The rapid advancements in artificial intelligence have led to the development of smaller, more efficient AI models. Gone are the days when AI programs could only be accessed through the cloud due to their enormous size. Today, researchers are crafting leaner and more capable models that can run on devices as compact as smartphones. One
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Deep learning techniques have seen significant advancements in recent years, with the ability to achieve human-level accuracy on various tasks such as image classification and natural language processing. As a result, researchers have been exploring new hardware solutions to cope with the high computational requirements of these techniques. One approach that has been gaining attention
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Nonlinear light microscopy has opened up new possibilities in observing and interpreting complex biological processes. However, the use of intense light in this technique raises concerns about the potential damage it can cause to living matter. Despite its benefits, the mechanism behind the irreversible perturbation of cellular processes by intense light remains a significant gap
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In a recent study published in Science Advances, researchers Prof. Wang Can and Prof. Xu Xiulai have delved into the relationship between valley polarization switching and polarization degree in electrically controlled transition metal dichalcogenide heterobilayers (hBLs). This groundbreaking research highlights the importance of twist engineering in manipulating the valley degrees of freedom of interlayer excitons
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