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A computer technologist advances 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 15, 2024179Views0Likes0Comments
Justin Solomon, an Associate Professor in the MIT Department of Electrical Engineering and Computer Science (EECS), is using geometric techniques to solve complex computing problems. Solomon says this method is ideally suited to finding solutions in data science, as it can enable a deeper understanding of the distances, similarities, curvature and shape data. About half…

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Bridging the gap between designing and manufacturing 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 15, 2024205Views0Likes0Comments
Researchers from the Massachusetts Institute of Technology (MIT) and the Chinese University of Hong Kong have developed a digital simulator using machine learning to optimize the manufacturing process used in fabricating devices like computer chips and lenses. This technology, known as photolithography, manipulates light to precisely etch features onto a surface, but minute deviations can…

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Deep neural networks demonstrate potential in simulating human auditory systems.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 15, 2024195Views0Likes0Comments
A new study by MIT researchers reveals that computational models derived from machine learning, similar to the human auditory system, could significantly enhance the development of hearing aids, cochlear implants, and brain-machine interfaces. This is the largest study so far that delves into deep neural networks trained to perform auditory tasks. These models produced internal…

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The computational model successfully documents the hard-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 15, 2024188Views0Likes0Comments
During a chemical reaction, molecules gain energy until they reach a position termed the transition state. Existing at a level of energy where the reaction has no choice but to proceed, the transition state's transient nature makes it extremely difficult to observe experimentally. Its structures can be calculated using quantum chemistry-based techniques, but these are…

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Revealing Gamer Insights: A Unique Machine Learning Technique to Decode Gaming Conduct

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 14, 2024193Views0Likes0Comments
The world of mobile gaming is persistently evolving, with a continually intense focus on creating personalized and engaging experiences. Traditional methodologies to decipher player behaviour have become grossly inadequate due to the rapidly paced, dynamic nature of gaming. Researchers from KTH Royal Institute of Technology, Sweden, have proposed an innovative solution. A paper released by the…

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Assessing Global Awareness and Rote Learning in Artificial Intelligence: A Research Undertaken by Tübingen University

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 14, 2024168Views0Likes0Comments
Large Language Models (LLMs) have become a crucial tool in artificial intelligence, capable of handling a variety of tasks, from natural language processing to complex decision-making. However, these models face significant challenges, especially regarding data memorization, which is pivotal in generalizing different types of data, particularly tabular data. LLMs such as GPT-3.5 and GPT-4 are effective…

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Scientists at Apple have unveiled ‘pfl-research’, a swift, adaptable, and user-friendly Python infrastructure for the simulation of federated learning.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 14, 2024150Views0Likes0Comments
Federated learning (FL) is a revolutionary concept in artificial intelligence that permits the collective training of machine learning (ML) models across various devices and locations without jeopardizing personal data security. However, carrying out research in FL is challenging due to the difficulties in effectively simulating realistic, large-scale FL scenarios. Existing tools lack the speed and…

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A computer scientist is advancing 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 14, 2024184Views0Likes0Comments
Justin Solomon, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), is using advanced geometric techniques to deal with complex issues that don't seemingly have any connection with geometry. Solomon explains that geometric terms like distance, similarity, and…

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A computer engineer explores the limits of geometric principles.

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 14, 2024182Views0Likes0Comments
More than 2000 years after Greek mathematician Euclid revolutionized the understanding of shapes, MIT associate professor Justin Solomon uses modern geometric techniques to resolve complex problems that seemingly have little to do with shapes. Adopting these techniques to compare two datasets for machine learning model performance, Solomon argues that geometric tools can reveal whether the…

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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 14, 2024185Views0Likes0Comments
Photolithography is a crucial technique in the production of computer chips and optical devices, but it is susceptible to micro discrepancies which can result in the final devices not performing as designed. MIT and the Chinese University of Hong Kong researchers have helped resolve this issue, using machine learning to create a digital simulator that…

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Neural networks with deep learning capabilities exhibit potential in their application to human auditory models.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 14, 2024172Views0Likes0Comments
Researchers from MIT have moved closer to creating computational models that effectively mimic the structure and function of the human auditory system. Utilizing machine learning, they developed models that could help improve hearing aids, cochlear implants, and brain-machine interfaces. The recent study showed that most deep learning models, trained to execute auditory tasks, generated internal…

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The computational model encapsulates the hard-to-detect transition states in chemical reactions.

Artificial Intelligence, Chemical engineering, Chemistry, Machine learning, National Science Foundation (NSF), Research, School of Engineering, School of Science, UncategorizedApril 14, 2024177Views0Likes0Comments
During a chemical reaction, molecules gain energy until they reach a transition state. This is a point from which the reaction must proceed. However, this state is brief and almost impossible to observe experimentally. Traditionally, the structures of these transition states have been calculated with methods rooted in quantum chemistry. This process is extremely time-consuming. The…

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