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

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An artificial intelligence algorithm can allow researchers to more efficiently use 3D printing to manufacture intricate structures. The development could allow for more seamless use of 3D printing for complex designs in everything from artificial organs to flexible electronics and wearable biosensors. As part of the study, the algorithm learned to identify, and then print, the best versions of kidney and prostate organ models, printing out 60 continually improving versions.

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Archeologists say new findings might help resolve the debate about Clovis points and reshape how we think about what life was like roughly 13,000 years ago. After an extensive review of writings and artwork -- and an experiment with replica Clovis point spears -- a team of archaeologists says humans may have braced the butt of their weapons against the ground in a way that would impale a charging animal. The force would have driven the spear deeper into the predator's body, unleashing a more damaging blow than even the strongest prehistoric hunters would have been capable of by throwing or jabbing megafauna.

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A new study shows how the mismatch between where fossils are preserved and where humans likely lived may influence our understanding of early human evolution.

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Artificial intelligence (AI) has exploded in popularity as of late. But just like a human, it's hard to read an AI model's mind. Explainable AI (XAI) could help us do just that by providing justification for a model's decisions. And now, researchers are using XAI to scrutinize predictive AI models more closely, which could help make better antibiotics.

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A new machine learning model can predict autism in young children from relatively limited information. The model can facilitate early detection of autism, which is important to provide the right support.

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Researchers are setting out to challenge our misconceptions about the Dodo, one of the most well-known but poorly understood species of bird. Researchers have undertaken the most comprehensive review of the taxonomy of the Dodo and its closest relative, the Rodriguez Island Solitaire.

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A mathematical framework that builds on the economic theory of hidden-action models provides insight into how the unobservable nature of effort and risk shapes investigators' research strategies and the incentive structures within which they work, according to a new study.

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Researchers simulated social norms with a supercomputer. Their findings contribute to a deeper understanding of the evolution of social norms and their role in fostering cooperative behavior.

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Researchers discover that while artificial intelligence (AI) tools can make accurate diagnoses from textbook-like descriptions of genetic diseases, the tools are significantly less accurate when analyzing summaries written by patients about their own health. These findings demonstrate the need to improve these AI tools before they can be applied in health care settings to help make diagnoses and answer patient questions.

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New research explains the mathematics behind how initial predispositions and additional information affect decision making.

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Large Language Models (LLMs) are entirely controllable through human prompts and lack 'emergent abilities'; that is, the means to form their own insights or conclusions. Increasing model size does not lead LLMs to gain emergent reasoning abilities, meaning they will not develop hazardous abilities and therefore do not pose an existential threat. A new study sheds light on the (until now unexplained) capabilities and shortcomings of LLMs, including the need for carefully engineered prompts to exhibit good performance.

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A new artificial intelligence model can predict how different proteins may bind to DNA.

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Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use machine learning in computational biology, understanding model behavior remains crucial for uncovering the underlying biological mechanisms in health and disease. Researchers now propose guidelines that outline pitfalls and opportunities for using interpretable machine learning methods to tackle computational biology problems.

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What distinguishes the growth and development patterns of early mammals of the Jurassic period? Paleontologists have been able to gauge the lifespan and growth rates of these ancient animals, and even when they reached maturity, by studying growth rings in fossilized tooth roots.

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Mammoths, the massive pre-historic ice age cousins of the modern-day elephant, have always been understood to have inhabited parts of British Columbia, but the question of when has always been a bit woolly. Now, a new study has given scientists the clearest picture yet when the giant mammals roamed Vancouver Island.

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The pterosaur likely used all four limbs to propel itself in the air, as seen in bats today, researchers have found.

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To protect the Amazon and support the wellbeing of its people, its economy needs to shift from environmentally harmful production to a model built around the diversity of indigenous and rural communities, and standing forests.

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With GROVER, a new large language model trained on human DNA, researchers could now attempt to decode the complex information hidden in our genome. GROVER treats human DNA as a text, learning its rules and context to draw functional information about the DNA sequences.

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A tiny fossil penguin plays a huge role in the evolutionary history of the bird, an international study shows.

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Thermometer, a new calibration technique tailored for large language models, can prevent LLMs from being overconfident or underconfident about their predictions. The technique aims to help users know when a model should be trusted.