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It is more challenging for physicians to identify diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMarch 7, 202464Views0Likes0Comments
AI technology could help improve doctors' accuracy when diagnosing skin diseases in individuals with darker skin, scientists from the Massachusetts Institute of Technology have found. The study involved over 1,000 dermatologists and general practitioners, with dermatologists correctly identifying roughly 38% of skin conditions seen in images, but this figure dropped to 34% where patients had…

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The role of symmetry in assisting machine learning processes.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), IDSS, Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedMarch 7, 202469Views0Likes0Comments
In 2021, while studying differential equations, MIT PhD student Behrooz Tahmasebi discovered a possible connection between Weyl’s law — a mathematical formula used to measure the complexity of data contained within frequencies such as a drum or guitar string — and computer science. He hypothesized that the application of a specific version of the law…

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Six students from MIT have been chosen as fellows for the MIT-Pillar AI Collective in the spring of 2024.

Artificial Intelligence, Awards, Data, Deshpande Center, Electrical Engineering & Computer Science (eecs), Graduate, honors and fellowships, Innovation and Entrepreneurship (I&E), Machine learning, Mechanical engineering, postdoctoral, Robotics, School of Engineering, Startups, Students, UncategorizedMarch 7, 202471Views0Likes0Comments
The MIT-Pillar AI Collective, a partnership between the Massachusetts Institute of Technology's (MIT) School of Engineering and Pillar VC, has named six fellows for the spring 2024 semester. Each fellow is a graduate student in their final year of a master's or PhD program who will conduct research in the fields of AI, machine learning,…

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Enhanced safety in the sky with autonomous helicopters.

Aeronautical and astronautical engineering, Aircraft, Alumni/ae, Artificial Intelligence, Autonomous vehicles, Graduate, Innovation and Entrepreneurship (I&E), postdoctoral, School of Engineering, Startups, Transportation, Uncategorized, Venture Mentoring ServiceMarch 7, 202472Views0Likes0Comments
In 2019, after years of studying aviation and aerospace engineering, Hector (Haofeng) Xu decided to learn how to fly helicopters. While pursuing his PhD in MIT’s Department of Aeronautics and Astronautics, Xu experienced the inherent risks of flying small aircrafts firsthand and was inspired to make helicopter flights safer. In 2021, he established his company…

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An innovative method enables AI chatbots to engage in conversation continuously without any system breakdowns.

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, UncategorizedMarch 7, 202469Views0Likes0Comments
Researchers from MIT and other institutions have developed a method to prevent AI chatbots from failing during extensive conversations. The team's solution centres on the key-value cache (KV Cache), or the chatbot's memory, within language models. Existing models often fail when the cache is overloaded with information, as incoming data pushes out the initial data.…

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Employing artificial intelligence to unveil rigid and strong microstructures.

3-D printing, Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Design, Electrical Engineering & Computer Science (eecs), Materials science and engineering, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedMarch 7, 202471Views0Likes0Comments
A team of researchers at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed a revolutionary computational design system that enhances the performance of microstructured materials. These materials, ubiquitous in everything from cars to airplanes, offer essential durability and strength. This project, led by Beichen Li, a CSAIL affiliate and an MIT PhD…

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The new system pinpoints medications that should not be concurrently consumed.

Artificial Intelligence, Computer science and technology, Drug delivery, Machine learning, Mechanical engineering, Medicine, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedMarch 7, 202474Views0Likes0Comments
Researchers at MIT, Brigham and Women’s Hospital, and Duke University have developed a method for identifying the protein transporters different drugs use to traverse the digestive tract. This could help to avoid dangerous drug interactions and enhance patient treatment as two medications that use the same transporter may interact negatively if prescribed together. The method…

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Empowering individuals facing challenges with the utilization of Artificial Intelligence.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedMarch 7, 202476Views0Likes0Comments
In 2010, Media Lab students at MIT Karthik Dinakar and Birago Jones began working on a project to help content moderation teams of companies like Twitter and YouTube. They developed an AI model to identify sensitive posts, but soon realized that the terminology and language used by some users was overlooked by the model. Challenged…

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AI Generation for Intelligent Grid Simulation

Artificial Intelligence, Climate, Computer modeling, Electrical Engineering & Computer Science (eecs), Energy, Funding, Grants, Laboratory for Information and Decision Systems (LIDS), Lincoln Laboratory, Machine learning, MIT Schwarzman College of Computing, School of Engineering, UncategorizedMarch 7, 202478Views0Likes0Comments
The Laboratory for Information and Decision Systems (LIDS) at Massachusetts Institute of Technology (MIT) has received a grant of $1,365,000 from the Appalachian Regional Commission (ARC). The funding supports LIDS's role in the "Forming the Smart Grid Deployment Consortium (SGDC) and Expanding the HILLTOP+ Platform" project. Made available through ARC's Appalachian Regional Initiative for Stronger…

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“We provide an alternative venue for learning.”

Abdul Latif Jameel World Education Lab (J-WEL), academics, Africa, Artificial Intelligence, Classes and programs, Collaboration, Computer science and technology, Data, Digital technology, Education, Global, Human-computer interaction, International development, International initiatives, Internet, K-12 education, Labor and jobs, Learning, Machine learning, Media Lab, MITx, Office of Open Learning, Online learning, Programming, Robotics, School of Architecture and Planning, Software, STEM education, teaching, Technology and society, UncategorizedMarch 7, 202474Views0Likes0Comments
Jospin Hassan, a resident of Dzaleka Refugee Camp in Malawi, realized the lack of educational opportunities in his environment, particularly in cutting-edge fields like data science and artificial intelligence that can offer employment opportunities and solutions to local challenges. This led him to establish his organization, ADAI Circle, after he earned a spot in the…

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A new AI model has the potential to enhance efficiency in robotic warehouses.

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, UncategorizedMarch 7, 202467Views0Likes0Comments
MIT researchers have developed a deep-learning model to help robots navigate crowded warehouses, where congestion can slow operations and even lead to crashes. The model does this by dividing the robots into smaller groups and using a path-finding algorithm to decongest each group more quickly. Researchers described the process as being similar to mitigating traffic…

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