Journey to the future of generative AI
MIT Generative AI Week will explore the latest cutting-edge research, along with the implications and possibilities of generative AI.
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Aging Brain Initiative symposium showcases “cutting-edge” research across MIT
Seed projects, posters represent a wide range of labs working on technologies, therapeutic strategies, and fundamental research to advance understanding of age-related neurodegenerative disease.
Technique enables AI on edge devices to keep learning over time
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
A new wave of treatment for Alzheimer’s disease
Professor Li-Huei Tsai studies how brain waves can be used to treat neurodegenerative diseases such as Alzheimer’s.
This 3D printer can watch itself fabricate objects
Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.
Explained: Generative AI
How do powerful generative AI systems like ChatGPT work, and what makes them different from other types of artificial intelligence?
Using AI to optimize for rapid neural imaging
MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.
Using language to give robots a better grasp of an open-ended world
By blending 2D images with foundation models to build 3D feature fields, a new MIT method helps robots understand and manipulate nearby objects with open-ended language prompts.
2023-24 Takeda Fellows: Advancing research at the intersection of AI and health
Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.
Forging climate connections across the Institute
Inaugural Fast Forward Faculty Fund grants aim to spur new work on climate change and deepen collaboration at MIT.
A new record for Math Prize for Girls wins
Twelfth grader Jessica Wan three-peats, as MIT hosts the 15th competition for female middle and high school math enthusiasts.
New techniques efficiently accelerate sparse tensors for massive AI models
Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.
Accelerating AI tasks while preserving data security
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
The brain may learn about the world the same way some computational models do
Two studies find “self-supervised” models, which learn about their environment from unlabeled data, can show activity patterns similar to those of the mammalian brain.
Making genetic prediction models more inclusive
MIT computer scientists developed a way to calculate polygenic scores that makes them more accurate for people across diverse ancestries.