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Categories: Computer Science: General, Engineering: Robotics Research

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Scientists have developed a technique called 'Time-dependent Stochastic Parameter Shift' in the realm of quantum computing and quantum machine learning. This breakthrough method revolutionizes the estimation of gradients or derivatives of functions, a crucial step in many computational tasks.

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Researchers have developed an easy-to-use optical chip that can configure itself to achieve various functions. The positive real-valued matrix computation they have achieved gives the chip the potential to be used in applications requiring optical neural networks.

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Researchers have demonstrated a type of quantum eraser. The physicists show that they can pinpoint and correct for mistakes in quantum computing systems known as 'erasure' errors. 

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Artificial intelligence (AI) comes with promises of helping coders code faster, drivers drive safer, and making daily tasks less time-consuming. But a recent study demonstrates that the tool, when adopted widely, could have a large energy footprint, which in the future may exceed the power demands of some countries.

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Understanding the interplay between consciousness, energy and matter could bring important insights to our fundamental understanding of reality.

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A team of computer scientists has created a neural network that can explain how it reaches its predictions. The work reveals what accounts for the functionality of neural networks--the engines that drive artificial intelligence and machine learning--thereby illuminating a process that has largely been concealed from users.   

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Whether you’re battling foes in a virtual arena or collaborating with colleagues across the globe, lag-induced disruptions can be a major hindrance to seamless communication and immersive experiences. That’s why researchers have developed new technology to make data transfer over optical fiber communication faster and more efficient.

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Big data and artificial intelligence (AI) are being used to model hidden patterns in nature, not just for one bird species, but for entire ecological communities across continents. And the models follow each species’ full annual life cycle, from breeding to fall migration to non-breeding grounds, and back north again during spring migration.

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Can artificial intelligence (AI) get hungry? Develop a taste for certain foods? Not yet, but a team of researchers is developing a novel electronic tongue that mimics how taste influences what we eat based on both needs and wants, providing a possible blueprint for AI that processes information more like a human being.

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Robots helped achieve a major breakthrough in our understanding of how insect flight evolved. The study is a result of a six-year long collaboration between roboticists and biophysicists.

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For reasons of food security and economic incentive, farmers continuously seek to maximize their marketable crop yields. As plants grow inconsistently, at the time of harvesting, there will inevitably be variations in quality and size of individual crops. Finding the optimal time to harvest is therefore a priority for farmers. A new approach making heavy use of drones and artificial intelligence demonstrably improves this estimation by carefully and accurately analyzing individual crops to assess their likely growth characteristics.

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Insect cyborgs may sound like something straight out of the movies, but hybrid insect computer robots, as they are scientifically called, could pioneer a new future for robotics. It involves using electrical stimuli to control an insect’s movement. Now, an international research group has conducted a study on the relationship between electrical stimulation in stick insects' leg muscles and the resulting torque (the twisting force that causes the leg to move). 

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As the internet quickly fills with viral videos of futuristic robots darting and racing around like the animals they’re built to mimic, researchers say that there’s an element of their movement’s programming that should not be overlooked: rhythm.

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Researchers developed the first AI to date that can intelligently design robots from scratch by compressing billions of years of evolution into mere seconds. It's not only fast but also runs on a lightweight computer and designs wholly novel structures from scratch — without human-labeled, bias-filled datasets.

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At the core of uncovering extreme events such as floods is the physics of fluids – specifically turbulent flows. Researchers leveraged a computer-vision deep learning technique and adapted it for nonlinear analysis of extreme events in wall-bounded turbulent flows, which are pervasive in numerous physics and engineering applications and impact wind and hydrokinetic energy, among others. Results show the technique employed can be invaluable for accurately identifying the sources of extreme events in a completely data-driven manner.

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Scientists unveil exciting possibilities for the development of highly efficient quantum devices.

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Scientists have created a non-invasive movement tracking method called GlowTrack that uses fluorescent dye markers to train artificial intelligence to capture movement, from a single mouse digit to the human hand. GlowTrack has applications spanning biology, robotics, medicine, and beyond.

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A new study has found that people can learn to use supernumerary robotic arms as effectively as working with a partner in just one hour of training.

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Researchers have developed a novel superconducting qubit architecture that can perform operations between qubits with much higher accuracy than scientists have yet been able to achieve. This architecture, which utilizes a relatively new type of superconducting qubit called fluxonium, is scalable and could be used to someday build a large-scale quantum computer.

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Boosting virtual screening with machine learning allowed for a 10-fold time reduction in the processing of 1.56 billion drug-like molecules. Researchers teamed up with industry and supercomputers to carry out one of the world's largest virtual drug screens.