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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 16, 202437Views0Likes0Comments
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.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 16, 202434Views0Likes0Comments
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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Narrowing 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 15, 202433Views0Likes0Comments
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.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 15, 202437Views0Likes0Comments
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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Bridging the gap between designing and manufacturing 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 15, 202442Views0Likes0Comments
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.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 15, 202440Views0Likes0Comments
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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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 14, 202437Views0Likes0Comments
Photolithography is a crucial technique in the production of computer chips and optical devices, but it is susceptible to micro discrepancies which can result in the final devices not performing as designed. MIT and the Chinese University of Hong Kong researchers have helped resolve this issue, using machine learning to create a digital simulator that…

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Neural networks with deep learning capabilities exhibit potential in their application to human auditory models.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 14, 202437Views0Likes0Comments
Researchers from MIT have moved closer to creating computational models that effectively mimic the structure and function of the human auditory system. Utilizing machine learning, they developed models that could help improve hearing aids, cochlear implants, and brain-machine interfaces. The recent study showed that most deep learning models, trained to execute auditory tasks, generated internal…

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Bridging the gap between the design and manufacturing 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 14, 202436Views0Likes0Comments
Photolithography is a manufacturing process that uses light to precisely etch features onto surfaces, such as producing computer chips and optical devices. However, small imprecisions in the process can sometimes result in devices not being produced to specifications. To close this gap, researchers from MIT and the Chinese University of Hong Kong are employing machine…

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Promising signs of modeling human hearing are displayed by deep neural networks.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 14, 202434Views0Likes0Comments
A new study from the Massachusetts Institute of Technology (MIT) has found that modern computational models based on machine learning and structured similarly to the human auditory system could assist researchers in developing better hearing aids, cochlear implants, and brain-machine interfaces. The largest study of its kind on deep neural networks trained for auditory tasks…

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Bridging the gap between the design and production stages 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 13, 202438Views0Likes0Comments
Researchers from MIT and the Chinese University of Hong Kong have leveraged machine learning to construct a digital simulator to enhance the precision of photolithography and bridge the gap between design and manufacturing. Photolithography, a crucial manufacturing process in computer chip production and optical device fabrication, suffers from slight deviations that can lead to shortcomings…

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Narrowing the distance 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 13, 202436Views0Likes0Comments
Photolithography, a technique used to etch precise features onto surfaces for the creation of computer chips and optical devices, is often inaccurately executed due to tiny deviations during manufacturing. In an attempt to bridge this gap between design and production, a team of researchers from MIT and the Chinese University of Hong Kong have developed…

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