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.
Computer Science and Artificial Intelligence Laboratory (CSAIL)
A computer scientist pushes the boundaries of geometry
Justin Solomon applies modern geometric techniques to solve problems in computer vision, machine learning, statistics, and beyond.
Boosting faith in the authenticity of open source software
Speranza system brings hope to users that the package they download is functional software, not malware.
MIT Generative AI Week fosters dialogue across disciplines
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.
Automated system teaches users when to collaborate with an AI assistant
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
A new optimization framework for robot motion planning
MIT CSAIL researchers established new connections between combinatorial and continuous optimization, which can find global solutions for complex motion-planning puzzles.
What does the future hold for generative AI?
Rodney Brooks, co-founder of iRobot, kicks off an MIT symposium on the promise and potential pitfalls of increasingly powerful AI tools like ChatGPT.
New method uses crowdsourced feedback to help train robots
Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.
Students pitch transformative ideas in generative AI at MIT Ignite competition
Twelve teams of students and postdocs across the MIT community presented innovative startup ideas with potential for real-world impact.
Three MIT affiliates receive Schmidt awards
Jörn Dunkel and Surya Ganguli ’98, MNG ’98 receive Science Polymath awards; Josh Tenenbaum is named AI2050 Senior Fellow.
Synthetic imagery sets new bar in AI training efficiency
MIT CSAIL researchers innovate with synthetic imagery to train AI, paving the way for more efficient and bias-reduced machine learning.
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.
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.