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Categories: Mathematics: Modeling, Paleontology: Early Mammals and Birds

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A new study places the origin of the Imazighen in the Epipaleolithic, more than twenty thousand years ago. The research concludes that the genetic origin of the current Arab population of north Africa is far more recent than previously believed, placing it in the seventh century AD. The team has designed an innovative demographic model that uses artificial intelligence to analyze the complete genomes of the two populations.

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Clean energy investments offer potential stability and growth, especially during volatile market conditions. A recent study explored the relationship between clean energy markets and global stock markets. Significant spillovers were observed from major indices like the SP500 to markets such as Japan's Nikkei225 and Global Clean Energy Index. These interactions suggest opportunities for optimizing investment portfolios and leveraging clean energy assets as hedging tools in volatile market environments.

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Researchers have found that training successive generations of generative artificial intelligence models on synthetic data gives rise to self-consuming feedback loops.

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Researchers argue that, in some situations where machine-learning models are used to allocate scarce resources or opportunities, randomizing decisions in a structured way may lead to fairer outcomes.

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Birds tend to be more colorful in the tropics, and scientists wanted to find out how they got there: if colorful feathers evolved in the tropics, or if tropical birds have brightly-colored ancestors that came to the region from somwhere else. Scientists built a database of 9,409 birds to explore the spread of color across the globe. They found that iridescent, colorful feathers originated 415 times across the bird tree of life, and in most cases, arose outside of the tropics -- and that the ancestor of all modern birds likely had iridescent feathers, too.

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Tackling a long-time mystery, scientists have found that the turbulent movements of air in clouds play a key role in the growth of water droplets and the initiation of rain. The research can improve computer model simulations of weather and climate and ultimately lead to better forecasts.

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Machine learning models can reliably inform clinicians about the disability progression of multiple sclerosis, according to a new study published this week in the open-access journal PLOS Digital Health by Edward De Brouwer of KU Leuven, Belgium, and colleagues.

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People generalize to form beliefs about a large language model's performance based on what they've seen from past interactions. When an LLM is misaligned with a person's beliefs, even an extremely capable model may fail unexpectedly when deployed in a real-world situation.

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Researchers found that an artificial intelligence (AI) model solved medical quiz questions -- designed to test health professionals' ability to diagnose patients based on clinical images and a brief text summary -- with high accuracy. However, physician-graders found the AI model made mistakes when describing images and explaining how its decision-making led to the correct answer.

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In blockchain development, there is a rule of thumb that only two of scalability, security, and decentralization are valid simultaneously. However, the mathematical expression of that rule was still a work in progress. Researchers discovered a mathematical expression for the blockchain trilemma. In the formula for Proof of Work-based blockchains, including Bitcoin, the product of the three terms--scalability, security, and decentralization--is 1.

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Large language models may pass medical exams with flying colors but using them for diagnoses would currently be grossly negligent. Medical chatbots make hasty diagnoses, do not adhere to guidelines, and would put patients' lives at risk. A team has systematically investigated whether this form of artificial intelligence (AI) would be suitable for everyday clinical practice. Despite the current shortcomings, the researchers see potential in the technology. They have published a method that can be used to test the reliability of future medical chatbots.

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Researchers have developed a new model that combines generative AI and satellite data to accurately forecast wildfire spread.

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Cut marks on fossils could be evidence of humans exploiting large mammals in Argentina more than 20,000 years ago, according to a new study.

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New research has examined the fossil record going back 66 million years and tracked changes to mammalian ecosystems and species diversity on the North American continent.

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A new technique estimates the reliability of a self-supervised foundation model, like those that power ChatGPT, without the need to know what task that model will be deployed on later.

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Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network even closer to the actual human brain may make it more reliable, according to the researchers.

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A new technique enables huge machine-learning models to efficiently generate more accurate quantifications of their uncertainty about certain predictions. This could help practitioners determine whether to trust the model when it is deployed in real-world settings.

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Researchers have developed a groundbreaking method for analysing heart MRI scans with the help of artificial intelligence, which could save valuable time and resources, as well as improve care for patients.

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An international research team has assembled the genome and 3D chromosomal structures of a 52,000-year-old woolly mammoth -- the first time such a feat has been achieved for any ancient DNA sample. The fossilized chromosomes, which are around a million times longer than most ancient DNA fragments, provide insight into how the mammoth's genome was organized within its living cells and which genes were active within the skin tissue from which the DNA was extracted. This unprecedented level of structural detail was retained because the mammoth underwent freeze-drying shortly after it died, which meant that its DNA was preserved in a glass-like state.

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Scientists developed and tested new artificial intelligence (AI) tools tailored to digital pathology--a rapidly growing field that uses high-resolution digital images created from tissue samples to help diagnose disease and guide treatment.