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A review of MIT’s media presence in 2023

academics, Administration, Alumni/ae, Artificial Intelligence, astronomy and planetary science, Boston and region, Cambridge, Climate change, Community, Computer science and technology, Diversity and inclusion, Education, Faculty, Global, Government, Health sciences and technology, Innovation and Entrepreneurship (I&E), MIT Schwarzman College of Computing, MIT Sloan School of Management, Policy, President Sally Kornbluth, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Social justice, Space, Staff, Students, teaching, UncategorizedApril 27, 202477Views0Likes0Comments
In 2023, the Massachusetts Institute of Technology (MIT) had an eventful year, making remarkable advances in diverse areas from artificial intelligence to healthcare, climate change, and astrophysics. This included cutting-edge research such as inventing tools for earlier cancer detection and exploring the science behind spreading kindness. One of the highlights was Professor Moungi Bawendi winning the…

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The language network of the brain is put under more strain when dealing with intricate and unfamiliar phrases.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedApril 27, 202464Views0Likes0Comments
A new study by neuroscientists at MIT has uncovered what kind of sentences are most likely to stimulate the brain's main language processing centers. Utilizing an artificial language network, the researchers discovered that sentences with unusual grammar or unexpected meanings produce stronger responses in these areas; while straightforward sentences or nonsensical word sequences hardly engage…

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The brain’s language network is strained more when dealing with intricate and unfamiliar sentences.

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Language, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Neuroscience, Research, School of Engineering, School of Science, UncategorizedApril 27, 202460Views0Likes0Comments
MIT neuroscientists, using an artificial language network, have learned that more complex sentences, due to either odd grammar or unexpected meanings, trigger stronger responses in the brain's key language processing centers. On the other hand, plain sentences barely stimulate these regions, and nonsense word sequences have little effect on them. Evelina Fedorenko, an Associate Professor…

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Neural Flow Diffusion Models (NFDM): A Unique Machine Learning Structure that Improves Diffusion Models by Facilitating More Advanced Forward Processes Beyond the Standard Linear Gaussian

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 26, 202462Views0Likes0Comments
Generative models, a class of probabilistic machine learning, have seen extensive use in various fields, such as the visual and performing arts, medicine, and physics. These models are proficient in creating probability distributions that accurately describe datasets, making them ideal for generating synthetic datasets for training data and discovering latent structures and patterns in an…

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Improving the Scalability and Efficiency of AI Models: Research on the Multi-Head Mixture-of-Experts Approach

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 26, 202471Views0Likes0Comments
Large Language Models (LLMs) and Large Multi-modal Models (LMMs) are effective across various domains and tasks, but scaling up these models comes with significant computational costs and inference speed limitations. Sparse Mixtures of Experts (SMoE) can help to overcome these challenges by enabling model scalability while reducing computational costs. However, SMoE struggles with low expert…

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CATS (Contextually Aware Thresholding for Sparsity): An Innovative Machine Learning Structure for Triggering and Utilizing Activation Sparsity in LLMs.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 26, 202475Views0Likes0Comments
Large Language Models (LLMs), while transformative for many AI applications, necessitate high computational power, especially during inference phases. This poses significant operational costs and efficiency challenges as the models become bigger and more intricate. Particularly, the computational expenses incurred when running these models at the inference stage can be intensive due to their dense activation…

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Pegasus-1, a multimodal language model specializing in video content comprehension and interaction using natural language, has been unveiled by Twelve Labs.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedApril 26, 202461Views0Likes0Comments
Pegasus-1 is a state-of-the-art multimodal Large Language Model (LLM) developed by Twelve Labs and designed to interact with and comprehend video content through natural language. The model is intended to overcome the complexities of video data, including the consideration of multiple modalities in one format and the understanding of the sequence and timeline of visual…

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Pegasus-1, a multimodal language model proficient in video content comprehension and interaction via natural language, has been unveiled by Twelve Labs.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedApril 26, 202466Views0Likes0Comments
Large Language Models (LLMs) with video content is a challenging area of ongoing study, with a notable advancement in this field being Pegasus-1. This innovative multimodal model is designed to comprehend, synthesize, and interact with video data using natural language. MarkTech Post explains that the purpose of Pegasus-1's creation was to manage the inherent complexity of…

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An adaptable approach to assist animators in enhancing their artistry.

Algorithms, Artificial Intelligence, Arts, Augmented and virtual reality, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, UncategorizedApril 26, 202467Views0Likes0Comments
Researchers from MIT have developed a technique that provides animation artists greater flexibility and control over their characters. Their approach generates mathematical functions known as barycentric coordinates which define how 2D and 3D shapes can bend, stretch, and move. This change allows artists to choose functions that best suit their vision for their characters, offering…

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