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Empowering individuals who have issues to resolve by providing them 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, UncategorizedMay 27, 202430Views0Likes0Comments
In 2010, Karthik Dinakar and Birago Jones began a project to develop a tool helping content moderation teams at companies like Twitter and YouTube. The aim was to assist these teams in identifying inappropriate or harmful content. The project created considerable interest and the researchers were invited to present their work at a cyberbullying summit…

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Google AI suggests LANISTR: A Machine Learning Framework that leverages attention-based mechanisms to learn from Language, Image, and Structured Data.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMay 27, 202437Views0Likes0Comments
Google Cloud AI researchers have unveiled a novel pre-training framework called LANISTR, designed to effectively and efficiently manage both structured and unstructured data. LANISTR, which stands for Language, Image, and Structured Data Transformer, addresses a key issue in machine learning; the handling of multimodal data, such as language, images, and structured data, specifically when certain…

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Premium Courses for Learning Algorithms and Data Structures

Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedMay 27, 202435Views0Likes0Comments
Data structures and algorithms are integral tools in creating effective, efficient, and reliable software. By studying them, programmers can enhance their coding abilities and gear up for technical interviews and complex real-world tasks. The following list details the best tutorials on data structures and algorithms to help you thrive in software development and interviews. 1. "Foundations…

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Assessing Anomaly Detection in Time Series: Awareness of Proximity in Time Series Anomaly Assessment (PATE)

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMay 27, 202441Views0Likes0Comments
Anomaly detection in time series data, which is pivotal for practical applications like monitoring industrial systems and detecting fraudulent activities, has been facing challenges in terms of its metrics. Existing measures such as Precision and Recall, designed for independent and identically distributed (iid) data, fail to entirely capture anomalies, potentially leading to flawed evaluations in…

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A Comprehensive Overview of Progress in the Claude Models Family by Anthropic AI

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 27, 202431Views0Likes0Comments
Anthropic AI's Claude family of models signifies a massive milestone in anomaly detection AI technology. The release of the Claude 3 series has seen a significant expansion in the models' abilities and performance, making them suitable for a broad spectrum of applications that span from text generation to high-level vision processing. This article aims to…

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A novel method allows AI chatbots to engage in conversations throughout the day without experiencing system failures.

Algorithms, Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMay 27, 202438Views0Likes0Comments
A group of researchers from MIT and other institutions have pinpointed a key issue that causes performance degradation in AI chatbots during long conversations and have developed a simple solution to rectify it. Large language machine-learning models such as the ChatGPT use key-value cache to store data. However, when the cache needs to hold more…

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This small, secure identification label has the ability to 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, UncategorizedMay 27, 202439Views0Likes0Comments
Researchers at MIT have developed a highly advanced anti-tampering ID tag that is significantly smaller and cheaper than traditional Radio Frequency Identification (RFID) tags. It leverages the power of terahertz waves to improve upon conventional security tools and offers an innovative solution to safeguard items from counterfeit. Traditional security tags, much like this one, use radio…

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The new design recognizes medications that are incompatible when taken concurrently.

Artificial Intelligence, Computer science and technology, Drug delivery, Machine learning, Mechanical engineering, Medicine, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedMay 27, 202433Views0Likes0Comments
Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a research approach to identify how different drugs exit the digestive tract. The method uses tissue models and machine-learning algorithms to understand which transporters are used by drugs, revealing how a commonly prescribed antibiotic and blood thinners can interfere with each other. Transporter…

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Implementing AI for individuals who are seeking solutions to their issues.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedMay 27, 202434Views0Likes0Comments
In 2010, Karthik Dinakar and Birago Jones, while working on a class project at Media Lab, developed a tool targeting content moderation for social media. The project, aimed at identifying harmful posts on platforms such as Twitter and YouTube, landed them a presentation at a White House cyberbullying summit. They realized before the event, however,…

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A Change in Perspective: MoRA’s Contribution to Promoting Techniques for Fine-Tuning Parameters Efficiently

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 26, 202432Views0Likes0Comments
Large language models (LLMs) are renowned for their ability to perform specific tasks due to the principle of fine-tuning their parameters. Full Fine-Tuning (FFT) involves updating all parameters, while Parameter-Efficient Fine-Tuning (PEFT) techniques such as Low-Rank Adaptation (LoRA) update only a small subset, thus reducing memory requirements. LoRA operates by utilizing low-rank matrices, enhancing performance…

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Going Beyond the Frequency Approach: AoR Assesses Logic Sequences for Precise LLM Resolutions

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 26, 202433Views0Likes0Comments
The field of Natural Language Processing (NLP) has seen a significant advancement thanks to Large Language Models (LLMs) that are capable of understanding and generating human-like text. This technological progression has revolutionized applications such as machine translation and complex reasoning tasks, and sparked new research and development opportunities. However, a notable challenge has been the…

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EleutherAI Introduces lm-eval, a Language Model Evaluation Framework for Consistent and Strict NLP Evaluations, which Improves Assessment of Language Models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMay 26, 202437Views0Likes0Comments
Language models are integral to the study of natural language processing (NLP), a field that aims to generate and understand human language. Applications such as machine translation, text summarization, and conversational agents rely heavily on these models. However, effectively assessing these approaches remains a challenge in the NLP community due to their sensitivity to differing…

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