Using generative AI to improve software testing
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
Dealing with the limitations of our noisy world
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
Department of EECS Announces 2024 Promotions
The Department of Electrical Engineering and Computer Science (EECS) is proud to announce multiple promotions.
Artificial intelligence for augmentation and productivity
The MIT Schwarzman College of Computing awards seed grants to seven interdisciplinary projects exploring AI-augmented management.
Planning algorithm enables high-performance flight
With this new approach, a tailsitter aircraft, ideal for search-and-rescue missions, can plan and execute complex, high-speed acrobatic maneuvers.
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
Strengthening trust in machine-learning models
Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where confidence in the results of a data analysis might break down.
Computers that power self-driving cars could be a huge driver of global carbon emissions
Study shows that if autonomous vehicles are widely adopted, hardware efficiency will need to advance rapidly to keep computing-related emissions in check.
Six With Ties to MIT Honored as ACM Fellows
Six distinguished scientists with ties to MIT were recognized “for significant contributions in areas including cybersecurity, human-computer interaction, mobile computing, and recommender systems among many other areas.”