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Deep neural networks demonstrate potential in replicating 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 4, 202435Views0Likes0Comments
Modern machine learning models are becoming increasingly adept at simulating the structure and function of the human auditory system, a development that could lead to improvements in devices like hearing aids, cochlear implants, and brain-machine interfaces. A team at MIT conducted what is considered the largest study of deep neural networks trained for auditory tasks…

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An automated platform instructs users on the appropriate timing for partnership 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, 202442Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have outlined an onboarding process, which includes training for users of artificial intelligence (AI) tools to better comprehend and utilise them. With a 5% accuracy improvement, the system setup enables a user to discern when to collaborate with AI by providing a personalised training programme. The AI…

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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 4, 202439Views0Likes0Comments
Researchers at Massachusetts Institute of Technology (MIT) and Chinese University of Hong Kong have invented a machine learning-based digital simulator to shrink the gap between design intention and actual manufacturing of computer chips and optical devices. The process of photolithography used in creating such devices often leads to tiny deviations between theoretical design and practical…

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Narrowing the divide between designing 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 4, 202436Views0Likes0Comments
Photolithography, a technique for fabricating computer chips and optical devices, frequently encounters problems due to minute deviations during the manufacturing process. To address this, scientists from MIT and the Chinese University of Hong Kong have successfully used machine learning to build a digital simulator that effectively mimics certain photolithography manufacturing processes. The simulator, which utilizes…

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Deep neural networks demonstrate potential in modeling human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 4, 202440Views0Likes0Comments
A study conducted by a team from MIT offers promising results in the development of computational models that simulate the function and structure of the human auditory system. These models have potential applications for improving hearing aids, cochlear implants, and brain-machine interfaces. Conducted on an unprecedented scale, the study used deep neural networks trained to…

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The automated mechanism instructs users on the optimal times to work in conjunction 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 3, 202433Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed an automated training system that can guide users on when and how to collaborate with AI models effectively. The system, designed to adapt to multiple tasks, does this by training users using data from the interaction between the human and AI for a specific…

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The automated system instructs users on the appropriate times for cooperating 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 3, 202438Views0Likes0Comments
MIT and MIT-IBM Watson AI Lab researchers have developed an automated system that trains users to effectively collaborate with artificial intelligence (AI). The system, which is designed to be customized for different tasks, identifies the circumstances under which a user should pay attention to the AI's recommendations and describes these conditions in natural language. Initially,…

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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 3, 202434Views0Likes0Comments
Photolithography, a process used to etch features onto surfaces like computer chips and optical lenses, often results in devices that underperform due to tiny variations during manufacturing. To address this, researchers from MIT and the Chinese University of Hong Kong have employed machine learning to create a digital simulator that replicates a specific photolithography manufacturing…

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Promising signs are exhibited by deep neural networks in their potential of modeling human hearing.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 3, 202435Views0Likes0Comments
In the largest study of deep neural networks that can perform auditory tasks, MIT found that the models mimic human auditory representations when exposed to the same sounds. Neural networks are models that have multiple layers of information-processing units that can be trained to perform particular tasks using large amounts of data. These models are…

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An automated setup instructs users about the appropriate timing for cooperation 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 3, 202437Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a system that educates a user on when to trust an AI assistant's recommendations. During the onboarding process, the user practices collaborating with the AI using training exercises and receives feedback on their and the AI's performance. This system led to a 5% improvement…

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MIT researchers investigating the influence and uses of generative AI have received the second installment of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedApril 3, 202444Views0Likes0Comments
Last summer, MIT called upon the academic community to provide papers that suggest effective approaches and policy recommendations in the field of generative AI. Expectations were surpassed when 75 proposals were received. After reviewing these submissions, the institution funded 27 of the proposed projects. During the fall, the response to a second call for proposals…

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