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Categories: Computer Science: Artificial Intelligence (AI), Mathematics: Modeling

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A technique can plan a trajectory for a robot using only language-based inputs. While it can't outperform vision-based approaches, it could be useful in settings that lack visual data to use for training.

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Researchers have succeeded in developing a DNA-based molecular controller. Crucially, this controller enables the autonomous assembly and disassembly of molecular robots, as opposed to manually directing it.

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Researchers have developed a technique that allows artificial intelligence (AI) programs to better map three-dimensional spaces using two-dimensional images captured by multiple cameras. Because the technique works effectively with limited computational resources, it holds promise for improving the navigation of autonomous vehicles.

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Data assimilation is an important mathematical discipline in earth sciences, particularly in numerical weather prediction (NWP). However, conventional data assimilation methods require significant computational resources. To address this, researchers developed a novel method to solve data assimilation on quantum computers, significantly reducing the computation time. The findings of the study have the potential to advance NWP systems and will inspire practical applications of quantum computers for advancing data assimilation.

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Researchers have successfully used a new robot system to improve treatment for debilitating eye disease.

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Flexible piezoelectric sensors are essential to monitor the motions of both humans and humanoid robots. However, existing designs are either are costly or have limited sensitivity. In a recent study, researchers tackled these issues by developing a novel piezoelectric composite material made from electrospun polyvinylidene fluoride nanofibers combined with dopamine. Sensors made from this material showed significant performance and stability improvements at a low cost, promising advancements in medicine, healthcare, and robotics.

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Researchers have demonstrated a new method that leverages artificial intelligence (AI) and computer simulations to train robotic exoskeletons to autonomously help users save energy while walking, running and climbing stairs.

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An artificial intelligence-powered virtual teammate with a female voice boosts participation and productivity among women on teams dominated by men, according to new research.

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Researchers have demonstrated miniature soft hydraulic actuators that can be used to control the deformation and motion of soft robots that are less than a millimeter thick. The researchers have also demonstrated that this technique works with shape memory materials, allowing users to repeatedly lock the soft robots into a desired shape and return to the original shape as needed.

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Today, researchers are developing ways to accelerate discovery by combining automated experiments, artificial intelligence and high-performance computing. A novel tool that leverages those technologies has demonstrated that AI can influence materials synthesis and conduct associated experiments without human supervision.

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To help probe the mystery of how brains control movement, scientists have created a virtual rat with an artificial brain that can move around just like a real rodent. The researchers found that activations in the virtual control network accurately predicted neural activity measured from the brains of real rats producing the same behaviors.

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Researchers are breaking through the difficulties of robotic recognition of various common, yet complex, items. Their layered sensor is equipped with material detection at the surface and pressure sensitivity at the bottom, with a porous middle layer sensitive to thermal changes. An efficient cascade classification algorithm rules out object types in order, from easy to hard, starting with simple categories like empty cartons before moving on to orange peels or scraps of cloth.

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Nightmare material or truly man's best friend? A team of researchers equipped a dog-like quadruped robot with a mechanized arm that takes air samples from potentially treacherous situations, such as an abandoned building or fire. The robot dog walks samples to a person who screens them for potentially hazardous compounds.

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Scientists have created innovative soft robots equipped with electronic skins and artificial muscles, allowing them to sense their surroundings and adapt their movements in real-time.

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Boys are good at math, girls not so much? A study has analyzed the social mechanisms that contribute to the gender gap in math confidence. While peer comparisons seem to play a crucial role for boys, girls' subjective evaluations are more likely to be based on objective performance.

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Researchers have created digital babies to better understand infants' health in their critical first 180 days of life. The team created 360 advanced computer models that simulate the unique metabolic processes of each baby.

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A research team has developed a liquid metal-based electronic logic device that mimics the intelligent prey-capture mechanism of Venus flytraps. Exhibiting memory and counting properties, the device can intelligently respond to various stimulus sequences without the need for additional electronic components. The intelligent strategies and logic mechanisms in the device provide a fresh perspective on understanding 'intelligence' in nature and offer inspiration for the development of 'embodied intelligence'.

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Have you ever wished you could understand what your dog is trying to say to you? Researchers are exploring the possibilities of AI, developing tools that can identify whether a dog's bark conveys playfulness or aggression.

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Researchers have developed a model that enables computers to interpret and understand human emotions, utilizing principles of mathematical psychology. In the future, the model can help the computer to adapt its own behavior and guide an irritated or anxious user in different ways. The implications of such technology are profound, offering a glimpse into a future where computers are not merely tools, but empathetic partners in user interaction.

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MIT researchers developed a technique to combine robotics training data across domains, modalities, and tasks using generative AI models. They create a combined strategy from several different datasets that enables a robot to learn to perform new tasks in unseen environments.