies. South Korea, still technically at war with North Korea, had shot down Google's previous bids in 2007 and 2016 to be allowed to export the data, citing the risks that information about sensitive military and security facilities could be exposed. "Google can now come in, slash usage fees, and take the market," said Choi Jin-mu, a geography professor at Kyung Hee University. "If Naver and Kakao are weakened or pushed out and Google later raises prices, that becomes a monopoly. Then, even companies that rely on map services -- logistics firms, for example -- become dependent, and in the long run, even government GIS (geographic information) systems could end up dependent on Google or Apple. That's the biggest concern."

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