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The computational model successfully records the hard-to-capture transition stages of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 11, 202436Views0Likes0Comments
A team of researchers at the Massachusetts Institute of Technology (MIT) has developed a machine learning-based method to swiftly calculate the structures of transition states, crucial moments in chemical reactions. This state, at which molecules attain the necessary energy for a reaction, is important but fleetingly transient and difficult to experimentally observe. Calculating these structures…

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Bridging the gap between design and production in the field of 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 10, 202431Views0Likes0Comments
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.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 10, 202426Views0Likes0Comments
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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An improved, more efficient method to inhibit AI chatbots from delivering harmful responses.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedApril 10, 202435Views0Likes0Comments

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Bridging the gap between design and manufacturing 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 10, 202441Views0Likes0Comments
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.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 10, 202434Views0Likes0Comments
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.

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 9, 202442Views0Likes0Comments
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.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 9, 202434Views0Likes0Comments
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.

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 9, 202438Views0Likes0Comments
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.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 9, 202438Views0Likes0Comments
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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In case an antibiotic is unsuccessful: AI is being utilized by MIT researchers to focus on dormant bacteria.

Antibiotics, Artificial Intelligence, Bacteria, Biological engineering, Drug discovery, Health sciences and technology, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Machine learning, Medicine, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 9, 202435Views0Likes0Comments
Since the 1970s, finding new antibiotics has been challenging. The World Health Organization now considers the antimicrobial resistance crisis as one of the top 10 global public health threats. Bacteria can become resistant to antibiotics, especially when an infection is treated repeatedly. Some bacteria become metabolically inert, avoiding detection by antibiotics that only respond to…

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The automated platform instructs users on the appropriate instances 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 8, 202438Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed an AI system designed to educate users on when to trust an AI's decision-making process - for instance, a radiologist determining if a patient's X-ray shows signs of pneumonia. The training system identifies scenarios where the human should not trust the AI model, automatically…

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