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Research

The computational model successfully encapsulates the hard-to-capture transitional stages of chemical reactions.

In a breakthrough study at MIT, researchers have used machine learning (ML) to calculate the ephemeral transition state in chemical reactions, representing a significant step forward for computational chemistry. The transition state occurs when molecules in a reaction gain energy to the point where the reaction becomes irreversible. Researchers have struggled to observe this pivotal…

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A dynamic approach to assist animators in enhancing their artistry.

A new technique introduced by researchers from the Massachusetts Institute of Technology (MIT) could provide artists with enhanced control over their animated creations. This method uses mathematical functions known as barycentric coordinates, which define how 2D and 3D shapes can bend, stretch, and move through space. The procedure offers multiple options for barycentric coordinate functions,…

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Bridging the gap between design and production for optical instruments.

Researchers from MIT and the Chinese University of Hong Kong have developed a machine learning technique to bridge the gap between the design and manufacturing processes in photolithography. Photolithography, a technique commonly used in fabricating computer chips and optical devices like lenses, often falls short of the designers' expectations due to minute deviations during manufacturing.…

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Human hearing can potentially be modeled effectively by deep neural networks.

MIT researchers have conducted the largest study to date of deep neural networks trained for auditory tasks. These computational models, which mimic the structure and function of the human auditory system, have the potential to improve hearing aids, cochlear implants, and brain-machine interfaces. The study shows that the majority of the models generate representations which…

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The computational model accurately encapsulates the hard-to-detect transitional phases of chemical reactions.

Scientists at MIT have devised a machine learning-based method that can rapidly calculate the transitional states of molecules during a chemical reaction. The transient nature of these states has made observation particularly challenging. Understanding these states is key to developing catalysts or deciphering how natural systems induce specific changes. The MIT team constructed their computational approach…

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A versatile approach to assist animators in enhancing their craft.

MIT researchers have developed a technique that might allow animators to have more control over their creations. It leverages mathematical functions known as barycentric coordinates to define the way 2D and 3D shapes bend, stretch and move. It gives artists significant flexibility, allowing them to select functions that best fit their vision for the animation.…

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Narrowing the gap between design and production in the field of optical devices.

Researchers from MIT and the Chinese University of Hong Kong have developed a machine-learning based digital simulator that can more precisely model specific photolithography manufacturing processes used in creating computer chips and optical devices like lenses. The simulator is designed to help close the gap between design and manufacturing, as tiny deviations during the manufacturing…

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Deep neural networks demonstrate potential in being suitable models for studying human auditory perception.

A new study by researchers from the Massachusetts Institute of Technology (MIT) has brought us closer to creating computational models that can mimic the human auditory system in the design of better hearing aids, cochlear implants, and brain-machine interfaces. The research, which is the most extensive of its kind, showed that most deep neural network models…

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The computational model successfully captures the hard-to-detect transition states in chemical reactions.

During a chemical reaction, molecules gain energy until they reach a point known as the transition state, a pivotal moment where the reaction must proceed. The structures of these states can be determined using quantum chemistry methods, but these calculations are time-intensive. To tackle this issue, a team of MIT researchers developed a machine learning-based…

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A versatile answer designed to assist animators in enhancing their artwork.

Researchers from MIT have developed a method that could provide animators with greater control over their animations. This new technique generates mathematical functions known as barycentric coordinates, which define how 2D and 3D shapes can bend, stretch, and move through space. This allows the artist to determine the movements of animated objects according to their…

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Bridging the gap between designing and manufacturing for optical equipment.

Researchers from the Massachusetts Institute of Technology (MIT) and the Chinese University of Hong Kong have developed a digital simulator using machine learning to optimize the manufacturing process used in fabricating devices like computer chips and lenses. This technology, known as photolithography, manipulates light to precisely etch features onto a surface, but minute deviations can…

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Deep neural networks demonstrate potential in simulating human auditory systems.

A new study by MIT researchers reveals that computational models derived from machine learning, similar to the human auditory system, could significantly enhance the development of hearing aids, cochlear implants, and brain-machine interfaces. This is the largest study so far that delves into deep neural networks trained to perform auditory tasks. These models produced internal…

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