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The Google AI team has introduced a machine learning method to enhance the reasoning capabilities of large language models (LLMs) when processing graphic data.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 19, 202439Views0Likes0Comments
A new study by Google is aiming to teach powerful large language models (LLMs) how to reason better with graph information. In computer science, the term 'graph' refers to the connections between entities - with nodes being the objects and edges being the links that signify their relationships. This type of information, which is inherent…

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A novel approach uses collective user feedback to assist in the training of robots.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robots, UncategorizedMarch 19, 202437Views0Likes0Comments
Researchers at MIT, Harvard, and the University of Washington have shunned traditional reinforcement learning approaches, using crowdsourced feedback to teach artificial intelligence (AI) new skills instead. Traditional methods to teach AI tasks often required a reward function, which was updated and managed by a human expert. This limited scalability and was often time-consuming, particularly if…

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What does the future entail for generative AI?

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, School of Engineering, Special events and guest speakers, Staff, Students, UncategorizedMarch 19, 202436Views0Likes0Comments
During the kickoff event of MIT’s Generative AI Week, the “Generative AI: Shaping the Future” symposium, Rodney Brooks, co-founder of iRobot, cautioned attendees about the dangers of overestimating the capabilities of generative AI technology. Brooks, also a professor emeritus at MIT and former director of the Computer Science and Artificial Intelligence Laboratory (CSAIL), warned that…

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A collaborative team of researchers from Harvard and MIT have created UNITS: A Comprehensive Machine Learning Model for Time Series Analysis. This innovative model enables a general task specification across a wide range of tasks.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 19, 202438Views0Likes0Comments
Time-series analysis is indispensable within numerous fields such as healthcare, finance, and environmental monitoring. However, the diversity of time series data, marked by differing lengths, dimensions, and task requirements, brings about significant challenges. In the past, dealing with these datasets necessitated the creation of specific models for each individual analysis need, which was effective but…

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This Machine Learning study by ServiceNow suggests WorkArena and BrowserGym: Steps forward in streamlining everyday workflows using AI.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 19, 202428Views0Likes0Comments
In the modern digital age, individuals often interact with technology through software interfaces. Even with advancements towards user-friendly designs, many still struggle with the complexity of repetitive tasks. This creates an obstacle to efficiency and inclusivity within the digital workspace, underlining the necessity for innovative solutions to streamline these interactions, thereby making technology more intuitive…

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Five professors from MIT tackle Major Cancer Challenges

Artificial Intelligence, Awards, Biological engineering, Biology, Cancer, Chemical engineering, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, honors and fellowships, Immunology, Jameel Clinic, Koch Institute, Machine learning, Research, School of Engineering, School of Science, UncategorizedMarch 19, 202438Views0Likes0Comments
Five MIT researchers—Michael Birnbaum, Regina Barzilay, Brandon DeKosky, Seychelle Vos, and Ömer Yilmaz—are part of winning teams for Cancer Grand Challenges 2024. Each team, made up of international, interdisciplinary cancer researchers, will receive $25 million over five years. Associate Professor of Biological Engineering Michael Birnbaum is heading Team MATCHMAKERS, comprised of co-investigators Regina Barzilay (Engineering Distinguished…

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New algorithm delivers detailed understanding for computer vision.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Imaging, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 19, 202437Views0Likes0Comments
MIT researchers have developed an algorithm called FeatUp that enables computer vision algorithms to capture both high-level details and fine-grained minutiae of a scene simultaneously. Modern computer vision algorithms, like human beings, can only recall the broad details of a scene while the more nuanced specifics are often lost. To understand an image, they break…

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GENAUDIT: An AI-Based Instrument Assisting Users in Validating Facts and Comparing Machine-Learned Outputs with Evidence-Backed Inputs

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 18, 202439Views0Likes0Comments
Recent developments in Artificial Intelligence (AI), particularly in Generative AI, have proven the capacities of Large Language Models (LLMs) to generate human-like text in response to prompts. These models are proficient in tasks such as answering questions, summarizing long paragraphs, and more. However, even provided with reference materials, they can generate errors which could have…

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This Artificial Intelligence study introduces ScatterMoE, a GPU-based application of Sparse Mixture-of-Experts (SMoE) in Machine Learning.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 18, 202432Views0Likes0Comments
The Sparse Mixture of Experts (SMoEs) has become popular as a method of scaling models, particularly in memory-restricted environments. They are crucial to the Switch Transformer and Universal Transformers, providing efficient training and inference. However, some limitations exist with current implementations of SMoEs, such as a lack of GPU parallelism and complications related to tensor…

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This article presents AQLM, a machine learning procedure that aids in the significant reduction of sizable language models through additive quantization.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 18, 202434Views0Likes0Comments
The development of effective large language models (LLMs) remains a complex problem in the realm of artificial intelligence due to the challenge of balancing size and computational efficiency. Minimizing these issue, a strategy called Additive Quantization for Language Models (AQLM) has been introduced by researchers from institutions such as HSE University, Yandex Research, Skoltech, IST…

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Stanford University researchers demonstrate ‘pyvene’: a freely accessible Python library that promotes intervention-oriented studies on Machine Learning Models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 17, 202441Views0Likes0Comments
Stanford University researchers are pushing the boundaries of artificial intelligence (AI) with the introduction of "pyvene," an innovative, open-source Python library designed to advance intervention-based research on machine learning models. As AI technology evolves, so does the need to refine and understand these advancement's underlying processes. Pyvene is an answer to this demand, propelling forward…

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COULER: An Artificial Intelligence Framework Developed for Streamlined Machine Learning Workflow Enhancement in Cloud Computing.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 17, 202433Views0Likes0Comments
Machine learning (ML) workflows have become increasingly complex and extensive, prompting a need for innovative optimization approaches. These workflows, vital for many organizations, require vast resources and time, driving up operational costs as they adjust to various data infrastructures. Handling these workflows involved dealing with a multitude of different workflow engines, each with their own…

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