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The new framework identifies medications that should not be concurrently administered.

Artificial Intelligence, Computer science and technology, Drug delivery, Machine learning, Mechanical engineering, Medicine, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJune 2, 202460Views0Likes0Comments
Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a strategy to understand how orally ingested drugs exit the digestive tract. The process relies on transporter proteins found in the lining of the digestive tract. Identifying the specific transporters used by various drugs can help avoid potential complications when two drugs using…

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Providing individuals facing challenges with access to artificial intelligence.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 2, 202462Views0Likes0Comments
In 2010, Karthik Dinakar and Birago Jones began a project while at MIT's Media Lab, aiming to build a tool to aid content moderation teams at companies like Twitter and YouTube. This tool aimed to identify concerning posts, but the creators struggled to comprehend the slang and indirect language commonly used by posters. This led…

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This AI research conducted by Princeton and the University of Warwick suggests an innovative AI method to improve the use of LLMs as cognitive models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202464Views0Likes0Comments
Large Language Models (LLMs) often exhibit judgment and decision-making patterns that resemble those of humans, posing them as attractive candidates for studying human cognition. They not only emulate rational norms such as risk and loss aversion, but also showcase human-like errors and biases, particularly in probability judgments and arithmetic operations. Despite their potential prospects, challenges…

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Flexible Architectural Neural Networks: Employing AI Solutions to Address Symmetric Issues in Optimization of Units and Common Parameters

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202456Views0Likes0Comments
Researchers from IT University Copenhagen, Denmark have proposed a new approach to solve a challenge with deep neural networks (DNNs) known as the Symmetry Dilemma. This issue arises because standard DNNs have a fixed structure tied to specific dimensions of input and output space. This rigid structure makes it difficult to optimize these networks across…

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Adaptive Visual Tokenization in Matryoshka Multimodal Models: Boosting Efficacy and Versatility in Multimodal Machine Learning

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202467Views0Likes0Comments
Multimodal machine learning combines various data types such as text, images, and audio to create more accurate and comprehensive models. However, large multimodal models (LMMs), like LLaVA, have been facing problems dealing with high-resolution graphics due to their inflexible and inefficient nature. Many have recognized the necessity for methods that may adjust the number of…

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RobustRAG: An Exclusive Protective Structure Designed to Counteract Retrieval Pollution Attacks within Retrieval-Augmented Generation (RAG) Systems.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 2, 202471Views0Likes0Comments
Retrieval-augmented generation (RAG) has been used to enhance the capabilities of large language models (LLMs) by incorporating external knowledge. However, RAG is susceptible to retrieval corruption, a type of attack in which disruptive information is inserted into the document collection, leading to the generation of incorrect or misleading responses. This poses a serious threat to…

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This small, secure identification label has the ability to verify almost anything.

Artificial Intelligence, Computer chips, Computer science and technology, Electrical Engineering & Computer Science (eecs), Electronics, Internet of things, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Research Laboratory of Electronics, School of Engineering, Sensors, Supply chains, UncategorizedJune 2, 202469Views0Likes0Comments
The ability to confirm the authenticity of products has become a paramount need in our world today, especially with the rise of counterfeiting. The most common method often used is radio frequency tags or RFIDs, which confirms the authenticity of a product but at a size and cost disadvantage. However, a new research by the…

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The new system recognizes medications that should not be combined.

Artificial Intelligence, Computer science and technology, Drug delivery, Machine learning, Mechanical engineering, Medicine, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJune 2, 202462Views0Likes0Comments
Oral medications must traverse the lining of the digestive tract through a process facilitated by proteins found in the cells lining the gastrointestinal tract. Researchers at MIT, Duke University, and Brigham and Women's Hospital have developed a new strategy to identify these proteins (transporters) utilized by individual drugs. This knowledge could enhance patient treatment, as…

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Empowering individuals who have issues to resolve with the use of Artificial Intelligence.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 2, 202460Views0Likes0Comments
In 2010, Karthik Dinakar SM ’12, PhD ’17 and Birago Jones SM ’12, Media Lab students at MIT, collaborated on a class project to design a practical tool for content moderation at companies such as Twitter and YouTube. This groundbreaking project garnered substantial excitement, leading to an invitation to present a demonstration at a cyberbullying…

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MoEUT: A Durable Machine Learning Method to Tackle Efficiency Issues in Universal Transformers

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 1, 202463Views0Likes0Comments
Universal Transformers (UTs) are key in machine learning applications such as language models and image processors, but they suffer from efficiency issues. Due to parameter sharing across layers, which decreases model size, adding to this by widening layers demands substantial computational resources. Consequently, UTs are not ideal for tasks which require heavy parameters, such as…

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This small, secure ID label has the capability to validate nearly everything.

Artificial Intelligence, Computer chips, Computer science and technology, Electrical Engineering & Computer Science (eecs), Electronics, Internet of things, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Research Laboratory of Electronics, School of Engineering, Sensors, Supply chains, UncategorizedJune 1, 202468Views0Likes0Comments
MIT researchers have advanced their previously developed cryptographic ID tag that uses terahertz waves instead of radio frequency (RFID) technology, to bolster its security and undermine counterfeiting efforts. The initial model of their tag had a major flaw in that it could be peeled off a genuine item and reattached to a counterfeit, thereby tricking…

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