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A computer scientist is expanding the limits of geometry.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, MIT Schwarzman College of Computing, Profile, School of Engineering, UncategorizedApril 13, 202436Views0Likes0Comments
Justin Solomon, an associate professor at the Massachusetts Institute of Technology (MIT) Department of Electrical Engineering and Computer Science, is applying modern geometric techniques to solve complex problems in machine learning, data science, and computer graphics. He leads the Geometric Data Processing Group, half of which works on optimizing two- and three-dimensional geometric data in…

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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 13, 202435Views0Likes0Comments
Researchers from MIT and the Chinese University of Hong Kong are using machine learning to close the gap between design and manufacturing processes in photolithography - a method used in the creation of computer chips and optical devices. Photolithography involves using light to etch features onto a surface. However, tiny variations during production often lead…

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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 13, 202436Views0Likes0Comments
A study by Massachusetts Institute of Technology (MIT) shows that machine learning-based computational models are making strides towards mimicking the human auditory system, potentially improving the design of devices like hearing aids and cochlear implants. The research indicated that these models’ internal data structures have similarities to those seen in the human brain in response…

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The computational model successfully records the difficult-to-detect transition phases of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 13, 202432Views0Likes0Comments
Chemical reactions reach a 'transition state' when molecules gain enough energy for the reaction to proceed. This state is brief and hard to observe experimentally. The arrangement of these transition states can be calculated through quantum chemistry, but it is highly time-consuming. Scientists at MIT have developed a faster method using machine learning which computes…

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This Artificial Intelligence research released by MIT presents a handbook for adjusting distinct material attributes through Machine Learning.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 12, 202435Views0Likes0Comments
Researchers at The Massachusetts Institute of Technology (MIT) have established a proposed method which merges machine learning with first-principles calculations to help in managing the computational complexities required in understanding the thermal conductivity of semiconductors, specifically focusing on diamonds. The diamond, known for its exceptional thermal conductivity, has several factors that complicate the conventional understanding…

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A technology scholar is expanding the horizons of geometric study.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, MIT Schwarzman College of Computing, Profile, School of Engineering, UncategorizedApril 12, 202435Views0Likes0Comments
Justin Solomon, based at MIT's Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory, is using modern geometric techniques to solve a wide range of mathematical and AI problems. Drawing on the principles of ancient geometry, Solomon's work has applications from autonomous vehicles identifying pedestrians using…

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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 12, 202437Views0Likes0Comments
Photolithography, the process of manipulating light to etch features on to a surface, is crucial in making computer chips and optical devices. However, the performance of devices made using this process often falls short of their original designs due to minute deviations during manufacturing. To address this design-to-manufacturing gap, researchers from MIT and the Chinese…

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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 12, 202441Views0Likes0Comments
Photolithography, a process of etching detailed patterns onto surfaces using light, is a crucial technique in the design and production of computer chips and other optical devices, such as lenses. However, minute deviations during manufacturing can cause a discrepancy between the designer's intentions and the actual produced device. To help bridge this gap between design…

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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 12, 202436Views0Likes0Comments
MIT researchers have conducted a study that suggests machine learning models might be used to better design hearing aids, cochlear implants, and brain-machine interfaces. In the largest research project to date involving deep neural networks trained to carry out auditory tasks, the researchers showed that most of these models mimic the human brain’s behaviour when…

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Computational model successfully identifies the hard-to-catch transitional stages of chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 12, 202433Views0Likes0Comments
A team of researchers from the Massachusetts Institute of Technology (MIT) has developed a machine learning model that can quickly calculate the structures of transition states in chemical reactions. These fleeting moments occur when molecules have gained enough energy to proceed with a reaction, but are notoriously difficult to study due to their ephemeral nature.…

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A computer science expert is expanding the frontiers of geometry.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, MIT Schwarzman College of Computing, Profile, School of Engineering, UncategorizedApril 12, 202437Views0Likes0Comments
Over 2,000 years ago, Greek mathematician Euclid, often called the father of geometry, revolutionized the understanding of shapes. In today's technological era, a 21st-century geometer, Justin Solomon, uses sophisticated techniques to solve complex problems related to shapes but often unrelated to them. Solomon applies geometry to study datasets for comparing their effectiveness in machine learning…

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