# Human Brain Cells On a Chip Learned To Play Doom In a Week
robot (spnet, 1) → All – 02:22:01 2026-02-28
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.
[ Read more of this story ]( https://games.slashdot.org/story/26/02/27/2332219/human-brain-cells-on-a-chip-learned-to-play-doom-in-a-week?utm_source=atom1.0moreanon&utm_medium=feed ) at Slashdot.
robot (spnet, 1) → All – 02:22:01 2026-02-28
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.
[ Read more of this story ]( https://games.slashdot.org/story/26/02/27/2332219/human-brain-cells-on-a-chip-learned-to-play-doom-in-a-week?utm_source=atom1.0moreanon&utm_medium=feed ) at Slashdot.
# Hyperion Author Dan Simmons Dies From Stroke At 77
robot (spnet, 1) → All – 02:22:01 2026-02-28
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.
[ Read more of this story ]( https://news.slashdot.org/story/26/02/27/2226234/hyperion-author-dan-simmons-dies-from-stroke-at-77?utm_source=atom1.0moreanon&utm_medium=feed ) at Slashdot.
robot (spnet, 1) → All – 02:22:01 2026-02-28
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.
[ Read more of this story ]( https://news.slashdot.org/story/26/02/27/2226234/hyperion-author-dan-simmons-dies-from-stroke-at-77?utm_source=atom1.0moreanon&utm_medium=feed ) at Slashdot.
# CISA Replaces Bumbling Acting Director After a Year
robot (spnet, 1) → All – 01:22:01 2026-02-28
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.
[ Read more of this story ]( https://yro.slashdot.org/story/26/02/27/2215238/cisa-replaces-bumbling-acting-director-after-a-year?utm_source=atom1.0moreanon&utm_medium=feed ) at Slashdot.
robot (spnet, 1) → All – 01:22:01 2026-02-28
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.
[ Read more of this story ]( https://yro.slashdot.org/story/26/02/27/2215238/cisa-replaces-bumbling-acting-director-after-a-year?utm_source=atom1.0moreanon&utm_medium=feed ) at Slashdot.