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The new framework 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 1, 202465Views0Likes0Comments
Oral medications inevitably must travel through the digestive tract, with transporter proteins assisting this process. However, the exact transporter proteins used by numerous drugs remain unknown. Understanding these transporters could augment patient treatment significantly, given that drugs using the same transporter can disrupt each other's function and should not be co-administered. To solve this, researchers…

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Empowering individuals facing challenges 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 1, 202462Views0Likes0Comments
In 2010, Media Lab students Karthik Dinakar SM ’12, PhD ’17, and Birago Jones SM ’12 partnered for a class project aimed at developing a tool to assist content moderation teams at firms such as Twitter (now X) and YouTube. The widely acclaimed project led to an invitation to demonstrate their innovation at a cyberbullying…

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Comprehending AI System Prompts and the Impact of Zero-shot versus Few-shot Prompting in Artificial Intelligence

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 1, 202471Views0Likes0Comments
Within the world of Artificial Intelligence (AI), system prompts and the concepts of zero-shot and few-shot prompting have revolutionized the interaction between humans and Large Language Models (LLMs). These methods enhance the effectiveness and applicability of LLMs by guiding AI models to produce accurate and contextually appropriate responses. Essentially, system prompts serve as the initial instructions…

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Stanford scientists suggest SleepFM: A fresh comprehensive foundational model for sleep study.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Multimodal AI, Staff, Tech News, Technology, UncategorizedJune 1, 202465Views0Likes0Comments
Sleep medicine is a specialized field dedicated to the diagnosis of sleep disorders and the study of sleep patterns. Various techniques, such as polysomnography (PSG), which is a recording of brain, heart, and respiratory activities during sleep, allow medical professionals to have an in-depth understanding of a person's sleep health. Due to the complexity of sleep…

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This small, secure identification label can verify 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, 202471Views0Likes0Comments
Researchers at MIT have created a cryptographic ID tag that offers improved security over traditional radio frequency (RFID) tags. This enhanced tag incorporates the use of terahertz waves and unique glue patterns to authenticate products and prevent counterfeiting. It’s smaller in size, cheaper to produce, and more secure than traditional RFIDs. The ID tag could…

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Improving Self-Directed Learning through Automated Data Organization: A Multi-Level K-Means Method.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMay 31, 202459Views0Likes0Comments
Researchers from Meta's FAIR, INRIA, Université Paris Saclay, and Google are working on ways to automatically curate high-quality datasets to improve self-supervised learning (SSL). SSL enables models to be trained without human annotations, expanding data and model scalability, but its success often requires careful data curation. The team proposes a clustering-based technique involving hierarchical k-means…

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