Computer Science and Artificial Intelligence Laboratory (CSAIL)
Computer Science and Artificial Intelligence Laboratory (CSAIL)

Computer Science and Artificial Intelligence Laboratory (CSAIL)

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering

A faster, better way to train general-purpose robots

Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Quest for Intelligence Research School of Engineering

Making it easier to verify an AI model’s responses

By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering Video

Combining next-token prediction and video diffusion in computer vision and robotics

A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.

Algorithms Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Faculty machine learning MIT Schwarzman College of Computing Profile School of Engineering Social networks

Modeling relationships to solve complex problems efficiently

Associate Professor Julian Shun develops high-performance algorithms and frameworks for large-scale graph processing.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering

How AI is improving simulations with smarter sampling techniques

MIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy.

Algorithms Artificial Intelligence Brain and cognitive sciences Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) Evolution Imaging Lincoln Laboratory machine learning MIT Schwarzman College of Computing Psychology Research School of Engineering School of Science

AI pareidolia: Can machines spot faces in inanimate objects?

New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.

Algorithms Artificial Intelligence Collaboration Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Research School of Engineering

Enhancing LLM collaboration for smarter, more efficient solutions

“Co-LLM” algorithm helps a general-purpose AI model collaborate with an expert large language model by combining the best parts of both answers, leading to more factual responses.

Algorithms Artificial Intelligence Broad Institute Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical Engineering & Computer Science (eecs) Health Care Imaging machine learning MIT Schwarzman College of Computing National Institutes of Health (NIH) Research School of Engineering

A fast and flexible approach to help doctors annotate medical scans

“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.

Algorithms Artificial Intelligence Computer graphics Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

A framework for solving parabolic partial differential equations

A new algorithm solves complicated partial differential equations by breaking them down into simpler problems, potentially guiding computer graphics and geometry processing.


Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) cybersecurity Electrical Engineering & Computer Science (eecs) Interview machine learning Media Lab MIT Schwarzman College of Computing Policy Privacy School of Architecture and Planning School of Engineering social media Social networks

3 Questions: How to prove humanity online

AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?