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Deep neural networks demonstrate potential as a representation of human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 8, 202440Views0Likes0Comments
A team from the Massachusetts Institute of Technology (MIT) has found that machine learning (ML) models can effectively mimic and understand the human auditory system, potentially helping to improve technologies such as cochlear implants, hearing aids and brain-machine interfaces. These findings are based on the largest-ever study of deep neural networks used to perform auditory…

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LASP: A Streamlined Machine Learning Technique Specifically Designed for Linear Attention-Based Linguistic Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 8, 202436Views0Likes0Comments
Researchers from the Shanghai AI Laboratory and TapTap have developed a Linear Attention Sequence Parallel (LASP) technique that optimizes sequence parallelism on linear transformers, side-stepping the limitations led by the memory capacity of a single GPU. Large language models, due to their significant size and long sequences, can place a considerable strain on graphical unit…

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IsoBench: A Benchmark Dataset for Artificial Intelligence covering Four Broad Domains: Mathematics, Science, Algorithms, and Gaming.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 8, 202440Views0Likes0Comments
Large language models and multimodal foundation models like GPT4V, Claude, and Gemini, that blend visual encoders and language models, have made profound strides in the realms of Natural Language Processing (NLP) and Natural Language Generation (NLG). They show impressive performance when working with text-only inputs or a combination of image and text-based inputs. Nonetheless, queries…

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The system instructs users on determining the appropriate 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 8, 202439Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a system to teach users of artificial intelligence (AI) technology when they should or shouldn't trust its outcomes. This could be particularly beneficial in the medical field, where errors could have serious repercussions. The team created an automated system to teach a radiologist how…

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The team from MIT publishes research documents about managing 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, 202440Views0Likes0Comments
The Massachusetts Institute of Technology (MIT) committee of leaders and scholars have published a set of policy briefs to aid the development of a practical artificial intelligence governance framework for U.S. policymakers. Aiming to promote U.S. leadership in AI, the briefs also seek to limit potential harm from new technology and explore how AI deployment…

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A computer programmer breaks new ground 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 8, 202435Views0Likes0Comments
Greek mathematician Euclid revolutionized the concept of shapes over two millennia ago, laying a strong foundation for geometry. Justin Solomon, leveraging his ancient principles with modern geometric techniques, is solving complex issues unrelated to shapes. Solomon, an associate professor at MIT Department of Electrical Engineering and Computer Science (EECS) and a member 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 8, 202439Views0Likes0Comments
Photolithography is a commonly used manufacturing process that manipulates light to etch features onto surfaces, creating computer chips and optical devices like lenses. However, minute deviations in the process often result in these devices not matching their original designs. To bridge this design-manufacturing gap, a team from MIT and the Chinese University of Hong Kong…

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Human hearing can potentially be modeled efficiently using deep neural networks.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 8, 202440Views0Likes0Comments
MIT researchers have found that computational models derived from machine learning, designed to mimic the human auditory system, have the potential to improve hearing aids, cochlear implants, and brain-machine interfaces. They are moving closer to this goal by using these models in the largest study yet of deep neural networks trained to perform auditory tasks.…

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This research on Machine Learning presents a structure known as Mechanistic Architecture Design (MAD) pipeline, which integrates unit tests for small-scale capacities that can predict scaling laws.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 7, 202438Views0Likes0Comments
Deep learning architectures require substantial resources due to their vast design space, lengthy prototyping periods, and high computational costs related to large-scale model training and evaluation. Traditionally, improvements in architecture have come from heuristic and individual experience-driven development processes, as opposed to systematic procedures. This is further complicated by the combinatorial explosion of possible designs…

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Scientists at Microsoft AI suggest LLM-ABR: A newly developed machine learning system that uses LLMs for the creation of adaptive bitrate (ABR) algorithms.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 7, 202435Views0Likes0Comments
Large Language Models (LLMs) have become increasingly influential in many fields due to their ability to generate sophisticated text and code. Trained on extensive text databases, these models can translate user requests into code snippets, design specific functions, and even create whole projects from scratch. They have numerous applications, including generating heuristic greedy algorithms for…

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