Artificial Intelligence + Machine Learning

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February 11, 2025

Bridging philosophy and AI to explore computing ethics

In a new MIT course co-taught by EECS and philosophy professors, students tackle moral dilemmas of the digital age.

February 10, 2025

Creating a common language

New faculty member Kaiming He discusses AI’s role in lowering barriers between scientific fields and fostering collaboration across scientific disciplines.

February 10, 2025

Can deep learning transform heart failure prevention?

A deep neural network called CHAIS may soon replace invasive procedures like catheterization as the new gold standard for monitoring heart health.

February 4, 2025

Aligning AI with human values

“We need to both ensure humans reap AI’s benefits and that we don’t lose control of the technology,” says senior Audrey Lorvo.

February 3, 2025

User-friendly system can help developers build more efficient simulations and AI models

By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.

Schmidt Center – MIT EECS Colloquium: Machine learning to analyze cellular behavior in live-cell imaging experiments of T cell—cancer cell co-cultures

 Barbara Engelhardt, Gladstone Institutes, Stanford University Thursday, February 6, 20254:00 – 5:00 pm (refreshments at 3:30 pm)Monadnock (Merkin building/415M 2040) 📅 Add to your calendar 🖊️ Register here A week from today — please

January 16, 2025

Algorithms and AI for a better world

Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.

January 13, 2025

Daniela Rus named to French National Academy of Medicine

As the Director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), Rus leads over 1,700 researchers in pioneering innovations to advance computing and improve global well-being.

January 6, 2025

Study reveals AI chatbots can detect race, but racial bias reduces response empathy

Researchers at MIT, NYU, and UCLA develop an approach to help evaluate whether large language models like GPT-4 are equitable enough to be clinically viable for mental health support.

December 11, 2024

Researchers reduce bias in AI models while preserving or improving accuracy

A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.