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Category: biological – Page 22

The kitchen can be a messy place in any home – some more than others, as anyone who’s lived in a student flat can attest to – but it turns out the humble microwave is home to far more microbes than you could possibly imagine.

And, not only that, but the bacteria these devices are hoarding is resistant to radiation and multiplying by the second.

A new study from a team from Darwin Bioprospecting Excellence SL in Paterna, Spain, published in journal Frontiers in Microbiology has found that hardy microbes able to adapt to extreme conditions and thrive in microwaves.

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In the search for less energy-hungry artificial intelligence, some scientists are exploring living computers.

By Jordan Kinard

Artificial intelligence systems, even those as sophisticated as ChatGPT, depend on the same silicon-based hardware that has been the bedrock of computing since the 1950s. But what if computers could be molded from living biological matter? Some researchers in academia and the commercial sector, wary of AI’s ballooning demands for data storage and energy, are focusing on a growing field known as biocomputing. This approach uses synthetic biology, such as miniature clusters of lab-grown cells called organoids, to create computer architecture. Biocomputing pioneers include Swiss company FinalSpark, which earlier this year debuted its “Neuroplatform”—a computer platform powered by human-brain organoids—that scientists can rent over the Internet for $500 a month.

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Researchers at Cold Spring Harbor Laboratory have traced the domestication of maize back to its origins 9,000 years ago, highlighting its crossbreeding with teosinte mexicana for cold adaptability.

The discovery of a genetic mechanism known as Teosinte Pollen Drive by Professor Rob Martienssen provides a critical link in understanding maize’s rapid adaptation and distribution across America, shedding light on evolutionary processes and potential agricultural applications.

Cold Spring Harbor Laboratory (CSHL) scientists have begun to unravel a mystery millennia in the making. Our story begins 9,000 years ago. It was then that maize was first domesticated in the Mexican lowlands. Some 5,000 years later, the crop crossed with a species from the Mexican highlands called teosinte mexicana. This resulted in cold adaptability. From here, corn spread across the continent, giving rise to the vegetable that is now such a big part of our diets. But how did it adapt so quickly? What biological mechanisms allowed the highland crop’s traits to take hold? Today, a potential answer emerges.

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CU Boulder scientists have found how ions move in tiny pores, potentially improving energy storage in devices like supercapacitors. Their research updates Kirchhoff’s law, with significant implications for energy storage in vehicles and power grids.

Imagine if your dead laptop or phone could be charged in a minute, or if an electric car could be fully powered in just 10 minutes. While this isn’t possible yet, new research by a team of scientists at CU Boulder could potentially make these advances a reality.

Published in the Proceedings of the National Academy of Sciences, researchers in Ankur Gupta’s lab discovered how tiny charged particles, called ions, move within a complex network of minuscule pores. The breakthrough could lead to the development of more efficient energy storage devices, such as supercapacitors, said Gupta, an assistant professor of chemical and biological engineering.

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Artificial neural networks—algorithms inspired by biological brains—are at the center of modern artificial intelligence, behind both chatbots and image generators. But with their many neurons, they can be black boxes, their inner workings uninterpretable to users.

Researchers have now created a fundamentally new way to make neural networks that in some ways surpasses traditional systems. These new networks are more interpretable and also more accurate, proponents say, even when they’re smaller. Their developers say the way they learn to represent physics data concisely could help scientists uncover new laws of nature.

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Could we store samples of Earth’s endangered biodiversity on the Moon for long-term preservation? This is what a recent study published in BioScience hopes to address as a team of researchers led by the Smithsonian Institution proposes how the Moon’s permanently shadowed regions (PSRs) located at the lunar north and south poles could be ideal locations for establishing a lunar biorepository where endangered species can be cryopreserved. This study holds the potential to safeguard Earth’s biodiversity from extinction while improving future space exploration and possible terraforming of other worlds.

“Initially, a lunar biorepository would target the most at-risk species on Earth today, but our ultimate goal would be to cryopreserve most species on Earth,” said Dr. Mary Hagedorn, who is a research cryobiologist at the Smithsonian National Zoo and Conservation Biology Institute and lead author of the study. “We hope that by sharing our vision, our group can find additional partners to expand the conversation, discuss threats and opportunities and conduct the necessary research and testing to make this biorepository a reality.”

The reason lunar PSRs are of interest for this proposal is due to several craters being completely devoid of sunlight from the Moon’s small axial tilt (6.7 degrees versus Earth’s 23.5 degrees). The team postulates this presents ample opportunity for storing several groups, including pollinators, threatened and endangered animals, culturally important species, and primary producers, just to name a few.

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Neuromorphic computers are devices that try to achieve reasoning capability by emulating a human brain. They are a different type of computer architecture that copies the physical characteristics and design principles of biological nervous systems. Although neuromorphic computations can be emulated, it’s very inefficient for classical computers to simulate. Typically new hardware is required.

The first neuromorphic computer at the scale of a full human brain is about to come online. It’s called DeepSouth, and will be finished in April 2024 at Western Sydney University. This computer should enable new research into how our brain actually functions, potentially leading to breakthroughs in how AI is created.

One important characteristic of this neuromorphic computer is that it’s constructed out of commodity hardware. Specifically, it’s built on top of FPGAs. This means it will be much easier for other organizations to copy the design. It also means that once AI starts self-improving, it can probably build new iterations of hardware quite easily. Instead of having to build factories from the ground up, leveraging existing digital technology allows all the existing infrastructure to be reused. This might have implications for how quickly we develop AGI, and how quickly superintelligence arises.

#ai #neuromorphic #computing.

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