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Deep neural networks demonstrate potential in modeling human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 4, 202443Views0Likes0Comments
A study conducted by a team from MIT offers promising results in the development of computational models that simulate the function and structure of the human auditory system. These models have potential applications for improving hearing aids, cochlear implants, and brain-machine interfaces. Conducted on an unprecedented scale, the study used deep neural networks trained to…

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Effortlessly shift between no-code and code-first machine learning using Amazon SageMaker Canvas and Amazon SageMaker Studio.

Amazon SageMaker, Amazon SageMaker Canvas, Amazon SageMaker Studio, Intermediate (200), Technical How-to, UncategorizedApril 4, 202443Views0Likes0Comments
Amazon SageMaker Studio and Amazon SageMaker Canvas are powerful tools by AWS designed for machine learning (ML) development and operation. SageMaker Studio is a web-based, integrated development environment (IDE) allowing users to build, train, debug, deploy, and monitor ML models. SageMaker Canvas is a no-code ML tool enabling business and data teams to craft accurate…

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Is Our Approach in Assessing Large-Scale Visual-Language Models Correct? This Chinese AI Research Presents MMStar: A Superior Vision-Driven Multi-Modal Benchmark.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedApril 3, 202436Views0Likes0Comments
Researchers have noted gaps in the evaluation methods for Large Vision Language Models (LVLMs). Primarily, they note that evaluations overlook the potential of visual content being unnecessary for many samples, as well as the risk of unintentional data leakage during training. They also indicate the limitations of single-task benchmarks for accurately assessing the multi-modal capabilities…

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The automated mechanism instructs users on the optimal times to work in conjunction 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 3, 202436Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed an automated training system that can guide users on when and how to collaborate with AI models effectively. The system, designed to adapt to multiple tasks, does this by training users using data from the interaction between the human and AI for a specific…

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The automated system instructs users on the appropriate times for cooperating 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 3, 202441Views0Likes0Comments
MIT and MIT-IBM Watson AI Lab researchers have developed an automated system that trains users to effectively collaborate with artificial intelligence (AI). The system, which is designed to be customized for different tasks, identifies the circumstances under which a user should pay attention to the AI's recommendations and describes these conditions in natural language. Initially,…

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The team from MIT publishes research reports on the regulation 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 3, 202440Views0Likes0Comments
A group of MIT leaders and scholars have released a series of policy briefs aimed at guiding U.S. policymakers in governing artificial intelligence (AI). The objective is to extend current regulatory and liability frameworks to cover AI, thereby limiting potential harm, and promoting social benefits resulting from its deployment. The central paper entitled “A Framework for…

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A computer science professional 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 3, 202438Views0Likes0Comments
Over 2000 years ago, Greek mathematician Euclid drastically influenced how we perceive shapes. Adding a modern facet to these ancient teachings, Justin Solomon is leveraging modern geometric methods to confront complex issues often unrelated to shapes. As an Associate Professor in the MIT Department of Electrical Engineering and Computer Science and a member of MIT’s…

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A computer engineer is pushing the limits in the field 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 3, 202440Views0Likes0Comments
Drawing influence from over 2,000 years ago, MIT Professor Justin Solomon is building upon the works of Greek mathematician Euclid - the father of geometry, using modern geometric techniques to tackle difficult problems, often not related to shapes. Solomon works in the Department of Electrical Engineering and Computer Science as part of the Computer Science…

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Bridging the gap between design and manufacturing for 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 3, 202437Views0Likes0Comments
Photolithography, a process used to etch features onto surfaces like computer chips and optical lenses, often results in devices that underperform due to tiny variations during manufacturing. To address this, researchers from MIT and the Chinese University of Hong Kong have employed machine learning to create a digital simulator that replicates a specific photolithography manufacturing…

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