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Arthur T Knackerbracket writes:

https://arstechnica.com/science/2026/02/genomes-chart-the-history-of-neanderthal-modern-human-interactions/

By now, it's firmly established that modern humans and their Neanderthal relatives met and mated as our ancestors expanded out of Africa, resulting in a substantial amount of Neanderthal DNA scattered throughout our genome. Less widely recognized is that some of the Neanderthal genomes we've seen have pieces of modern human DNA as well.

Not every modern human has the same set of Neanderthal DNA, however; different people will, by chance, have inherited different fragments. But there are also some areas, termed "Neanderthal deserts," where none of the Neanderthal DNA seems to have persisted. Notably, the largest Neanderthal desert is the entire X chromosome, raising questions about whether this reflects the evolutionary fitness of genes there or mating preferences.

Now, three researchers at the University of Pennsylvania, Alexander Platt, Daniel N. Harris, and Sarah Tishkoff, have done the converse analysis: examining the X chromosomes of the handful of completed Neanderthal genomes we have. It turns out there's also a strong bias toward modern human sequences there, as well, and the authors interpret that as selective mating, with Neanderthal males showing a strong preference for modern human females and their descendants.

Given how long modern humans and Neanderthals had been evolving as separate populations, some degree of genetic incompatibility is definitely possible. Lots of proteins interact in various ways, and the genes behind these interaction networks will evolve together—a change in one gene will often lead to compensatory changes in other genes in the network. Over time, those changes may mean re-introducing the original gene will actually disrupt the network, with a negative impact on fitness.

That means the introduction of some Neanderthal genes into the modern human genome (or vice versa) would be disruptive and make carriers of them less fit. So they'd be selected against and lost over the ensuing generations. Of course, some segments would likely be lost at random—the genome's pretty big, and the modern human population was likely large and growing, allowing its DNA to dilute out the influence of other human populations. Figuring out which influence is dominant can be challenging.

One way to sort this out is to make the same comparison with Neanderthal genomes. If a Neanderthal gene is disruptive in a modern human context, then it's likely that the modern human version will be disruptive in Neanderthals. And, in fact, that's what we seem to see: A look at one Neanderthal genome found that there's some correlation between the Neanderthal deserts in the human genome and the human deserts in that Neanderthal.

All of that, however, doesn't go far to explain the fact that the X chromosome looks like a giant Neanderthal desert, with long stretches of nothing but modern human DNA. The genetics of the X is complicated by the fact that males inherit a single copy from their mothers, so they have only a single copy of almost every gene on it. If any of those genes are causing problems, they will be quickly selected against in males.

Thus, evolutionary selection against the Neanderthal X is definitely an option. The alternative they consider is that it's the product of biased matings. If most mating between the two groups was biased in some way, it could skew the frequency with which the X chromosome was inherited. For example, if most of the matings involved Neanderthal males and modern human females, then you would have fewer Neanderthal X's around as a result, since only half of a male's offspring will inherit an X chromosome from them.

To figure out which result might be the case, the researchers again turned to the three Neanderthal genomes we have available, looking at the pattern of inheritance along the X chromosome. That was compared to X chromosomes from African populations that have very little Neanderthal DNA.

The results contrasted sharply with what was seen elsewhere in the genome, where Neanderthal deserts in modern humans correspond to human deserts in the Neanderthal genome. Instead, the X chromosome in Neanderthals tended to have an excess of modern human sequences—exactly as you see in modern humans. It appears that the modern human X ended up more common in both human and Neanderthal populations.

Could this be from evolutionary selection for something favorable about it? The researchers found that modern human DNA found on the Neanderthal X had a lower than average frequency of important sequences like those that regulate nearby genes or code for proteins. While that doesn't rule out evolutionary selection as a factor, it does make it seem a bit less likely, since there's less indication that the DNA being kept around is functional.

That leaves preferential mating as a more probable explanation. But the modern human DNA was present at such a high frequency on the X that it's difficult to explain by a simple preference of Neanderthal males for modern human females. Instead, you'd have to have a continued preference for the offspring of these matches as well. "We did not rule out more complicated scenarios combining selection and sex biases, such as natural selection acting as a modifying force on top of the strong signature left by sex bias," the authors also note.

Overall, we're left with a picture of a relatively large number of matings between male Neanderthals and modern human females. The offspring of these matings ended up in both the modern human and Neanderthal populations; in the latter, their offspring were favored enough to have led to an excess contribution to the X chromosome.

Science, 2026. "Interbreeding between Neanderthals and modern humans was strongly sex biased"
DOI: 10.1126/science.aea6774 (Source).

Original Submission

Arthur T Knackerbracket writes:

https://www.slashgear.com/2109851/states-cracking-down-drivers-move-over-laws/5def81c4f1d3d85733888dd4951cd6f1

There is a trend in a variety of states across the U.S. to crack down on those motorists who do not observe "Slow Down, Move Over" laws that require drivers to reduce their speed and clear the lane next to emergency responders and motorists who are parked on the shoulders of highways. (In fact, the dangers involved in emergency situations mean some first responders now have robots to assist them.) As of 2012, every state in the union had one of these laws, but they provided protection only to fire, police, and ambulance personnel. As time went on, a number of states expanded these laws to cover road crews, utility vehicles, and tow trucks. The latest development involves expanding these laws to cover anyone who finds themselves stuck by the side of the road.

According to the Emergency Responder Safety Institute, a total of 46 persons responding to a roadside emergency lost their lives while helping people by the roadside during 2024. This was in spite of the presence of Slow Down, Move Over laws being in effect in every single state.

A recent study put out by the AAA Foundation for Traffic Safety has revealed that, because of both drivers' lack of compliance and poor understanding about these laws, more than one-third of all drivers do not slow down or move over when workers are present on the roadside. The other two-thirds either changed lanes or reduced their speed but did not do both. The study found that fewer motorists slowed down or moved over for tow trucks, while a higher percentage conformed with this behavior for police vehicles.

AAA, which offers many services you might have not known about, provided several recommendations for improving the public's awareness of and compliance with these Slow Down, Move Over laws that already exist in every state. It recommends that all 50 states' laws be standardized to give protection to all types of vehicles on the roadside and to any person who happens to end up there. It also suggests a public education campaign that starts with driver's ed. classes and reaches older drivers through public service announcements, navigation apps, and roadway signs.

Finally, AAA acknowledged that more emphasis needs to be put on enforcement of these Slow Down, Move Over laws, with an initial emphasis on making the driving public more aware of these laws. This should then provide the desired result of having more drivers observe them by slowing down and moving over, which will save many more lives of first responders, roadside workers, and anyone else who finds themselves stuck on the side of the road. (Just in case that person is you, you may want to check out these Milwaukee apparel items to keep safe.) And that's a good thing.

Slow Down, Move Over laws already exist in every U.S. state that you will ever drive through. So it only makes sense to be alert for any vehicles stopped by the roadside, slow down if you see any, and move over whenever possible to give them some space to do what they need to do and get home safely.

Original Submission

Arthur T Knackerbracket writes:

Neuron-powered computer chips can now be easily programmed to play a first-person shooter game, bringing biological computers a step closer to useful applications:

A clump of human brain cells can play the classic computer game Doom. 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.

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.

Arthur T Knackerbracket writes:

https://arstechnica.com/ai/2026/02/block-lays-off-40-of-workforce-as-it-goes-all-in-on-ai-tools/c16fbef0848a80413fcac6e5598b4dc9

Block, the fintech group headed by Twitter cofounder Jack Dorsey, will cut its workforce by "nearly half" in one of the clearest signs of the sweeping changes AI tools are having on employment.

Shares in the payment company soared more than 25 percent in after-hours trading on Thursday as it announced it would shed more than 4,000 jobs from its 10,000-strong workforce.

"Intelligence tools have changed what it means to build and run a company. We're already seeing it internally," Dorsey wrote in a letter to shareholders.

"A significantly smaller team, using the tools we're building, can do more and do it better. And intelligence tool capabilities are compounding faster every week."

Dorsey, who left his role as CEO of Twitter in 2021, is among the first Silicon Valley chiefs to explicitly tie huge job cuts to the ability of AI to replace human workers.

Amazon has sought to play down the link to AI after announcing lay-offs totaling 30,000 roles since October, months after CEO Andy Jassy warned the technology would mean "fewer people doing some of the jobs that are being done today" in the coming years, especially in white-collar roles.

Dorsey said he did not think he was early to the realization about the effect that AI could have on work, but that "most companies are late."

He said he expected a "majority of companies" would reach the same conclusion within the next year and make similar structural changes.

The staff reduction at Block comes as anxiety rises about AI leading to job losses across vast parts of the economy.

Investors and economists are grappling with an influx of US economic data and corporate announcements in an effort to gauge the impact the technology could be having on the labor market. The latest non-farm payrolls figures were better than expected, suggesting the domestic jobs market was stabilizing, but several big US companies have committed to cutting staff.

Amazon, UPS, Dow, Nike, Home Depot, and others in late January announced they would be cutting a combined 52,000 jobs.

Dorsey said the cuts at Block, which owns the payment processor Square, came despite what he described as a "strong" financial performance in 2025.

Block has made a contrarian bet on bitcoin at a time when many payment companies favored stablecoins: cash-like digital tokens that became regulated in the US last year.

Block's strategy was spearheaded by Dorsey, a "bitcoin maximalist" who has said he believes the digital currency will eventually eclipse the dollar.

The company offers payment services in bitcoin for merchants and consumers—and suffered a loss on its own bitcoin holdings as the price of the cryptocurrency dropped 23 percent this year.

In contrast, payment companies that made a bet on stablecoins experienced a boost. Stripe earlier this week said its stablecoin transaction volumes increased fourfold last year.

In its fiscal fourth quarter, Block reported revenue of almost $6.3 billion, in line with Wall Street expectations. Its earnings tumbled to 19 cents a share, owing to a $234 million hit on its bitcoin holdings.

Original Submission

Arthur T Knackerbracket writes:

https://www.slashgear.com/2105562/us-military-c-17-airlifts-advanced-nuclear-reactor-california-to-utah/

February 15, 2026 was a historic day for the United States military and the future of nuclear reactors in the United States. That's the day United States Air Force personnel and civilian contractors worked together to load a 5-megawatt nuclear reactor onto a USAF C-17 Globemaster III, an airplane some call the Moose. It was the first time a nuclear reactor was airlifted by a C-17. The March Air Reserve Base, located about 60 miles east of Los Angeles, is home to the 452d Air Mobility Wing, operating a squadron of C-17s among other weapons.

The nuclear reactor, a Ward 250 micro-reactor, fits neatly into the back of the plane, making it easily transportable. The history-making flight saw the Ward 250 transported from March to Utah's Hill Air Force Base, about 30 miles north of Salt Lake City. From there, it'll make its way to the Utah San Rafael Energy Lab where it will undergo more testing and evaluation, according to a press release issued by the U.S. Department of War.

On August 12, 2025, just six months before the historic flight aboard the C-17 Globemaster III, Isaiah Taylor issued a press release announcing his company, Valar Atomics, had been selected to participate in "the President's accelerated nuclear program." The nation's renewed interest in nuclear energy led to a May 23, 2025 Executive Order directing the US Army to build a nuclear microreactor and provide nuclear energy to a domestic military installation by September 30, 2028, and private-sector programs such as the Ward 250.

Valar Atomics developed its WardZero prototype in Los Angeles months before Executive Order 14301 was signed in May of 2025. The US Department of Energy selected the Valar Atomics Ward 250 as one of the projects poised to "achieve criticality on American soil by July 4th, 2026," as directed by section five of EO 14301.

The 5-megawatt Ward 250 nuclear microreactor is about the size of a large van. The power generated by the small package is enough power to service an estimated 5,000 homes or a sizable military installation. With the rapid-deployment capability demonstrated by the February 15th flight, the Ward 250 will eliminate the need for military operations to rely on civilian power grids or diesel-powered generators anywhere in the world.

The USAF Boeing C-17 Globemaster III is a capable aircraft designed to safely transport cargo and military personnel. While the C-5 Galaxy is larger, the C-17 squadron located at March Air Reserve Base offered close proximity to Valar Atomics where the Ward 250 was built and its capabilities closely matching the payload requirements.

Original Submission

fliptop writes:

OpenAI has closed a new funding round that could total $110 billion, valuing the ChatGPT maker at $730 billion pre-money and potentially putting it on course for an IPO in the second half of the year:

The new funding round comes on top of the $40 billion already on OpenAI's balance sheet, giving the company more runway to rapidly expand and develop new models and AI infrastructure. OpenAI expects to remain unprofitable until 2030, when management forecasts it will turn free cash flow positive.

In a separate release, Amazon detailed its major multi-year partnership with OpenAI, centered on enterprise AI infrastructure, distribution, and custom model development.

Here are the highlights of the Amazon-OpenAI investment:

• Amazon will invest $50 billion in OpenAI, with $15 billion upfront and another $35 billion later if certain conditions are met.
• AWS and OpenAI will jointly build a "Stateful Runtime Environment" powered by OpenAI models and offered through Amazon Bedrock, aimed at helping customers run AI apps and agents with persistent context, memory, tool access, and compute.
• AWS becomes the exclusive third-party cloud distribution provider for OpenAI Frontier, OpenAI's enterprise platform for building and managing teams of AI agents.
• OpenAI will expand its AWS infrastructure commitment by $100 billion over 8 years, on top of an existing $38 billion agreement.
• As part of that, OpenAI will use roughly 2 gigawatts of AWS Trainium capacity, spanning Trainium3 and future Trainium4 chips, to support Frontier, Stateful Runtime, and other advanced workloads.
• OpenAI and Amazon will also develop custom OpenAI-based models for Amazon's customer-facing apps, giving Amazon teams another model option alongside its in-house Nova family.

"OpenAI and Amazon share a belief that AI should show up in ways that are practical and genuinely useful for people," OpenAI boss Sam Altman stated, adding, "Combining OpenAI's models with Amazon's infrastructure and global reach helps us put powerful AI into the hands of businesses and users at real scale."

Altman commented on today's announcement, saying, "As long as revenue keeps growing, the deals are not circular."

Previously:

• $100 Billion Mega Deal Between OpenAI and Nvidia is on Ice
• Venture Capital Valuations of AI Startups Surge and Raise Fears of an AI Bubble Forming

Original Submission

owl writes:

https://osmand.net/blog/fast-routing/

Offline navigation is a lifeline for travelers, adventurers, and everyday commuters. We demand speed, accuracy, and the flexibility to tailor routes to our specific needs. For years, OsmAnd has championed powerful, feature-rich offline maps that fit in your pocket. But as maps grew more detailed and user demands for complex routing increased, our trusty A* algorithm, despite its flexibility, started hitting a performance wall. How could we deliver a 100x speed boost without bloating map sizes or sacrificing the deep customization our users love?

The answer: OsmAnd's custom-built Highway Hierarchy (HH) Routing. This isn't your standard routing engine; it's a ground-up redesign, meticulously engineered to overcome the unique challenges of providing advanced navigation on compact, offline-first map data.

Original Submission

fliptop writes:

https://www.irregular.com/publications/vibe-password-generation

To security practitioners, the idea of using LLMs to generate passwords may seem silly. Secure password generation is nuanced, and requires care to implement correctly; the random seed, the source of entropy, the mapping of random output to password characters, and even the random number generation algorithm must be chosen carefully in order to prevent critical password recovery attacks. Moreover, password managers (generators and vaults) have been around for decades, and this is exactly what they’re designed to do.

At the heart of any strong password generator is a cryptographically-secure pseudorandom number generator(CSPRNG), responsible for generating the password characters in such a way that they are very hard to predict, and are drawn from a uniform probability distribution over all possible characters.

Conversely, the LLM output token sampling process is designed to do exactly the opposite. Basically, all LLMs do is iteratively predict the next token; the random generation of tokens is, by definition, predictable (with the token probabilities decided by the LLM), and the probability distribution over all possible tokens is very far from uniform.

In spite of this, LLM-generated passwords are likely to be generated and used. First, with the explosive growth and significant improvement in capabilities of AI over the past year (which, at Irregular, we have also seen direct evidence of in the offensive security domain), AI is much more accessible to less technologically-inclined users. Such users may not know secure methods for password generation, not place importance on them, and rely on ubiquitous AI tools to generate a password instead of looking for a specialized tool, such as a password manager. Moreover, while LLM-generated passwords are insecure, they appear strong and secure to the untrained eye, exacerbating this issue and reducing the likelihood that users will avoid these passwords.

Furthermore, with the recent surge in popularity of coding agents and vibe-coding tools, people are increasingly developing software without looking at the code. We’ve seen that these coding agents are prone to using LLM-generated passwords without the developer’s knowledge or choice. When users don’t review the agent actions or the resulting source code, this “vibe-password-generation” is easy to miss.

TFA shows results obtained using several major LLMs, including GPT, Claude, and Gemini in their latest versions and most powerful variations, and found that all of them generate weak passwords.

Originally spotted on Schneier on Security.

Original Submission

fliptop writes:

A single attacker used Anthropic's Claude and OpenAI's ChatGPT to compromise nine Mexican government agencies, stealing 195 million taxpayer records and voter data:

On February 25, 2026, Bloomberg published a story that would have sounded like fiction two years ago. A lone hacker, with no apparent ties to any government, used Anthropic's Claude chatbot to orchestrate a cyberattack against Mexico's federal and state government agencies. The campaign lasted roughly six weeks, from late December 2025 through January 2026. By the time it was over, the attacker had stolen 150 gigabytes of sensitive data -- including 195 million taxpayer records, voter registration files, government employee credentials, and civil registry data.

The hacker did not use custom malware. They did not deploy a zero-day exploit. They used a consumer AI subscription and a set of carefully written Spanish-language prompts. The AI did the rest.

The breach was uncovered not by any of the affected agencies, but by Gambit Security, an Israeli cybersecurity startup whose researchers stumbled onto publicly accessible conversation logs showing exactly how the attacker coaxed Claude into becoming an offensive hacking assistant. The paper trail was remarkably detailed -- a step-by-step record of how guardrails were tested, resisted, and ultimately bypassed.

"This reality is changing all the game rules we have ever known," said Alon Gromakov, Gambit Security's co-founder and CEO.

TFA goes on to list what was stolen, how Claude was weaponized and how the affected entities responded.

Original Submission

upstart writes:

Hackers Expose The Massive Surveillance Stack Hiding Inside Your “Age Verification” Check:

We’ve been saying this for years now, and we’re going to keep saying it until the message finally sinks in: mandatory age verification creates massive, centralized honeypots of sensitive biometric data that will inevitably be breached. Every single time.

[...] A couple weeks ago, Discord announced it would launch “teen-by-default” settings for its global audience, meaning all users would be shunted into a restricted experience unless they verified their age through biometric scanning. The internet, predictably, was not thrilled. But while many users were busy venting their frustration, a group of security researchers decided to do something more useful: they took a look under the hood at Persona, one of the companies Discord was using for verification (specifically for users in the UK).

[...] Let me say that again: 2,456 publicly accessible files sitting on a government-authorized server, exposed to the open internet. Files that revealed a system performing not a simple age check, but a ton of potentially intrusive checks:

Once a user verifies their identity with Persona,the software performs 269 distinct verification checks and scours the internet and government sources for potential matches, such as by matching your face to politically exposed persons (PEPs), and generating risk and similarity scores for each individual. IP addresses, browser fingerprints, device fingerprints, government ID numbers, phone numbers, names, faces, and even selfie backgrounds are analyzed and retained for up to three years.

[...] Discord, to its credit, has now said it will not be proceeding with Persona for identity verification. And to be fair, Discord and similar internet companies are in an impossible position here—facing mounting regulatory pressure in multiple jurisdictions to verify ages while being handed a market of vendors who keep turning out to be security nightmares. But this is part of a pattern that should be deeply familiar by now.

[...] See the pattern? Discord keeps swapping vendors like someone frantically rotating buckets under a leaking roof, apparently hoping the next bucket won’t have a hole in it. But the problem was never the bucket. The problem is the hole in the roof — the never-ending stream of age-verification government mandates.

And this brings us to the bigger, more important point that almost nobody in the “protect the children” policy crowd seems willing to engage with honestly. Every single time you mandate age verification, you are mandating the creation of a centralized database of extraordinarily sensitive personal information. Government IDs. Biometric facial data. The kind of data that, once breached, cannot be “changed” like a password. You get one face. You get one government ID number. When those leak—and they will leak—the damage is permanent.

[...] We have been cataloging these breaches for years. In 2024, Australia greenlit an age verification pilot, and hours later a mandated verification database for bars was breached. That same year, another ID verification service was breached, exposing private info collected on behalf of Uber, TikTok, and more. Then came the Discord vendor breach last year. And now Persona.

Original Submission

Arthur T Knackerbracket writes:

Electronic eyes are watching from above, ready to catch dumpers of smashed up couches in the act:

The UK government is pulling together an elite squad of drone operators to crack down on the scourge of fly tippers and unauthorized dumpers across this ever less green and pleasant land.

The top drawer cadre of joystick jockeys will "track down illegal dumps from the air," the Environment Agency said, as part of a "major crackdown on waste crime."

Some of the drones will be upgraded with laser mapping technology, including LIDAR, the EA said, while the agency will also deploy "a new screening tool that enables EA officers to scan and cross-check lorry license applications against waste permit records." This means suspect operators will be flagged "before they have a chance to move waste illegally."

From the government's point of view, illegal fly tipping and dumping is now in the realms of organized crime. The government is increasing the Environment Agency's enforcement budget by half to more than £15.6 million. The motivation is often to avoid landfill charges, and criminals can make as much as £2,500 per lorry load of waste by billing customers for legal landfill, then diverting it to illegal dumps.

"With organized criminals becoming ever more sophisticated, we are adopting new technologies to find and, importantly, stop them," said Phil Davies, Head of the Joint Unit for Waste Crime.

[...] Earlier this week, Varun Datta, 36, [...] was told he must pay £1.1 million by way of a confiscation order, and given a four month prison sentence, suspended for 18 months. He had earlier pleaded guilty to knowingly causing 4,275 metric tons of controlled waste to be deposited at a network of 16 sites. Datta must also pay £100,000 in compensation and £200,000 in prosecution costs. It's not just the UK that is facing the problem of unscrupulous operators dumping waste. This week it emerged that a man in Sicily had trained his dog to dump plastic bags of waste by the roadside, evading CCTV cameras installed to catch flytippers in the process.

Original Submission

canopic jug writes:

Blogger Ben Werdmuller has discussed an article in Nature about the political impact of the algorithm(s) used by X (formerly known as Twitter). The gist is that the use of the algorithms against X's users tends to shift about 5% of them in a specific direction. That's more than enough to tip an election one way or another especially since the damage seems persistent and lasts even after exposure ceases.

Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects. Here we present results from a 2023 field experiment on Elon Musk's platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users' feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X's algorithm has persistent effects on users' current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship.

— The political effects of X's feed algorithm. Nature

It should be added that the effect has already been seen in multiple countries. For example, the elections in Turkey were affected with outright censorship, within X. And the impact from the CPP's Bytedance's Tiktok is likely even more severe, not to mention multiple experiments in manipulation in Meta's properties like Facebook.

Journal Reference: Gauthier, G., Hodler, R., Widmer, P. et al. The political effects of X's feed algorithm. Nature (2026). https://doi.org/10.1038/s41586-026-10098-2

Previously:
(2026) How Screwed is Generation Alpha, and the Generations Which Will Depend on Them?
(2025) European Union Orders X to Hand Over Algorithm Documents
(2024) Six Months Ago NPR Left Twitter. The Effects Have Been Negligible
(2023) Utah Sues Tiktok For Getting Children 'Addicted' To Its Algorithm
(2022) Leaked Documents Reveal Instagram Was Pushing Girls Towards Content That Harmed Mental Health
(2022) Musk Buying Twitter Is Not About Freedom of Speech
... and more

Original Submission

Arthur T Knackerbracket writes:

12-core chiplets coming to Zen 6?

Following Ryzen 9000, AMD is set to release its next-gen Ryzen 10000 series processors this year — assuming the company sticks to its existing nomenclature. These upcoming desktop CPUs from AMD are codenamed "Olympic Ridge" and will be based on the company's new Zen 6 microarchitecture. Today, a new leak from reliable tipster HXL says we can expect seven different configs as part of this lineup, across dual- and single-CCD SKUs.

According to the [information in a tweet], Ryzen 10000 will come in 6-core, 8-core, 10-core, and 12-core layouts as part of the single CCD designs. For the variants with two CCDs, you have 16-core (8+8), 20-core (10+10) and 24-core (12+12) made possible by simply doubling the chiplets. Either way, the lineup looks to be flexible enough to span from entry-level to power users and professionals.

This will mark the first time in Ryzen history that AMD ventures outside of its 8-core CCDs, by introducing new chiplets maxing out at 12 cores instead. Each of those CCDs is said to carry 48 MB of L3 cache, which shall make the flagship (non-X3D) SKU a 96 MB option. Throughout Zen 1 to Zen 5, the highest-end config for Ryzen chips has been 16 cores, but it should finally be upgraded to 24 cores with Ryzen 10000.

Now, comparing that to what Intel has in store with Nova Lake, that's an entirely different story. Current rumors suggest Nova Lake's flagship offering will be a monstrous 52-core SKU, with possibly 288 MB of bLLC (also across two tiles). Unlike the Red Team, Intel doesn't seem to be interested in segregating its extra-cache CPUs as a separate lineup entirely.

Apart from the core layouts of these chips, the underlying architecture is also of interest, since Zen 6 is said to usher in IPC improvements and higher clock speeds, while still working on the existing AM5 platform — the same cannot be said for Intel. It's a little too early to judge any of this, since Intel's Arrow Lake refresh isn't even out yet , and AMD hasn't made Ryzen 10000 official, beyond the Olympic Ridge codename. But hopefully, by the time we know all the details about AMD's next-gen CPUs, the price of RAM will also be a bit more affordable.

Original Submission

upstart writes:

NASA Officially Classifies Boeing Starliner Failure As A Maximum-Level Type A Mishap - Jalopnik:

NASA has officially categorized the 2024 failure of the Boeing Starliner spacecraft, which stranded astronauts Suni Williams and Butch Wilmore on the International Space Station (ISS) for nine months, as a Type A mishap. This is NASA-speak for the maximum level of failure a mission can reach, defined as an incident that causes over $2 million in damage, results in the loss of a vehicle or at least control over it, or any fatalities, per the BBC. This designation signifies that the space agency now views the mission as a disaster, even if the astronauts regained enough control at the last minute to prevent the worst-case scenario.

[...] Who's to blame here? Citing the full 312-page report, Isaacman found plenty to go around. Basically, NASA wanted a second option for launching people into space beyond SpaceX, and it wanted it so bad that it simply swept problems under the rug. "As development progressed, design compromises and inadequate hardware qualifications extended beyond NASA's complete understanding," said Isaacman in a very polite way. Multiple test flights failed in various ways, but before these technical faults were understood, NASA just greenlit the following flights anyway. Oops.

There were organizational problems as well: NASA more or less trusted Boeing, which once upon a time had a sterling reputation, to sort out its engineering problems. Isaacman stated that the agency didn't want to damage that reputation. Safe to say it's pretty well shot now, and this Type A classification isn't going to help. Meanwhile, Boeing was also not giving sufficient scrutiny to its own subcontractors. So nobody was overseeing anybody enough. Who could imagine this would go poorly?

But rest assured: it gets worse. CNN quotes one NASA insider as saying, "There was yelling at meetings," and another as saying, "There are some people that just don't like each other very much." Isaacman himself admitted that "disagreements over crew return options deteriorated into unprofessional conduct while the crew remained on orbit." Welcome to the world's premiere space exploration agency.

Despite it all, NASA doesn't want to give up on Boeing, and the Starliner project is moving ahead in a reduced capacity. But Isaacman made it clear that there would be much stricter oversight going forward, and no launches would be approved until technical fixes were verified and implemented. The desire to diversify off of SpaceX alone is still there.

Original Submission

upstart writes:

Hungarian startup Allonic secures $7.2M to transform robot manufacturing with 3D tissue braiding:

Budapest-based robotics startup Allonic raised $7.2 million in pre-seed funding, led by Visionaries Club, marking the largest pre-seed round in Hungary to date, as Vestbee was told. The funds will be allocated towards developing a new method for producing complex, dexterous robotic bodies.

• Founded in 2025 by Benedek Tasi, Dávid Pelyva, and David Holló, Allonic develops robotic manufacturing systems that automate the production of complex, human-like robot bodies.
• The company's platform, 3D Tissue Braiding, creates robotic structures by first producing a skeletal scaffolding, then weaving soft, load-bearing fibers around it, and integrating actuators and tendons directly into the structure during production.
• This process eliminates traditional multi-part assembly, embeds sensors and wiring into the body, and produces fully operational, compliant robotic mechanisms in a single automated workflow. The system allows complex 3D designs to be realized at scale, distributes mechanical stress uniformly, and enables rapid iteration from digital design to functional hardware.

See also:

• This New Way of Making Robots is Wild
• Dexterous Robotics with Biomimetic Tissues –and How to Make Them Simple Enough for Mass Production

Original Submission