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Deep neural networks exhibit potential in mimicking the human auditory system.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 5, 202442Views0Likes0Comments
Researchers at MIT have discovered that computational models derived from machine learning are increasingly mimicking the function and structure of the human auditory system. This finding has significant implications for the design of more effective hearing aids, cochlear implants, and brain-machine interfaces. In the most extensive study to date of deep neural networks used for…

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Deep neural networks demonstrate potential in replicating the human auditory system.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 4, 202434Views0Likes0Comments
Modern machine learning models are becoming increasingly adept at simulating the structure and function of the human auditory system, a development that could lead to improvements in devices like hearing aids, cochlear implants, and brain-machine interfaces. A team at MIT conducted what is considered the largest study of deep neural networks trained for auditory tasks…

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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, 202439Views0Likes0Comments
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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Promising signs are exhibited by deep neural networks in their potential of modeling human hearing.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 3, 202434Views0Likes0Comments
In the largest study of deep neural networks that can perform auditory tasks, MIT found that the models mimic human auditory representations when exposed to the same sounds. Neural networks are models that have multiple layers of information-processing units that can be trained to perform particular tasks using large amounts of data. These models are…

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MIT researchers investigating the influence and uses of generative AI have received the second installment of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedApril 3, 202443Views0Likes0Comments
Last summer, MIT called upon the academic community to provide papers that suggest effective approaches and policy recommendations in the field of generative AI. Expectations were surpassed when 75 proposals were received. After reviewing these submissions, the institution funded 27 of the proposed projects. During the fall, the response to a second call for proposals…

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A novel computational method may simplify the process of engineering beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedApril 3, 202434Views0Likes0Comments

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Five professors from MIT tackle Major Cancer Challenges

Artificial Intelligence, Awards, Biological engineering, Biology, Cancer, Chemical engineering, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, honors and fellowships, Immunology, Jameel Clinic, Koch Institute, Machine learning, Research, School of Engineering, School of Science, UncategorizedMarch 19, 202438Views0Likes0Comments
Five MIT researchers—Michael Birnbaum, Regina Barzilay, Brandon DeKosky, Seychelle Vos, and Ömer Yilmaz—are part of winning teams for Cancer Grand Challenges 2024. Each team, made up of international, interdisciplinary cancer researchers, will receive $25 million over five years. Associate Professor of Biological Engineering Michael Birnbaum is heading Team MATCHMAKERS, comprised of co-investigators Regina Barzilay (Engineering Distinguished…

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The search algorithm uncovers almost 200 novel types of CRISPR systems.

Algorithms, Artificial Intelligence, Bacteria, Biological engineering, Biology, Brain and cognitive sciences, Broad Institute, Computational biology, Computer science and technology, CRISPR, Data, DNA, Genetic engineering, Genome, Genome editing, McGovern Institute, Microbes, National Institutes of Health (NIH), Research, RNA, School of Engineering, School of Science, UncategorizedMarch 18, 202448Views0Likes0Comments

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The search algorithm has uncovered almost 200 new types of CRISPR systems.

Algorithms, Artificial Intelligence, Bacteria, Biological engineering, Biology, Brain and cognitive sciences, Broad Institute, Computational biology, Computer science and technology, CRISPR, Data, DNA, Genetic engineering, Genome, Genome editing, McGovern Institute, Microbes, National Institutes of Health (NIH), Research, RNA, School of Engineering, School of Science, UncategorizedMarch 18, 202440Views0Likes0Comments
Scientists from the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information at the National Institutes of Health, have developed a new search algorithm to find enzymes of interest in vast microbial sequence databases. This algorithm, called Fast Locality-Sensitive Hashing-based clustering (FLSHclust), discovered…

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Nearly 200 new types of CRISPR systems have been identified via a search algorithm.

Algorithms, Artificial Intelligence, Bacteria, Biological engineering, Biology, Brain and cognitive sciences, Broad Institute, Computational biology, Computer science and technology, CRISPR, Data, DNA, Genetic engineering, Genome, Genome editing, McGovern Institute, Microbes, National Institutes of Health (NIH), Research, RNA, School of Engineering, School of Science, UncategorizedMarch 17, 202441Views0Likes0Comments
Researchers at MIT, Harvard, and the National Institutes of Health have utilized a new search algorithm to identify 188 different types of rare CRISPR systems in bacterial genomes. This data holds potential to advance genome-editing technology, enabling more precise treatments and diagnostics. The algorithm, developed in the lab of prominent CRISPR researcher, Professor Feng Zhang uses…

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The search algorithm uncovers almost 200 novel types of CRISPR systems.

Algorithms, Artificial Intelligence, Bacteria, Biological engineering, Biology, Brain and cognitive sciences, Broad Institute, Computational biology, Computer science and technology, CRISPR, Data, DNA, Genetic engineering, Genome, Genome editing, McGovern Institute, Microbes, National Institutes of Health (NIH), Research, RNA, School of Engineering, School of Science, UncategorizedMarch 17, 202433Views0Likes0Comments
Scientists from the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information at the National Institutes of Health have developed a new algorithm that can sift through massive amounts of genomic data to identify unique CRISPR systems. Known as Fast Locality-Sensitive Hashing-based clustering…

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Scientists improve the side vision abilities in AI systems.

Artificial Intelligence, Autonomous vehicles, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, UncategorizedMarch 9, 202443Views0Likes0Comments
Researchers at MIT have developed an image dataset that simulates peripheral vision for use in training machine learning (ML) models, an area where artificial intelligence (AI) notably diverges from human ability. Humans leverage less-detailed peripheral vision to detect shapes and items outside their direct line of sight, an ability AI lacks. Incorporating aspects of peripheral…

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