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This small microchip can protect user information and simultaneously promote efficient processing on a mobile phone.

Artificial Intelligence, Computer science and technology, Cybersecurity, Data, Electrical Engineering & Computer Science (eecs), Electronics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedAugust 6, 202474Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that can resist the two most common types of cyberattacks while maintaining the functionality of large Artificial Intelligence (AI) models, according to senior author Anantha Chandrakasan, MIT’s chief innovation and strategy officer, dean of the School of Engineering, and the Vannevar…

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Julie Shah has been appointed as the lead of the Aeronautics and Astronautics Department.

Administration, Aeronautical and astronautical engineering, Alumni/ae, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Electrical Engineering & Computer Science (eecs), Faculty, Leadership, MIT Schwarzman College of Computing, Robotics, School of Engineering, UncategorizedAugust 6, 202435Views0Likes0Comments
Julie Shah has been named the new head of the Department of Aeronautics and Astronautics (AeroAstro) at the Massachusetts Institute of Technology (MIT) as of May 1st. Shah is recognized for her visionary contributions to the fields of robotics and artificial intelligence. She currently heads the Interactive Robotics Group in MIT's Computer Science and Artificial…

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A dataset based on AI paves the way for innovative tornado detection methods.

Algorithms, Artificial Intelligence, Climate change, Data, Disaster response, Lincoln Laboratory, Machine learning, Natural disasters, Radar, Research, Technology and society, Uncategorized, Weather, Weather modelingAugust 6, 202438Views0Likes0Comments
Researchers at MIT Lincoln Laboratory have introduced an open-source dataset called TorNet in an attempt to enable enhanced detection and prediction of tornadoes. The dataset comprises radar returns from thousands of tornadoes that struck the US over the past decade and includes copies of storms that generated tornadoes as well as other extreme weather events…

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Speedier LLMs through theoretical deciphering and AWS Inferentia2.

AI/ML, Amazon Machine Learning, Artificial Intelligence, AWS Inferentia, Generative AI, Machine learning, Technical How-to, UncategorizedAugust 6, 202436Views0Likes0Comments
Large language models (LLMs), used to solve natural language processing (NLP) tasks, have seen a significant increase in their size. This increase dramatically improves the model's performance, with larger models scoring better on tasks such as reading comprehension. However, these larger models require more computation and are more costly to deploy. The role of larger models…

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Protein Annotation-Enhanced Depictions (PAIR): A Versatile Refinement System Using a Text Decoder to Direct the Precision Adjustment Operation of the Encoder

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedAugust 5, 202435Views0Likes0Comments
Researchers from the University of Toronto and the Vector Institute have developed an advanced framework for protein language models (PLMs), called Protein Annotation-Improved Representations (PAIR). This framework enhances the ability of models to predict amino acid sequences and generate feature vectors representing proteins, proving particularly useful in predicting protein folding and mutation effects. PLMs traditionally make…

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LlamaIndex Processes: A Stimulus-Based Strategy for Managing Intricate AI Applications

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedAugust 5, 202439Views0Likes0Comments
Artificial intelligence (AI) applications are becoming increasingly complicated, involving multiple interactive tasks and components that must be coordinated for effective and efficient performance. Traditional methods of managing this complex orchestration, such as Directed Acyclic Graphs (DAGs) and query pipelines, often fall short in dynamic and iterative processes. To overcome these limitations, LlamaIndex has introduced…

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CC-SAM: Attaining Exceptional Medical Image Segmentation with a Dice Score of 85.20 and a Hausdorff Distance of 27.10 through the Combined Use of Convolutional Neural Network (CNN) and Vision Transformer (ViT)

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedAugust 5, 202434Views0Likes0Comments
Medical image segmentation, the identification, and outlining of anatomical structures within medical scans, plays a crucial role in the accurate diagnosis, treatment planning, and monitoring of diseases. Recent advances in deep learning models such as U-NET, extensions of U-NET, and the Segment Anything Model (SAM) have significantly improved the accuracy and efficiency of medical image…

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11 Diverse Applications of Meta’s SAM 2 Model: Segment Anything Model 2

AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Object Detection, Staff, Tech News, Technology, UncategorizedAugust 5, 202436Views0Likes0Comments
Meta’s Segment Anything Model 2 (SAM 2) is a cutting-edge AI tool that has taken the tech world by storm, owing to its novel functionality in promptable object segmentation in images and videos in real-time. This unified model, complete with advanced speed and adaptability, is set to be a game-changer across various industries. The discussion…

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Safety Standards for AI May Not Guarantee Real Safety: This AI Study Uncovers the Concealed Dangers of Overstating Safety Measures

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedAugust 5, 202436Views0Likes0Comments
Artificial Intelligence (AI) safety continues to become an increasing concern as AI systems become more powerful. This has led to AI safety research aiming to address the imminent and future risks through the development of benchmarks to measure safety properties such as fairness, reliability, and robustness. However, these benchmarks are not always clear in defining…

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ARCLE: An Abstract Reasoning Challenge Platform Utilizing Reinforcement Learning Environment

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedAugust 5, 202435Views0Likes0Comments
As an area of Artificial Intelligence (AI), Reinforcement Learning (RL) enables agents to learn by interacting with their environment and making decisions that maximize their cumulative rewards over time. This learning approach is especially useful in robotics and autonomous systems due to its focus on trial and error learning. However, RL faces challenges in situations…

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