“Seismologist Deborah Kilb was wading through California earthquake records from the past four decades when she noticed something odd,” reports CNN, “a series of deep earthquakes that had occurred under the Sierra Nevada at a depth where Earth’s crust would typically be too hot and high pressure for seismic activity…”

Kilb flagged the data to Vera Schulte-Pelkum, a research scientist at the Cooperative Institute for Research in Environmental Sciences and an associate research professor of geological sciences at the University of Colorado Boulder… Using the newfound data, the researchers imaged the Sierra Nevada through a technique known as receiver function analysis, which uses seismic waves to map Earth’s internal structure. The scientists found that in the central region of the mountain range, Earth’s crust is currently peeling away, a process scientifically known as lithospheric foundering. Kilb and Schulte-Pelkum reported the findings in December in the journal Geophysical Research Letters.

The hypothesis lined up with previous speculation that the area had undergone lithospheric foundering, which happens when Earth’s outermost layer sinks into the lower layer of the mantle. Now, the study authors believe that the process is ongoing and is currently progressing to the north of the mountain range, according to the study… What’s happening under the Sierra Nevada could offer rare insight into how the continents formed, Schulte-Pelkum said. The finding could also help scientists identify more areas where this process is happening as well as provide a better understanding of earthquakes and how our planet operates, she added…

Evidence for this process has been hard to come by. It is not visible from above ground, and it’s an extremely slow process. Scientists theorize that the south Sierra finished the process of lithospheric foundering about 4 million to 3 million years ago, according to the study. It appears that these natural events happen occasionally around the world, Schulte-Pelkum said. “Geologically speaking, this is a pretty quick process with long periods of stability in between. … This (lithosphere foundering) probably started happening a long time ago when we started building continents, and (the continents) have gotten bigger over time. So it’s just sort of this punctuated, localized thing,” she added…

Further study within this area could also help scientists better understand how the Earth evolves on long timescales. If the lithospheric foundering continues underneath the mountain range, one can speculate that the land will continue to stretch vertically, changing the way the landscape looks now [said Mitchell McMillan, a research geologist and postdoctoral fellow at Georgia Tech, who was not involved with the study]. But that could take anywhere from several hundred thousand to a few million years, he added.

Read more of this story at Slashdot.

CNN looks at “one field that’s really benefitting” from the use of AI: “the discovery of new medicines”.

The founder/CEO of London-based LabGenius says their automated robotic system can assemble “thousands of different DNA constructs, each of which encodes a completely unique therapeutic molecule that we’ll then test in the lab. This is something that historically would’ve had to have been done by hand.” In short, CNN says, their system lets them “design and conduct experiments, and learn from them in a circular process that creates molecular antibodies at a rate far faster than a human researcher.”
While many cancer treatments have debilitating side effects, CNN notes that LabGenius “reengineers therapeutic molecules so they can selectively target just the diseased cells.”
But more importantly, their founder says they’ve now discovered “completely novel molecules with over 400x improvement in [cell] killing selectivity.”

A senior lecturer at Imperial College London tells CNN that LabGenius seems to have created an efficient process with seamless connections, identifying a series of antibodies that look like they can target cancer cells very selectively “that’s as good as any results I’ve ever seen for this.” (Although the final proof will be what happens when they test them on patients..) “And that’s the next step for Labgenius,” says CNN. “They aim to have their first therapeutics entering clinics in 2027.”

Finally, CNN asks, if it succeeds is their potential beyond cancer treatment? “If you take one step further,” says the company’s CEO/founder, “you could think about knocking out senescent cells or aging cells as a way to treat the underlying cause of aging.”

Read more of this story at Slashdot.

Beijing held what’s being called the world’s first half-marathon for robots, allowing bipedal bots to compete alongside human runners, and as one might expect, ridiculousness ensued. The robots, which had human operators running with them, for the most part struggled to make it through the course at all, let alone complete the full 13 miles within the four-hour cutoff time. “One fell at the starting line,” Bloomberg reports. “Another’s head fell off and rolled on the ground. And one collapsed and broke into pieces.” They may not be gold medalists just yet, but the videos sure are entertaining.

According to Bloomberg, 21 robots participated in the race, but the winner — X Humanoid’s five-foot-ten Tiangong Ultra — was one of only four to make it all the way to the end in the allotted time. And at two hours and 40 minutes, its finishing time was more than double that of the winning human runners.

The teams were allowed to do battery swaps (Tiangong Ultra reportedly finished on its third battery) and even switch out their robots mid-race for substitutes, though doing that came with time penalties. Along with Tiangong Ultra, which ran at around five miles per hour, the robot runners included Noetix Robotics’ N2, a Gundam-inspired robot, a “female-looking” bot called Huan Huan, and the 30-inch-tall Little Giant robot made by local college students, Bloomberg reports. Many of them were wearing human running shoes.

This article originally appeared on Engadget at https://www.engadget.com/ai/a-bunch-of-robots-ran-a-half-marathon-alongside-humans-and-it-was-incredibly-goofy-215134524.html?src=rss

Billions of years ago Mars “had a warm, habitable climate with liquid water in lakes and flowing rivers,” writes Ars Technica.

But “In order for Mars to be warm enough to host liquid water, there must have been a lot of carbon dioxide in the atmosphere,” says Benjamin Tutolo, a researcher at the University of Calgary. “The question we’ve been asking for at least 30 years was where the record of all this carbon is.”

Tutolo led a new study of rock samples collected by the Curiosity rover that might have answered this question…

Curiosity rover was called Mars Science Laboratory for a reason. It went to the red planet fitted with a suite of instruments, some of which even the newer Perseverance was lacking. These enabled it to analyze the collected Martian rocks on the spot and beam the results back to Earth. “To get the most bang for the buck, NASA decided to send it to the place on Mars called the Gale Crater, because it was the tallest stack of sediments on the planet,” Tutolo says. The central peak of Gale Crater was about 5 kilometers tall, created by the ancient meteorite impact… The idea then was to climb up Mount Sharp and collect samples from later and later geological periods at increasing elevations, tracing the history of habitability and the great drying up of Mars.

On the way, the carbon missed by the satellites was finally found…

It turned out the samples contained roughly between 5 and 10 percent of siderite… The siderite found in the samples was also pure, which Tutolo thinks indicates it has formed through an evaporation process akin to what we see in evaporated lakes on Earth. This, in turn, was the first evidence we’ve found of the ancient Martian carbon cycle. “Now we have evidence that confirms the models,” Tutolo claims. The carbon from the atmosphere was being sequestered in the rocks on Mars just as it is on Earth. The problem was, unlike on Earth, it couldn’t get out of these rocks… A large portion of carbon that got trapped in Martian rocks stayed in those rocks forever, thinning out the atmosphere.

“While it’s likely the red planet had its own carbon cycle, it was an imperfect one that eventually turned it into the lifeless desert it is today,” the article points out.

But the study still doesn’t entirely explain what warmed the atmosphere of Mars — or why Martian habitability “was seemingly intermittent and fluctuating”.

Read more of this story at Slashdot.

For combining machine learning with astronomy, high school senior Matteo Paz won $250,000 in the Regeneron Science Talent Search, reports Smithsonian magazine:

The young scientist’s tool processed 200 billion data entries from NASA’s now-retired Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) telescope. His model revealed 1.5 million previously unknown potential celestial bodies…. [H]e worked on an A.I. model that sorted through the raw data in search of tiny changes in infrared radiation, which could indicate the presence of variable objects.
Working with a mentor at the Planet Finder Academy at Caltech, Paz eventually flagged 1.5 million potential new objects, accoridng to the article, including supernovas and black holes.
And that mentor says other Caltech researchers are using Paz’s catalog of potential variable objects to study binary star systems.

Thanks to long-time Slashdot reader schwit1 for sharing the article.

Read more of this story at Slashdot.

Matt Asay answered questions from Slashdot readers in 2010 (as the then-COO of Canonical). He currently runs developer relations at MongoDB (after holding similar positions at AWS and Adobe).

This week he contributed an opinion to piece to InfoWorld arguing that DeepSeek “may have originated in China, but it stopped being Chinese the minute it was released on Hugging Face with an accompanying paper detailing its development.”

Soon after, a range of developers, including the Beijing Academy of Artificial Intelligence (BAAI), scrambled to replicate DeepSeek’s success but this time as open source software. BAAI, for its part, launched OpenSeek, an ambitious effort to take DeepSeek’s open-weight models and create a project that surpasses DeepSeek while uniting “the global open source communities to drive collaborative innovation in algorithms, data, and systems.”

If that sounds cool to you, it didn’t to the U.S. government, which promptly put BAAI on its “baddie” list. Someone needs to remind U.S. (and global) policymakers that no single country, company, or government can contain community-driven open source… DeepSeek didn’t just have a moment. It’s now very much a movement, one that will frustrate all efforts to contain it. DeepSeek, and the open source AI ecosystem surrounding it, has rapidly evolved from a brief snapshot of technological brilliance into something much bigger — and much harder to stop. Tens of thousands of developers, from seasoned researchers to passionate hobbyists, are now working on enhancing, tuning, and extending these open source models in ways no centralized entity could manage alone.

For example, it’s perhaps not surprising that Hugging Face is actively attempting to reverse engineer and publicly disseminate DeepSeek’s R1 model. Hugging Face, while important, is just one company, just one platform. But Hugging Face has attracted hundreds of thousands of developers who actively contribute to, adapt, and build on open source models, driving AI innovation at a speed and scale unmatched even by the most agile corporate labs.

Hugging Face by itself could be stopped. But the communities it enables and accelerates cannot. Through the influence of Hugging Face and many others, variants of DeepSeek models are already finding their way into a wide range of applications. Companies like Perplexity are embedding these powerful open source models into consumer-facing services, proving their real-world utility. This democratization of technology ensures that cutting-edge AI capabilities are no longer locked behind the walls of large corporations or elite government labs but are instead openly accessible, adaptable, and improvable by a global community.
“It’s Linux all over again…” Asay writes at one point. “What started as the passion project of a lone developer quickly blossomed into an essential, foundational technology embraced by enterprises worldwide,” winning out “precisely because it captivated developers who embraced its promise and contributed toward its potential.”

We are witnessing a similar phenomenon with DeepSeek and the broader open source AI ecosystem, but this time it’s happening much, much faster…
Organizations that cling to proprietary approaches (looking at you, OpenAI!) or attempt to exert control through restrictive policies (you again, OpenAI!) are not just swimming upstream — they’re attempting to dam an ocean. (Yes, OpenAI has now started to talk up open source, but it’s a long way from releasing a DeepSeek/OpenSeek equivalent on GitHub.)

Read more of this story at Slashdot.

Like giant bones planted in the earth, clusters of tree trunks, stripped clean of bark, are appearing along the Chesapeake Bay on the United States’ mid-Atlantic coast. They are ghost forests: the haunting remains of what were once stands of cedar and pine. Since the late 19th century, an ever-widening swath of these trees have died along the shore. And they won’t be growing back.

These arboreal graveyards are showing up in places where the land slopes gently into the ocean and where salty water increasingly encroaches. Along the United States’ East Coast, in pockets of the West Coast, and elsewhere, saltier soils have killed hundreds of thousands of acres of trees, leaving behind woody skeletons typically surrounded by marsh.

What happens next? That depends. As these dead forests transition, some will become marshes that maintain vital ecosystem services, such as buffering against storms and storing carbon. Others may become home to invasive plants or support no plant life at all—and the ecosystem services will be lost. Researchers are working to understand how this growing shift toward marshes and ghost forests will, on balance, affect coastal ecosystems.

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