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National Institutes of Health (NIH)

Deep neural networks demonstrate potential as representations of human auditory mechanisms.

An MIT study has been making strides towards developing computational models that mimic the human auditory system, which could enhance the design of hearing aids, cochlear implants, and brain-machine interfaces. These computational models stem from advances in machine learning. The study found that internal representations generated by deep neural networks often mirror those within the…

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Bridging the gap between design and production for optical devices

Researchers from Massachusetts Institute of Technology (MIT) and the Chinese University of Hong Kong have developed a digital simulator that mimics the photolithography process, a technique used to manufacture computer chips and optical devices. The project marks the first use of actual data from a photolithography system in the construction of a simulator. This advancement could…

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Deep neural networks exhibit potential in serving as models for human auditory processing.

A study by Massachusetts Institute of Technology (MIT) researchers has indicated that computational models that perform auditory tasks could speed up the development of improved hearing aids, cochlear implants, and brain-machine interfaces. In the study, the largest ever conducted into deep neural network-based models trained to perform hearing-related functions, it was found that most mimic…

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Bridging the gap between design and production in the field of optical instruments.

Researchers from MIT and the Chinese University of Hong Kong have developed a machine learning-powered digital simulator that can accurately replicate a particular photolithography manufacturing process. Photolithography is a technique used to intricately etch features onto surfaces, often used in the creation of computer chips and optical devices. Despite its precision, tiny deviations in the…

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Deep neural networks present potential in modeling human auditory perceptions.

Scientists at MIT have made significant progress in developing advanced computational models that can emulate the human auditory system, which could be pivotal in improving hearing aids, cochlear implants, and brain-machine interfaces. The researchers used deep neural networks—a type of artificial intelligence (AI) that imitates the human brain—to conduct the most extensive study so far…

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Bridging the gap between design and manufacturing in the field of optical devices.

Researchers at MIT and the Chinese University of Hong Kong have developed a machine learning-powered digital simulator for the photolithography process, frequently used in the manufacture of computer chips and optical devices. The team has built a digital simulator that can model the photolithography system based on real-world data, allowing for a greater level of…

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Deep neural networks demonstrate potential in being models for human auditory systems.

Computational models that imitate how the human auditory system works may hold promise in developing technologies like enhanced cochlear implants, hearing aids, and brain-machine interfaces, a recent study from the Massachusetts Institute of Technology (MIT) reveals. The study focused on deep neural networks, machine learning-derived computational models that stimulate the basic structure of the human…

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

Photolithography is an important process in the manufacture of computer chips and optical devices like lenses, using light to carve precise features onto a surface. However, minor deviations during the manufacturing process can lead to these devices underperforming when compared to the original designs. To address this issue, researchers from MIT and the Chinese University…

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Deep neural networks demonstrate potential as frameworks for understanding human auditory perception.

An MIT study has taken a significant step towards the development of computational models capable of mimicking the structure and function of the human auditory system. The models could have applications in the production of improved hearing aids, cochlear implants, and brain-machine interfaces. The researchers discovered that modern machine learning-derived computational models are progressing towards…

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Bridging the divide between design and production for optical instruments.

Photolithography, the process of using light to etch features onto surfaces for the manufacturing of computer chips and optical devices, often fails to accurately match designer’s intentions due to tiny inconsistencies in the manufacturing process. Researchers at MIT and the Chinese University of Hong Kong have developed a machine-learning digital simulator in an effort to…

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Promising indications have been seen in deep neural networks as potential models for human auditory perception.

A recent study from MIT suggests that computational models built using machine learning could closely mimic the structure and function of the human auditory system. This discovery could potentially help researchers in designing more effective hearing aids, cochlear implants, and brain-machine interfaces. In the largest-ever examination of deep learning neural networks trained for auditory tasks, the…

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