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alt="A software program runs on a monitor at an empty desk (Credit: Pixabay)."
CSAIL article

A particular set of probabilistic inference algorithms common in robotics involve Sequential Monte Carlo methods, also known as “particle filtering,” which approximates using repeated random sampling. (“Particle,” in this context, refers to individual samples.) Traditional particle filtering struggles with providing accurate results on complex distributions, giving rise to advanced algorithms such as hybrid particle filtering.

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The new compiler, called SySTeC, can optimize computations by automatically taking advantage of both sparsity and symmetry in tensors (Credits: iStock).
CSAIL article

The neural network artificial intelligence models used in applications like medical image processing and speech recognition perform operations on hugely complex data structures that require an enormous amount of computation to process. This is one reason deep-learning models consume so much energy.

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MIT professor and CSAIL Director Daniela Rus.
CSAIL article

Daniela Rus, a distinguished computer scientist and professor at the Massachusetts Institute of Technology (MIT), has been honored with induction into the prestigious Académie Nationale de Médecine (ANM) as a foreign member on January 7, 2025. As the Director of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), Daniela leads over 1,700 researchers in pioneering innovations to advance computing and improve global well-being.