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.
Master’s students Irene Terpstra ’23 and Rujul Gandhi ’22 use language to design new integrated circuits and make it understandable to robots.
MITx MicroMasters credential leads learner to accelerated graduate program in data science.
“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.
The graduate students will aim to commercialize innovations in AI, machine learning, and data science.
Series of 2030 quantitative campus impact goals aims to reduce emissions and inform and advance the Institute’s commitment to climate.
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
By analyzing bacterial data, researchers have discovered thousands of rare new CRISPR systems that have a range of functions and could enable gene editing, diagnostics, and more.
MIT CSAIL researchers innovate with synthetic imagery to train AI, paving the way for more efficient and bias-reduced machine learning.
MIT researchers who share their data recognized at second annual awards celebration.
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
How do powerful generative AI systems like ChatGPT work, and what makes them different from other types of artificial intelligence?
Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.
Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.
Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.