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The automated system instructs users on appropriate timings for collaboration with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedMarch 7, 202434Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed an onboarding process that efficiently combines human and AI efforts. The system educates a user when to collaborate with an AI assistant and when not. This method can find situations when a user trusts the AI model's advice, but the model is incorrect. The…

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MIT team publishes research papers on the management of AI.

Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Government, Machine learning, MIT Schwarzman College of Computing, Policy, School of Engineering, Technology and society, UncategorizedMarch 7, 202435Views0Likes0Comments
A committee of leaders and scholars from the Massachusetts Institute of Technology (MIT) has released a series of policy papers providing a regulatory framework for artificial intelligence (AI). The goal is to enable the US to maintain its leadership position in AI, preventing potential harm from novel technologies and promoting their societal benefits. The central…

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MIT’s Generative AI Week promotes conversation among different fields.

academics, Algorithms, Architecture, Artificial Intelligence, Biology, Civil and environmental engineering, Comparative Media Studies/Writing, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, DMSE, EAPS, Education, Electrical Engineering & Computer Science (eecs), Ethics, Faculty, Health, Laboratory for Information and Decision Systems (LIDS), Machine learning, Media Lab, MIT Morningside Academy for Design, MIT Schwarzman College of Computing, MIT Sloan School of Management, Robotics, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Special events and guest speakers, Staff, Students, teaching, Technology and society, UncategorizedMarch 7, 202441Views0Likes0Comments
In late November, Massachusetts Institute of Technology (MIT) held a Generative AI Week involving faculty, staff, and students from the institution. The event served as a platform to discuss the opportunities and important applications of generative artificial intelligence technologies across varied disciplines. The week's agenda included a main symposium and four subject-specific symposia. MIT President…

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A technology expert in computing is extending the limits of geometrical studies.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, MIT Schwarzman College of Computing, Profile, School of Engineering, UncategorizedMarch 7, 202434Views0Likes0Comments
Justin Solomon, an associate professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), is making use of modern geometric techniques to address intricate problems, many of which don't appear to be linked to shapes. He extrapolates from the foundations laid more than 2,000 years ago by the…

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Three students from MIT have been chosen as the first fellows for the MIT-Pillar AI Collective.

Artificial Intelligence, Awards, Computer science and technology, Data, Deshpande Center, Electrical Engineering & Computer Science (eecs), Graduate, Harvard-MIT Health Sciences and Technology, honors and fellowships, Innovation and Entrepreneurship (I&E), Machine learning, postdoctoral, School of Engineering, Students, UncategorizedMarch 7, 202440Views0Likes0Comments
The MIT-Pillar AI Collective has selected Alexander Andonian, Daniel Magley, and Madhumitha Ravichandra as its three inaugural fellows for the fall 2023 semester. All are on the cusp of concluding a master’s or PhD program and will aid in conducting research in artificial intelligence (AI), machine learning, and data science, backed by the program. The…

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The unseen hurdle of today’s AI: Accuracy in image identification.

Artificial Intelligence, Center for Brains Minds and Machines, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Data, Electrical Engineering & Computer Science (eecs), Image Processing, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, Uncategorized, VisionMarch 7, 202444Views0Likes0Comments
MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers, in collaboration with the MIT-IBM Watson AI Lab, have developed a new metric, the "minimum viewing time" (MVT), to measure the difficulty of recognizing an image. The researchers aimed to close the gap between the performance of deep learning-based AI models and humans in recognizing and…

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A versatile approach to assist artists in enhancing animation.

Algorithms, Artificial Intelligence, Arts, Augmented and virtual reality, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, UncategorizedMarch 7, 202437Views0Likes0Comments
MIT researchers have developed a new tool that provides better control to animators in shaping their characters. The new technique works by generating mathematical functions, known as barycentric coordinates, that describe how 2D and 3D shapes in animations can move, stretch, and deform in space. By using these functions, an animator can tailor the movement…

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Utilizing language to comprehend machines.

Artificial Intelligence, Classes and programs, Collaboration, Data, Electrical Engineering & Computer Science (eecs), Graduate, Human-computer interaction, Industry, Linguistics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Natural language processing, postdoctoral, Research, School of Engineering, School of Humanities Arts and Social Sciences, Students, UncategorizedMarch 7, 202441Views0Likes0Comments
MIT engineering students Irene Terpstra ’23 and Rujul Gandhi ’22 are collaborating with the MIT-IBM Watson AI Lab to advance Artificial Intelligence (AI) systems using Natural Language Processing (NLP), taking advantage of the vast amount of natural language data available. Terpstra is focusing on the application of AI algorithms for computer chip design, leveraging the…

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AI representatives assist in elucidating other AI frameworks.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedMarch 7, 202437Views0Likes0Comments
Interpreting the functions and behaviors of large-scale neural networks remains a complex task and a significant challenge in the field of Artificial Intelligence. To tackle this problem, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a strategy that uses AI models to investigate the computations inside other AI systems.  Central to this…

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Numerous AI systems assist robots in carrying out intricate strategies with greater clarity.

Algorithms, Artificial Intelligence, Computer science and technology, Computer vision, Data, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, Robotics, School of Engineering, UncategorizedMarch 7, 202437Views0Likes0Comments
MIT's Improbable AI Lab has developed a novel multimodal framework for artificial intelligence (AI) called the Compositional Foundation Models for Hierarchical Planning (HiP). The aim of this system is to help robots conduct complex tasks that involve numerous smaller steps, from household chores to more elaborate industrial processes. Traditionally, AI systems have required paired visual,…

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Safety Guidelines in the Stratosphere: The Potential Influence of Aviation on Regulating Health-based AI Systems

Aeronautical and astronautical engineering, Artificial Intelligence, Aviation, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Digital technology, Electrical Engineering & Computer Science (eecs), Ethics, Health care, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Machine learning, MIT Schwarzman College of Computing, School of Engineering, Technology and policy, Technology and society, UncategorizedMarch 7, 202437Views0Likes0Comments
A 2022 report from the International Air Transport Association revealed that the odds of dying in a plane crash are extremely low, with an industry fatality risk of 0.11. This implies that a person would need to fly daily for over 25,000 years to have a 100% chance of experiencing a fatal accident, underscoring why…

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Logical thinking and dependability in Artificial Intelligence

Artificial Intelligence, Communications, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Graduate, Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Natural language processing, postdoctoral, Research, Robotics, School of Engineering, Students, UncategorizedMarch 7, 202443Views0Likes0Comments
MIT PhD students interning at the MIT-IBM Watson AI Lab are researching ways to improve the efficiency and accuracy of AI systems in understanding and communicating through natural language. The team, including Athul Paul Jacob, Maohao Shen, Victor Butoi, and Andi Peng, aims to enhance each stage of the process involving natural language models, from…

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