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Implementing AI to aide individuals encountering challenges.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 10, 202441Views0Likes0Comments
In 2010, while studying at MIT Media Lab, Karthik Dinakar and Birago Jones developed a tool to assist in content moderation for social media platforms like Twitter and YouTube. The project, aimed at identifying concerning posts and potential cyberbullying, sparked enough interest to receive an invitation to a cyberbullying summit at the White House. However,…

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A new AI model has the potential to improve efficiency in automated warehouse processes.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, Robots, School of Engineering, UncategorizedJune 10, 202435Views0Likes0Comments
MIT researchers have designed an artificial intelligence solution to help robotic warehouses operate more efficiently. Automated warehouses, which employ hundreds of robots to pick and deliver goods, are becoming more commonplace, especially in industries such as e-commerce and automotive production. However, coordinating this robot workforce to avoid collisions, while also maintaining a high operational pace,…

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Interpreting Uncertainty: Guiding Through Ambiguity in LLM Responses

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 9, 202436Views0Likes0Comments
This paper delves into the realm of uncertainty quantification in large language models (LLMs), aiming to pinpoint scenarios where uncertainty in responses to queries is significant. The study delves into both epistemic and aleatoric uncertainties. Epistemic uncertainty arises from inadequate knowledge or data about reality, while aleatoric uncertainty originates from inherent randomness in prediction problems.…

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Google AI presents a machine learning structure for comprehending AI models in medical imagery.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 9, 202440Views0Likes0Comments
Machine learning (ML) has been instrumental in advancing healthcare, especially in the realm of medical imaging. However, current models often fall short in explaining how visual changes impact ML decisions, creating a need for transparent models that not only classify medical imagery accurately but also elucidate the signals and patterns they learn. Google's new framework,…

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ABodyBuilder3: An Expandable and Accurate Framework for Predicting the Structure of Antibodies

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 9, 202433Views0Likes0Comments
Researchers from Exscientia and the University of Oxford have developed an advanced predictive model called ABodyBuilder3 for antibody structures. This new tool is key for creating monoclonal antibodies, which are integral in immune responses and therapeutic applications. The novel model improves upon the previous ABodyBuilder2 by enhancing the accuracy of predicting Complementarity Determining Region (CDR)…

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Empowering individuals with challenges to harness the potential of AI.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 9, 202436Views0Likes0Comments
Founded by MIT graduates Karthik Dinakar and Birago Jones, Pienso is a platform that allows non-specialists to build machine-learning models to address societal issues. The idea stemmed from their 2010 study at MIT's Media Lab, where they developed a content moderation tool for companies like Twitter and YouTube. The innovation got companies excited and the…

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DiffUCO: An Unsupervised Neural Network Optimization Framework based on Diffusion Model

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 9, 202435Views0Likes0Comments
Sampling from complex and high-dimensional target models, like the Boltzmann distribution, is critical in various spheres of science. Often, these models have to handle Combinatorial Optimization (CO) problems, which deal with finding the best solutions from a vast pool of possibilities. Sampling in such scenarios can get intricate due to the inherent challenge of obtaining…

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Integrating AI into the processes utilized by individuals facing challenges.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 9, 202432Views0Likes0Comments
Karthik Dinakar and Birago Jones, both MIT graduates, developed a tool facilitating social media content moderation as part of a class project in 2010. The project generated significant interest and was demonstrated at a White House cyberbullying summit. However, they initially struggled with their demo due to their unfamiliarity with teenage slang used in harmful…

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A fresh AI model has the potential to enhance efficiency in an automated warehouse operation.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, Robots, School of Engineering, UncategorizedJune 9, 202439Views0Likes0Comments
In an enormous robotic warehouse, hundreds of robots zip back and forth, picking up items and delivering them to human workers for packing and shipping. This is becoming an increasingly common scene in various industries, from e-commerce to automotive manufacturing. However, managing these large numbers of robots, ensuring they reach their destinations effectively, and avoiding…

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Revealing Sequential Logic Analysis: Investigating Cyclic Algorithms in Language Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 8, 202442Views0Likes0Comments
Research conducted by institutions like FAIR, Meta AI, Datashape, and INRIA explores the emergence of Chain-of-Thought (CoT) reasoning in Language Learning Models (LLMs). CoT enhances the capabilities of LLMs, enabling them to perform complex reasoning tasks, even though they are not explicitly designed for it. Even as LLMs are primarily trained for next-token prediction, they…

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