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A computational model successfully grasps the hard-to-detect transitional phases of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 17, 202472Views0Likes0Comments
A team of MIT scientists has developed a machine learning-based model to calculate transition states during chemical reactions, a process which normally requires quantum computing and can take hours or even days to complete. Transition states, which inevitably occur during reactions when molecules reach a particular energy threshold, were previously calculated through quantum chemistry’s density…

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A versatile approach designed to assist illustrators in enhancing their animation.

Algorithms, Artificial Intelligence, Arts, Augmented and virtual reality, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, UncategorizedApril 17, 202464Views0Likes0Comments
Researchers at MIT have developed a technique that could allow animators to have greater control over their characters. The method uses mathematical functions known as barycentric coordinates, which define how 2D and 3D shapes can bend, stretch, and move through space. This technique could provide artists with more flexibility in their animations, unlike previous techniques…

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MIT researchers, utilizing AI, have discovered a new category of potential antibiotics.

Antibiotics, Artificial Intelligence, Biological engineering, Broad Institute, Drug discovery, Drug resistance, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Machine learning, Research, School of Engineering, UncategorizedApril 17, 202468Views0Likes0Comments
A powerful new class of antibiotics capable of killing drug-resistant bacteria has been discovered by researchers at the Massachusetts Institute of Technology (MIT), by utilizing a subtype of artificial intelligence (AI) known as deep learning. Results from the study, published in the journal Nature, demonstrate the compound's effectiveness against Methicillin-Resistant Staphylococcus Aureus (MRSA), a bacterium…

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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 17, 202466Views0Likes0Comments
Photolithography, a process used to fabricate computer chips and optical devices, often falls short of designers' intentions due to tiny deviations during manufacturing. To address this, researchers from MIT and the Chinese University of Hong Kong have used machine learning to develop a digital simulator that precisely replicates a specific photolithography manufacturing process. The simulator…

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Deep neural networks demonstrate potential in simulating human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 17, 202469Views0Likes0Comments
A new study from MIT reveals that modern computational models based on machine learning, which mimic the structure and function of the human auditory system, are coming closer to potentially aiding the design of improved hearing aids, cochlear implants, and brain-machine interfaces. The MIT team’s research is the most extensive to date on deep neural networks,…

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A computational model successfully records the hard-to-track transitional phases of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 17, 202461Views0Likes0Comments
MIT researchers have developed a machine learning-based technique that can rapidly calculate the structures of fleeting transition states during chemical reactions. Identifying and understanding these quasi-instantaneous moments, when molecules have collected enough energy to proceed with reaction, is crucial to fields such as catalyst design and natural system research. With traditional quantum chemistry-based techniques, it…

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A versatile approach for assisting artists in enhancing animation.

Algorithms, Artificial Intelligence, Arts, Augmented and virtual reality, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, UncategorizedApril 17, 202471Views0Likes0Comments
An innovative technique introduced by MIT researchers could offer greater control to artists who create animations for films and video games. The researchers' method revolves around generating mathematical functions known as barycentric coordinates. These coordinates determine how 2D and 3D shapes can stretch, bend and move in space. This new technique is distinctive in its…

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3 Enquiries: Improving final-stage distribution using artificial intelligence learning systems.

Algorithms, Artificial Intelligence, Business and management, Center for Transportation and Logistics, Interview, Machine learning, MIT Schwarzman College of Computing, MIT Sloan School of Management, MIT-IBM Watson AI Lab, Research, School of Engineering, Staff, Supply chains, Transportation, UncategorizedApril 17, 202464Views0Likes0Comments
Across the U.S., hundreds of thousands of drivers deliver innumerable parcels daily, with most deliveries taking a few days. Coordinating such a enormous supply chain in a predictable and timely manner is a challenging problem in operations research, particularly optimizing the last leg of delivery routes, which is often the costliest due to factors such…

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Bridging the gap between designing 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 16, 202472Views0Likes0Comments
Photolithography, a process used to create computer chips and optical devices, can often have tiny deviations during production, causing the final product to fall short of the initial design. To address this, researchers from MIT and the Chinese University of Hong Kong have used machine learning to develop a digital simulator that more accurately models…

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Deep neural networks exhibit potential for modelling human auditory processes.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 16, 202465Views0Likes0Comments
A new study from MIT suggests that modern computational models powered by machine learning could potentially aid the design of better hearing aids, cochlear implants, and brain-machine interfaces. These models, specifically deep neural networks, are starting to encompass functions that replicate the structure of the human auditory system.  The study further illuminates how to best train…

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