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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 9, 202438Views0Likes0Comments
Mathematician Justin Solomon is using modern geometric techniques to solve complex problems, often unrelated to shapes. He explains that geometric tools can be used to compare datasets, providing insight into the performance of machine-learning models. He asserted the significance of distance, similarity, curvature, and shape, all derived from geometry, in discussing data. His Geometric Data…

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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, 202443Views0Likes0Comments
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, 202435Views0Likes0Comments
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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A computational expert expands the limits of geometric studies.

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 9, 202441Views0Likes0Comments
Over two millennia ago, the ancient mathematician Euclid, widely recognized as the father of geometry, shifted our perspective on shapes. Today, Justin Solomon of MIT uses contemporary geometric methods to tackle complex challenges seemingly unrelated to shapes. Solomon utilizes geometric tools to analyze high-dimensional datasets, providing insights about the potential performance of machine learning models.…

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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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SiloFuse: Advancing Artificial Data Creation in Distributed Networks with Improved Privacy, Productivity, and Data Usefulness

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 8, 202437Views0Likes0Comments
Data is as valuable as currency in today's world, leading many industries to face the challenge of sharing and enhancing data across various entities while also protecting privacy norms. Synthetic data generation has provided organizations with a means to overcome privacy obstacles and unlock potential for collaborative innovation. This is especially relevant in distributed systems,…

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Effector: A Machine Learning Library Built on Python, Focused on Regional Feature Effects

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 8, 202445Views0Likes0Comments
Effector is a new Python library developed to address the limitations of traditional methods used to explain black-box models. Current global feature effect methods, including Partial Dependence Plots (PDP) and SHAP Dependence Plots, often fall short in explaining such models, especially when feature interactions or non-uniform local effects occur, resulting in potentially misleading interpretations. To overcome…

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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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The team at MIT publishes research reports on the administration of artificial intelligence.

Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Government, Machine learning, MIT Schwarzman College of Computing, Policy, School of Engineering, Technology and society, UncategorizedApril 8, 202438Views0Likes0Comments
MIT has released a set of policy briefs offering guidance for the governance of artificial intelligence (AI) for lawmakers. The goal of these documents is to strengthen the U.S.'s leadership in AI, minimize potential harm from misapplication, and promote the beneficial uses of AI in our society. The primary policy paper, titled “A Framework for U.S.…

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