Being attacked by your opponents is one thing. Being turned on by your allies is another. For that reason, the coverage in the left wing media would have been more painful for Jason Arday than in the right wing media.

The post For Jason Arday, Attacks in the ‘Left Wing Media’ Must Have Been Harder to Take Than Attacks in the ‘Right Wing Media’ appeared first on The Daily Sceptic.

Hundreds of US government drones have switched from border surveillance to a different surveillance mission this summer—looking for signs of screwworm infestations in wild animals and livestock herds.

The flesh-eating New World Screwworm is the parasitic larva that emerges from eggs laid by flies in the open wounds or body openings of warm-blooded animals and humans, with untreated cases potentially leading to severe injury or death. Since the first screwworm cases were detected in South Texas in June, the US Department of Agriculture and US Customs and Border Protection have been conducting “one of the most extensive animal-health surveillance operations in the country,” the USDA said on August 10 in social media posts on platforms like X and Facebook.

The effort involves at least 200 drones owned by the Department of Homeland Security, which includes the Customs and Border Protection (CBP) agency. But the actual number in use "varies depending on availability and need," a USDA spokesperson told Ars.

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Whether you’re looking for medical advice or tips on industrial agriculture, one thing is abundantly clear: never trust an AI chatbot without first getting a second opinion, preferably from a human who has actual expertise in the topic.

That’s the takeaway from an incident in the small city of Chuzhou, China, after a large langue model dispensed some advice that led to the untimely death of 25 acres worth of produce.

According to the Taiwanese publication CTWANT, a 67-year-old farmer surnamed Wu decided to start consulting an AI chatbot for advice nearly a year ago. He was reportedly skeptical at first, though the farmer began to let his guard down after some early successes with the AI’s farming tips.

Since that time, Wu has come to rely on his LLM for everything from fertilizing guidance to scheduling various tasks around the farm. After months of fruitful consultations, he decided to follow his AI chatbot’s new pesticide plan to the letter, letting loose on some 25 acres of precious sesame seedlings, all without ever double-checking with an expert or outside documentation.

The plan generated for him was basically a Long Island ice tea of agro-chemicals: a mix of “high-efficiency flupyridine” and “flufenazate” for pesky weeds, with plenty of “thiamethoxam” and “emamectin benzoate” for bugs and other pests, CT reported.

Not even a day after treatment, Wu says his juvenile sesame crop began to wither and die.

Per a video interview later translated by Tom’s Hardware, the farmer offered some hard-earned advice to any other growers looking to use his concoction: “If you spray it, the next day the seedlings won’t survive.”

“Both the grass and the seedlings will die, and the seedlings will die even faster,” Wu lamented.

It’s just the latest case of an LLM cooking up some slop that lands a professional in hot water. If nothing else, Wu’s in good company: he joins a host of other dupes across the legal, medical, financial, education, and media industries who’ve likewise fallen prey to an AI chatbot’s inaccurate output.

More on farms: The Diarrhea Lettuce Company Has Been Linked to Forced Labor

The post Farmer Horrified as AI Gives Bad Advice That Kills 25 Acres of Crops appeared first on Futurism.

Scientists in Arkansas have developed a machine-learning approach that can identify potentially disease-causing strains of a poultry bacterium by analyzing not only which genes are present, but also how those genes are arranged across the genome. The method focuses on the “genetic neighborhoods” surrounding genes, offering a new way to distinguish harmful strains of Enterococcus cecorum from closely related strains that do not cause disease.

E. cecorum is commonly found in poultry environments, and many of its strains are harmless. However, pathogenic strains can cause arthritis, bone infections and lameness, creating serious animal-welfare problems and economic losses for poultry producers. Because pathogenic and nonpathogenic strains can share many of the same genes, identifying the genetic features associated with disease has been challenging.

The research team, led by Aranyak Goswami of the Arkansas Agricultural Experiment Station’s Center for Agricultural Data Analytics, examined the organization of genes within genomic islands. These are segments of DNA that bacteria often acquire from other microorganisms through horizontal gene transfer. Genomic islands can carry genes involved in antibiotic resistance, bacterial survival, movement of DNA and virulence, making them important regions for understanding how pathogens emerge.

Rather than treating the bacterial genome as a simple list of genetic components, the researchers analyzed it as a structured map. They investigated which genes occurred near one another, the order in which they appeared and the way groups of neighboring genes formed recurring units known as genomic-island cassettes. This architecture provided information that could be missed when genes are examined individually.

“The machine-learning model recognizes patterns in gene order much like it recognizes patterns in language,” Goswami said. In the same way that a language model can learn that certain words frequently appear together, the computational system learned that particular combinations and arrangements of bacterial genes were associated with pathogenic strains. The approach therefore captures relationships among genes rather than relying only on the presence or absence of individual DNA sequences.

For the proof-of-concept study, the researchers analyzed the genomes of 145 E. cecorum strains isolated from poultry. The dataset included 95 nonpathogenic strains and 50 pathogenic strains capable of causing illness. The analysis found that disease-associated strains were more likely to contain genomic islands enriched in genes linked to antimicrobial resistance and the transfer of genetic material between bacteria.

Those findings do not mean that every bacterium carrying such genes will necessarily cause disease. Instead, the researchers describe the system as an exploratory classification and research tool. It identifies patterns that may help scientists investigate why some bacterial lineages become harmful, while also providing clues about how resistance and virulence traits move through bacterial populations.

Current monitoring methods for E. cecorum often depend on culturing the bacterium or screening for specific genes. Such techniques remain valuable, but they may overlook broader genomic relationships. The new pipeline could complement these approaches by evaluating the wider context in which genes occur. Additional testing with larger and more geographically diverse datasets will be necessary before the method can be used for routine flock surveillance or diagnostic decision-making.

The researchers believe the strategy could eventually be adapted to other bacterial species affecting animals, humans, wildlife and plants. Goswami’s team is beginning to examine Enterococcus faecalis, a close relative of E. cecorum and a frequent cause of hospital-acquired infections in humans. They also plan to apply the pipeline to Escherichia coli and other bacteria to study how nonpathogenic lineages acquire the genomic configurations associated with disease. The study, published in Frontiers in Microbiology, demonstrates how machine learning and comparative genomics can reveal hidden signals in bacterial DNA and may help researchers track the evolution of emerging pathogens.

Subject of Research: Animals

Article Title: Genomic-island cassette architecture provides interpretable signal for exploratory classification of poultry-associated Enterococcus cecorum lineages

News Publication Date: 7-Jul-2026

Web References: https://doi.org/10.3389/fmicb.2026.1882753

References: Frontiers in Microbiology, DOI: 10.3389/fmicb.2026.1882753

Image Credits: UA University Relations photo by Chieko Hara

Keywords: artificial intelligence, machine learning, deep learning, computational biology, bacterial pathogens, Enterococcus cecorum, genomic islands, genomic architecture, antibiotic resistance, poultry disease, pathogen surveillance, comparative genomics

What do you do when you return to your home town, with your dead mother in your car boot, to find the inhabitants have been turned into robots?

In the boot of her car, Pratelle carries the corpse of her mother and a giant sledgehammer. Her mission is simple: take the hammer to her home town. As you enter shops and homes through the door and leave them through the opposite wall, it becomes clear that the robots who either attack you or flee are all digital versions of your old neighbours.

Pratelle, with her close-cropped hair and dungarees, read to me as a queer woman, but interestingly, testers of the game often mistook her as a man. The team at developer Deconstructeam and longtime collaborator Selkie Harbour didn’t anticipate this confusion but found it fits the character perfectly, especially in this setting based on a small Spanish town like those in which the developers grew up.

Recently, a man I was rock climbing with told me about how he'd used AI to make a motivational poster for himself, which he'd hung on his bedroom wall: a bear, walking a slackline over a canyon, holding a sign that said, "Do cool shit." I made what I hoped was a polite noise. What reaction was this man looking for? He probably hoped someone, maybe me, would say it was cool or inspiring. It seemed I was not the first person he'd told about this poster. "You know, it's funny," he said to me. "No one ever says anything about it."

I have been thinking about this now for several days. There's a sort of turducken of things that I find off-puttin …

Read the full story at The Verge.

A sky-splitting boom rarely hurts anyone, and that one fact upends most of the arguments people have about it. The rattled windows, the pets losing their minds, the neighbor swearing something fell out of the sky — that part is real. What comes next, the confident theories about the source and who owes whom, is […]

The post What People Get Wrong About Injuries From Mystery Booms and Sky Trumpets appeared first on Strange Sounds.

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Game developer David Ashby and Aunty Donna’s Broden Kelly talk about their chaotic and silly sport game – involving meat pies with legs and Ford Falcons on the oval

Try explaining Australian rules football to anyone outside Australia and “it sounds like you’re making it up”, says David Ashby, the multi-hyphenate comedic mind behind deeply silly spoofs such as Italian Spider-Man and Danger 5. “Eighteen players a side, running around on a cricket oval with a rugby ball that has to be bounced every so often and gets kicked between posts – like, what the fuck is happening?”

Two years ago at a fantasy footy barbecue, Ashby had a brainwave: why not make a video game where Australia’s strange national sport becomes even stranger the more you play?

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Sunset Visitor studio’s founder tells us about their new, unnerving Captcha-filled world which prompts players to ask what it means to have a ‘meat body’

Sunset Visitor is a studio that has long engaged with the idea that video games are an effective vehicle for ruminating on societal problems. Its Peabody award-winning project, 1000XResist, incorporated the development team’s complex feelings about the Covid pandemic. “We’re pretty used to absorbing the world into the work,” says studio founder Remy Siu. The outfit’s latest game, Prove You’re Human, continues this legacy of reflective game making, providing players with an AI-centric psychological horror experience where they must reason with a learning model convinced that it’s alive. “We’ve tried to situate ourselves in [the question]: what is the effectual feeling of being a person inside of all of this?” Siu says.

The story orbits around Santana, a living, breathing person who’s chosen to split herself in two for work, with her digital clone sent to test a corporate product, a computing system called Mesa. “A large part of [why Santana chooses to do this] is to allow her meat body a life that she doesn’t have, while the digital version of her gets to labour,” says Siu. As Santana’s copy wades into increasingly murky ethical waters, she becomes entangled with Mesa, completing surreal 2D and 3D Captchas to investigate the cyber-world and halt the hallucinations.

Power cable linking UK and Ireland now passes near Bronze Age human burial remains instead of fictional grave on Welsh beach

Harry Potter fans have forced a new multimillion-pound power cable between the UK and Ireland to be relocated after complaining it would desecrate the “grave” of Dobby, a fictional elf.

The character was laid to rest on Freshwater West beach in Pembrokeshire, Wales, in the film Harry Potter and the Deathly Hallows. Fans of the wizard series come to leave stones reading “Here Lies Dobby” despite being asked not to by the land owner, the National Trust, because the beach is an ecologically sensitive site.

Fleet maintenance software is usually adopted for practical, straightforward reasons. Vehicles need servicing, downtime is expensive, and tracking repairs manually eventually becomes unsustainable. Those motivations are clear enough. What often surprises companies, however, is how quickly the impact spreads beyond the maintenance shop. Once the data begins flowing and processes align, the software influences scheduling, […]

The post What Are the Most Surprising Benefits of Fleet Maintenance Software? appeared first on Strange Sounds.