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Newly Discovered Fossil Tracks May Rewrite Early History of Reptiles

Newly Discovered Fossil Tracks May Rewrite Early History of Reptiles

Yahoo15-05-2025

Fossil claw prints found in Australia were probably made by the earliest known members of the group that includes reptiles, birds and mammals, according to a study published in Nature today. The findings suggest that this group — the amniotes — originated at least 35 million years earlier than previously thought.
Early amniotes evolved to lay eggs on land, because they were encased in an amniotic membrane that stopped them drying out. Before this study, the earliest known amniote fossils had been found in Nova Scotia, Canada, and were dated to the mid-Carboniferous period, about 319 million years ago. The latest findings suggest that amniotes also existed in the early Carboniferous period, around 355 million years ago.
'This discovery is exciting, and if the tracks have been interpreted the right way, the findings have important implications for our understanding of tetrapod evolution,' says Steven Salisbury, a palaeontologist at the University of Queensland in Brisbane, Australia.
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The claw tracks were found in a sandstone block on the bank of the Broken River at Barjarg in the state of Victoria, by two co-authors of the paper who are not professional scientists. This area of the river is known as Berrepit to the Indigenous Taungurung people who own the land.
The sandstone block is part of a larger structure that had already been dated to the early Carboniferous on the basis of radiometric and tectonic evidence. Fossilized tracks of aquatic invertebrates and fish found in the same layer were also dated to this time period.
The three sets of tracks in the study have clear footprints with indentations from claws, a feature of reptiles but not of amphibians. 'Having these hooked claws on the trackways indicates they're definitely a reptile-like animal,' says John Long, a palaeontologist at Flinders University in Adelaide, Australia.
There are no marks of dragging bellies or tails, and the authors suggest that the amniotes that left the tracks were able to keep their bodies and tails off the ground while they walked on land. But Salisbury questions that interpretation, because it would mean the animals had developed sophisticated structures for complex locomotion, which would be surprising given how early they are. 'It seems more likely that the tracks were made by an animal that was 'punting' in shallow water, rather than walking on land,' he says.
Until now, evidence suggested that the last common ancestor of modern amphibians and amniotes lived around 352 million years ago. But if the ancestors of reptiles existed during the early Carboniferous, their split from amphibians must have occurred even earlier, says Long. Dating by the team suggests that the groups diverged in the Devonian period, about 380 million years ago.
To estimate the probable time of divergence, Long and his colleagues used several dating methods. One included geological evidence from radioactive decay in volcanic rock layers above and below the fossil tracks. They also used molecular phylogenetics, which compares similarities and differences in the DNA of living species to estimate their evolutionary relationships and how recently their last common ancestor lived.
The discovery could also shift the origin of amniotes to the Gondwana landmass. This formed the southern portion of the Pangaea supercontinent and gave rise to multiple current landmasses, including Africa and Australia. Previously, the earliest known amniotes were found in North America, leading palaeontologists to think that the group originated in the Northern Hemisphere. But more evidence from Australian fossils is needed before definitively shifting their origin site, says Long. 'Australia is a vast area with fewer palaeontologists on the ground,' Long says. 'We've got a lot more unexplored fossil sites where new things like this keep turning up.'
This article is reproduced with permission and was first published on May 14, 2025.

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Inside the Secret Meeting Where Mathematicians Struggled to Outsmart AI
Inside the Secret Meeting Where Mathematicians Struggled to Outsmart AI

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Inside the Secret Meeting Where Mathematicians Struggled to Outsmart AI

On a weekend in mid-May, a clandestine mathematical conclave convened. Thirty of the world's most renowned mathematicians traveled to Berkeley, Calif., with some coming from as far away as the U.K. The group's members faced off in a showdown with a 'reasoning' chatbot that was tasked with solving problems they had devised to test its mathematical mettle. After throwing professor-level questions at the bot for two days, the researchers were stunned to discover it was capable of answering some of the world's hardest solvable problems. 'I have colleagues who literally said these models are approaching mathematical genius,' says Ken Ono, a mathematician at the University of Virginia and a leader and judge at the meeting. The chatbot in question is powered by o4-mini, a so-called reasoning large language model (LLM). It was trained by OpenAI to be capable of making highly intricate deductions. Google's equivalent, Gemini 2.5 Flash, has similar abilities. Like the LLMs that powered earlier versions of ChatGPT, o4-mini learns to predict the next word in a sequence. Compared with those earlier LLMs, however, o4-mini and its equivalents are lighter-weight, more nimble models that train on specialized datasets with stronger reinforcement from humans. The approach leads to a chatbot capable of diving much deeper into complex problems in math than traditional LLMs. To track the progress of o4-mini, OpenAI previously tasked Epoch AI, a nonprofit that benchmarks LLMs, to come up with 300 math questions whose solutions had not yet been published. Even traditional LLMs can correctly answer many complicated math questions. Yet when Epoch AI asked several such models these questions, which were dissimilar to those they had been trained on, the most successful were able to solve less than 2 percent, showing these LLMs lacked the ability to reason. But o4-mini would prove to be very different. [Sign up for Today in Science, a free daily newsletter] Epoch AI hired Elliot Glazer, who had recently finished his math Ph.D., to join the new collaboration for the benchmark, dubbed FrontierMath, in September 2024. The project collected novel questions over varying tiers of difficulty, with the first three tiers covering undergraduate-, graduate- and research-level challenges. By February 2025, Glazer found that o4-mini could solve around 20 percent of the questions. He then moved on to a fourth tier: 100 questions that would be challenging even for an academic mathematician. Only a small group of people in the world would be capable of developing such questions, let alone answering them. The mathematicians who participated had to sign a nondisclosure agreement requiring them to communicate solely via the messaging app Signal. Other forms of contact, such as traditional e-mail, could potentially be scanned by an LLM and inadvertently train it, thereby contaminating the dataset. The group made slow, steady progress in finding questions. But Glazer wanted to speed things up, so Epoch AI hosted the in-person meeting on Saturday, May 17, and Sunday, May 18. There, the participants would finalize the final batch of challenge questions. Ono split the 30 attendees into groups of six. For two days, the academics competed against themselves to devise problems that they could solve but would trip up the AI reasoning bot. Each problem the o4-mini couldn't solve would garner the mathematician who came up with it a $7,500 reward. By the end of that Saturday night, Ono was frustrated with the bot, whose unexpected mathematical prowess was foiling the group's progress. 'I came up with a problem which experts in my field would recognize as an open question in number theory—a good Ph.D.-level problem,' he says. He asked o4-mini to solve the question. Over the next 10 minutes, Ono watched in stunned silence as the bot unfurled a solution in real time, showing its reasoning process along the way. The bot spent the first two minutes finding and mastering the related literature in the field. Then it wrote on the screen that it wanted to try solving a simpler 'toy' version of the question first in order to learn. A few minutes later, it wrote that it was finally prepared to solve the more difficult problem. Five minutes after that, o4-mini presented a correct but sassy solution. 'It was starting to get really cheeky,' says Ono, who is also a freelance mathematical consultant for Epoch AI. 'And at the end, it says, 'No citation necessary because the mystery number was computed by me!'' Defeated, Ono jumped onto Signal early that Sunday morning and alerted the rest of the participants. 'I was not prepared to be contending with an LLM like this,' he says, 'I've never seen that kind of reasoning before in models. That's what a scientist does. That's frightening.' Although the group did eventually succeed in finding 10 questions that stymied the bot, the researchers were astonished by how far AI had progressed in the span of one year. Ono likened it to working with a 'strong collaborator.' Yang Hui He, a mathematician at the London Institute for Mathematical Sciences and an early pioneer of using AI in math, says, 'This is what a very, very good graduate student would be doing—in fact, more.' The bot was also much faster than a professional mathematician, taking mere minutes to do what it would take such a human expert weeks or months to complete. While sparring with o4-mini was thrilling, its progress was also alarming. Ono and He express concern that the o4-mini's results might be trusted too much. 'There's proof by induction, proof by contradiction, and then proof by intimidation,' He says. 'If you say something with enough authority, people just get scared. I think o4-mini has mastered proof by intimidation; it says everything with so much confidence.' By the end of the meeting, the group started to consider what the future might look like for mathematicians. Discussions turned to the inevitable 'tier five'—questions that even the best mathematicians couldn't solve. If AI reaches that level, the role of mathematicians would undergo a sharp change. For instance, mathematicians may shift to simply posing questions and interacting with reasoning-bots to help them discover new mathematical truths, much the same as a professor does with graduate students. As such, Ono predicts that nurturing creativity in higher education will be a key in keeping mathematics going for future generations. 'I've been telling my colleagues that it's a grave mistake to say that generalized artificial intelligence will never come, [that] it's just a computer,' Ono says. 'I don't want to add to the hysteria, but in many ways these large language models are already outperforming most of our best graduate students in the world.'

Resilience, a Private Japanese Spacecraft, Crash-Landed on the Moon
Resilience, a Private Japanese Spacecraft, Crash-Landed on the Moon

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Resilience, a Private Japanese Spacecraft, Crash-Landed on the Moon

A Japanese spacecraft has probably crashed on the Moon, the second failed landing attempt for Tokyo-based private firm ispace. The HAKUTO-R Mission 2 (M2) lander — also called Resilience — began its landing sequence from a 100-kilometre-altitude orbit at 3.13am local time on 5 June. The craft was due to land near the centre of Mare Frigoris (Sea of Cold) at 4.17am. The ispace team said at a press conference that it lost contact with M2 when the craft was 192 metres above the Moon's surface and descending faster than expected. An attempt to reboot M2 was also unsuccessful. [Sign up for Today in Science, a free daily newsletter] M2 didn't receive measurements of the distance between itself and the lunar surface in time to slow down and reach its correct landing speed, the team said. 'It eventually slowed down, but not softly enough,' says Clive Neal, who studies the Moon at the University of Notre Dame in Indianapolis, US. He speculates that the failure was probably caused by a systems issue that wasn't identified and addressed during the M1 landing attempt. 'It's something that I believe will definitely be fixable, because getting that close means there's a few tweaks that are going to be needed for the next one,' he adds. If M2 had successfully landed on the lunar surface, the mission would have been the second time a commercial company had achieved the feat and a first for a non-US company. ispace's Mission 1 (M1) probably crashed during a landing attempt in April 2023. Lunar landings are challenging. When M1 crashed, Ryo Ujiie, ispace's chief technology officer said the telemetry — which collects data on the craft's altitude and speed — estimated that M1 was on the surface when it wasn't, causing the lander to free fall. Speaking to Nature last week, Ujiie said the company had addressed the telemetry issue with M2 and modified its software. 'We also carefully selected how to approach the landing site,' he added. Had M2 landed successfully, the craft would have supplied electricity for its cargo, including water electrolyzing equipment and a module for food production experiments — developed by Japan-based Takasago Thermal Engineering and biotechnology firm Euglena. A deep space radiation probe made by Taiwan's National Central University, and the 54-centimetre Tenacious rover were also be on board. The rover, created by ispace's European subsidiary in Luxemburg, was going to be released from the lander to collect imagery, location data and lunar sand known as regolith. Tenacious also carries a small red house made by Swedish artist Mikael Genberg. The craft launched on 15 January from Cape Canaveral, Florida, onboard a SpaceX Falcon 9 rocket. The rocket was also carrying the Blue Ghost Moon lander — developed by Firefly Aerospace, an aerospace firm based in Texas — which landed on the Moon on 2 March. M2 took a longer path to the moon than Blue Ghost, performing a lunar flyby on 15 February and spending two months in a low-energy transfer orbit before entering lunar orbit on 7 May. Ujiie says the path was slower because it was a low-energy trajectory, meaning that less fuel was used to move between Earth and lunar orbit. Richard de Grijs, an astronomer at Macquarie University in Sydney, Australia, says there will likely be more private companies trying to land their own crafts on the Moon. 'It seems that the big government players like NASA are quite keen to partner with commercial companies,' he says, because they can develop and launch crafts more cheaply than government bodies. He also expects that more missions will be launched in clusters, like the launch of M2 and Blue Ghost. This article is reproduced with permission and was first published on June 6, 2025.

In a world without people, how fast would NYC fall apart? Here's the timeline.
In a world without people, how fast would NYC fall apart? Here's the timeline.

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In a world without people, how fast would NYC fall apart? Here's the timeline.

Imagine the ceaseless cacophony of New York City suddenly stopped. No sirens wailed. No cars zoomed. No subways rumbled beneath sidewalks. All eight million New Yorkers disappeared overnight. Now, imagine what would happen next. If no one's around to sweep the sidewalks, weed Central Park, or turn the power grid on, nature would move in—and quick. Dandelions would spring up in asphalt cracks. Raccoons would move into abandoned apartments. Sidewalk trees would outgrow their planters. But just how swiftly would the city disappear beneath a curtain of green? We talked to architects and urban ecologists to map out a potential timeline. With no one to maintain the power grid, the Big Apple would go dark within a few days. The Milky Way would illuminate Midtown as light pollution disappears overnight. Without air conditioning and heat, 'you start getting weird temperatures inside the building. Mold starts to form on the walls,' says architect Jana Horvat of the University of Zagreb, who studies building decay. Some green energy projects in the city might stay lit for longer, such as the solar and wind-powered Ricoh Americas billboard in Times Square. Eventually, though, even the Ricoh billboard would go dark; not because the billboard would lose power, but because there would be no one to replace its LED lightbulbs. Without power, the pump rooms that clear out 13 million gallons of water daily from the subway would be useless, and the train tunnels would begin to flood. 'Probably this water would result in [the subway] being, you know, occupied by new species,' says Horvat. 'Some plants would start growing, some animals' would move in. Likely, species that already thrive in the subway—rats, cockroaches, pigeons, opossums—would be the first ones to take advantage of the human-free passages. Within the first month, the manicured lawns of Central and Prospect Park would grow wild and unkept. 'When you stop mowing a lawn, you get a meadow,' says botanist Peter Del Tredici, a senior research scientist emeritus at the Arnold Arboretum of Harvard University, who wrote a book on urban plant life. Within a month, dandelions, ragweed, and yellow nutsedge would start popping up in the now knee-high grasses of New York's iconic parks. 'First, it's herbaceous plants, but then, you know, you get trees and shrubs and vines,' says Tredici. In a year without people, many of New York's buildings would start to deteriorate. 'The glass facades would be the first to go,' says Horvat. The single-pane glass on brownstones and family homes would be the most vulnerable, but in a decade, even the heat-strengthened glass on skyscrapers would start to wear down and crack. And once windows break, water gets in. 'Then you'll have plants start growing in there,' says Tredici. Apartments would transform into humid hothouses, the perfect habitat for mosquitoes, water snakes, fungus, and rushes. 'It's like a wetland on the second floor.' Without maintenance, the asphalt streets and parking lots in New York would quickly degrade. Freeze-thaw cycles would create cracks. 'Water settles in that crack, and then that's all the plants need,' says Tredici. First, mosses would grow. Within a decade, young trees may even sprout. The London planetree, the most common street tree in New York, is particularly known for its resilience and fast growth rate, and any of its offspring could quickly find a toehold in a deteriorating asphalt parking lot. Within a decade, the Statue of Liberty would also start to deteriorate. The statue's copper plating would start to split, allowing sea spray to break down its interior steel skeleton. Steel 'is a very durable material, but it is very prone to corroding if it comes in contact with damp conditions,' says Horvat: That's bad news for New York, a city made from steel. In the decades since humans abandoned New York, a 'novel ecosystem' would emerge, says Tredici. 'It's not going to look like anything that's ever existed anywhere in the world.' Tredici points to Detroit as a case study. Today, crabapple trees—tough ornamentals native to the Central Asian mountains—blanket Detroit. 'They actually will spread all over,' says Tredici, and after 50 years without humans, Central and Riverside Park's crabapple trees would grow among a young forest full of London planetrees, honeylocusts, pin oaks, and Norway maples (the last three being common New York street trees). Nightshade vines and poison ivy would creep up buildings, and mosses and resilient weeds would cover the higher reaches of exposed windy skyscrapers. Among the greenery, more and more animals would call Manhattan home. Deer, rabbits, groundhogs, and wild turkeys would move in. Larger predators—coyotes, bobcats, black bears, and copperhead snakes—would follow. Peregrine falcons, bald eagles, red-tailed hawks, and great horned owls would nest in hollowed-out buildings, while feral cats prowl the abandoned upper floors of apartment buildings, feasting on mice and birds. Despite their futuristic look, the city's newest spires, such as 10 Hudson Yards and 111 West 57th Street, would be the first to fall. These buildings rely on slender, reinforced steel skeletons encased in reinforced concrete. But when the power shuts off and water seeps in through these buildings' glass curtain walls, these high-rises would rot from the inside out. The Empire State Building and Chrysler Building would likely outlast their younger rivals. Built to support much more weight than necessary (a safety precaution in the early days of skyscrapers), these giants' steel frames are bolstered by thick masonry and interior walls. Ten Hudson Yards might last a century. The Empire State Building might last 50 years longer, but eventually even these historic titans would collapse. After a century, New York City would 'become a forest,' says Tredici. A canopy of mature trees over a 100-feet-tall would replace the city's skyscrapers. Soil would regenerate. Concrete, one of the world's 'strongest' construction materials, says Horvat, would dissolve. New York's carefully manicured river parks, such as the Hudson River and East River Park, would transform into wetlands teeming with eels, egrets, turtles, beavers, and muskrats. But even as skyscrapers fell and forests grew, parts of New York would 'survive for centuries in this ruinous state,' says Horvat. Cracked marble lions would stalk the forest floor. Soil and underbrush would obscure once-gleaming granite fountains. Rusted steel beams would jut out from dense root systems. Even without humans, pieces of New York would endure—a fragile legacy for the future to either uncover or forget. This story is part of Popular Science's Ask Us Anything series, where we answer your most outlandish, mind-burning questions, from the ordinary to the off-the-wall. Have something you've always wanted to know? Ask us.

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