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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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The automated system educates users on the appropriate times to partner with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 6, 202437Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a system that instructs users when to trust an AI system’s decision-making. In medicine, there might be instances like a radiologist using an AI model for reading X-rays where human intervention can make a difference. However, clinicians are uncertain whether to lean on 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…

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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 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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The automated system instructs users on the appropriate time to work together with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 5, 202434Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed an onboarding process which teaches users how to effectively collaborate with artificial intelligence (AI) assistants. The system was designed to provide guidance to users and to improve collaboration between humans and AI. The automated system learns how to create the onboarding process by gathering…

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Human hearing models indicate potential through the use of deep neural networks.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 5, 202437Views0Likes0Comments
A study from MIT has shown that machine learning can be employed to improve the design of hearing aids, cochlear implants, and brain-machine interfaces. These computational models are designed to simulate the function and structure of the human auditory system. The research is the largest of its kind in studying deep neural networks that have…

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The automated system provides guidance on when to engage with an AI assistant for collaboration.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 5, 202435Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed an automated system that trains users on when to collaborate with an AI assistant. In medical fields such as radiology, this system could guide a practitioner on when to trust an AI model’s diagnostic advice. The researchers claim that their onboarding procedure led to…

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Deep neural networks exhibit potential in mimicking the human auditory system.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 5, 202442Views0Likes0Comments
Researchers at MIT have discovered that computational models derived from machine learning are increasingly mimicking the function and structure of the human auditory system. This finding has significant implications for the design of more effective hearing aids, cochlear implants, and brain-machine interfaces. In the most extensive study to date of deep neural networks used for…

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The automated system instructs users on the appropriate times to engage with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 4, 202435Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a system that trains users on when to trust an AI model's advice. This automated system essentially creates an onboarding process based on a specific task performed by a human and an AI model. It then uses this data to develop training exercises, helping…

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