MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

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.

Closing the design-to-manufacturing gap for optical devices

A new method enables optical devices that more closely match their design specifications, boosting accuracy and efficiency.

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.

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.

MIT group releases white papers on governance of AI

The series aims to help policymakers create better oversight of AI in society.

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.

AI accelerates problem-solving in complex scenarios

A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.

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.