A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.
Using generative AI to improve software testing
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
Department of EECS Announces 2024 Promotions
The Department of Electrical Engineering and Computer Science (EECS) is proud to announce multiple promotions.
How symmetry can come to the aid of machine learning
Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.
Reasoning and reliability in AI
PhD students interning with the MIT-IBM Watson AI Lab look to improve natural language usage.
MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.
Leveraging language to understand machines
Master’s students Irene Terpstra ’23 and Rujul Gandhi ’22 use language to design new integrated circuits and make it understandable to robots.
MIT group releases white papers on governance of AI
The series aims to help policymakers create better oversight of AI in society.
Image recognition accuracy: An unseen challenge confounding today’s AI
“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.
EECS Alliance Roundup: 2023
Founded in 2019, The EECS Alliance program connects industry leading companies with EECS students for internships, post graduate employment, networking, and collaborations. In 2023, it has grown to include over 30 organizations that have either joined the Alliance or participate in its flagship program, 6A.