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Deep neural networks demonstrate potential as a representation of human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 8, 202439Views0Likes0Comments
A team from the Massachusetts Institute of Technology (MIT) has found that machine learning (ML) models can effectively mimic and understand the human auditory system, potentially helping to improve technologies such as cochlear implants, hearing aids and brain-machine interfaces. These findings are based on the largest-ever study of deep neural networks used to perform auditory…

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Bridging the gap between design and manufacturing for optical devices.

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 8, 202438Views0Likes0Comments
Photolithography is a commonly used manufacturing process that manipulates light to etch features onto surfaces, creating computer chips and optical devices like lenses. However, minute deviations in the process often result in these devices not matching their original designs. To bridge this design-manufacturing gap, a team from MIT and the Chinese University of Hong Kong…

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Human hearing can potentially be modeled efficiently using deep neural networks.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 8, 202440Views0Likes0Comments
MIT researchers have found that computational models derived from machine learning, designed to mimic the human auditory system, have the potential to improve hearing aids, cochlear implants, and brain-machine interfaces. They are moving closer to this goal by using these models in the largest study yet of deep neural networks trained to perform auditory tasks.…

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Bridging the gap between design and production for optical instruments.

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 7, 202432Views0Likes0Comments
Photolithography, the technique of etching features onto a surface using light manipulation, is commonly used in the manufacturing of computer chips and optical devices. However, small deviations during the manufacturing process often impact the performance of the finished product. To address this, researchers from MIT and the Chinese University of Hong Kong have leveraged machine…

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Deep neural networks exhibit potential as representations of human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 7, 202434Views0Likes0Comments
MIT researchers have found that computational models based on machine learning that simulate the human auditory system are drawing closer to potentially helping in the creation of improved hearing aids, cochlear implants and brain-machine interfaces. The study is the most comprehensive comparison so far made between these computer models and the human auditory system. Notably,…

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Bridging the gap between design and production for optical instruments

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 7, 202432Views0Likes0Comments
Researchers at MIT and the Chinese University of Hong Kong have developed a machine learning tool to emulate photolithography manufacturing processes. Photolithography is commonly used in the production of computer chips and optical devices, manipulating light to etch features onto surfaces. Variations in the manufacturing process can cause the end products to deviate from their…

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

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 7, 202430Views0Likes0Comments
A study from MIT has suggested that machine-learning computational models can help design more effective hearing aids, cochlear implants, and brain-machine interfaces by mimicking the human auditory system. The study was based on deep neural networks which, when trained on auditory tasks, create internal representations similar to those generated in the human brain when processing…

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Bridging the gap between design and production for optical equipment.

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 6, 202436Views0Likes0Comments
Photolithography, the process of using light to precisely etch designs onto a surface, is a primary method for creating computer chips and optical devices. However, it's common for slight deviations during manufacturing to cause the final product to diverge from the intended design. To bridge this gap, researchers from MIT and the Chinese University of…

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Deep neural networks exhibit potential in replicating human auditory models.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 6, 202436Views0Likes0Comments
A new study from MIT suggests that computational models rooted in machine learning are moving closer to simulating the structure and function of the human auditory system. Such technology could improve the development of hearing aids, cochlear implants, and brain-machine interfaces. The study analyzed deep neural networks trained for auditory tasks, finding similarities with the…

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Bridging the gap between design and production in the field of optical devices

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 6, 202434Views0Likes0Comments
Photolithography is a complex process often used in making computer chips and lenses where light is expertly etched onto a surface to create features. However, tiny deviations that occur during the manufacturing process often result in the final product not meeting the initially intended design. To rectify this, a team of researchers from MIT and the…

Read More

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

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 6, 202434Views0Likes0Comments
MIT researchers have found that computational models designed with machine learning techniques are becoming more accurate in mimicking the structure and function of the human auditory system. They believe these models could assist in the development of improved hearing aids, cochlear implants and brain-machine interfaces. In an extensive study of deep neural networks trained for…

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