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A crossroads for computing at MIT

April 16, 2024

The MIT Schwarzman College of Computing building will form a new cluster of connectivity across a spectrum of disciplines in computing and artificial intelligence.

Engineering household robots to have a little common sense

March 29, 2024

With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.

New software enables blind and low-vision users to create interactive, accessible charts

March 29, 2024

Screen-reader users can upload a dataset and create customized data representations that combine visualization, textual description, and sonification.

AI generates high-quality images 30 times faster in a single step

March 25, 2024

Novel method makes tools like Stable Diffusion and DALL-E-3 faster by simplifying the image-generating process to a single step while maintaining or enhancing image quality.

Optimizing nuclear fuels for next-generation reactors

March 25, 2024

While working to nurture scientific talent in his native Nigeria, Assistant Professor Ericmoore Jossou is setting his sights on using materials science and computation to design robust nuclear components.

2024 MacVicar Faculty Fellows named

March 18, 2024

Professors Berggren, Campbell, Pollock, and Vaikuntanathan are honored for exceptional undergraduate teaching.

Priya Donti named AI2050 Early Career Fellow

March 12, 2024

Assistant Professor Priya Donti has been named an AI2050 Early Career Fellow by Schmidt Sciences, a philanthropic initiative from Eric and Wendy Schmidt aimed at helping to solve hard problems in AI.

Using generative AI to improve software testing

March 6, 2024

MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.

Student Spotlight: Victory Yinka-Banjo

March 4, 2024

Victory Yinka-Banjo is a junior majoring in 6-7: Computer Science and Molecular Biology.

Dealing with the limitations of our noisy world

March 1, 2024

Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.