Algorithms
Algorithms

Algorithms

Algorithms Artificial Intelligence Civil and environmental engineering Computer science and technology IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

MIT researchers develop an efficient way to train more reliable AI agents

The technique could make AI systems better at complex tasks that involve variability.

Algorithms Artificial Intelligence Climate change Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Environment MIT Schwarzman College of Computing Plants Research School of Engineering Sustainability Urban studies and planning

Advancing urban tree monitoring with AI-powered digital twins

The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.

Algorithms Artificial Intelligence Computer science and technology Data Design Human-computer interaction Interview machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

3 Questions: Inverting the problem of design

MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.

Algorithms Artificial Intelligence Biological engineering Broad Institute Cells Computer science and technology Data Electrical engineering and computer science (EECS) Genetic engineering Genetics IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

A causal theory for studying the cause-and-effect relationships of genes

By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.

Algorithms Artificial Intelligence Computer science and technology Economics Electrical engineering and computer science (EECS) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering School of Humanities Arts and Social Sciences

Despite its impressive output, generative AI doesn’t have a coherent understanding of the world

Researchers show that even the best-performing large language models don’t form a true model of the world and its rules, and can thus fail unexpectedly on similar tasks.

Algorithms Artificial Intelligence Data Electrical engineering and computer science (EECS) Equity and inclusion Ethics IDSS machine learning MIT Schwarzman College of Computing MIT Sloan School of Management Open access Policy Racism Research School of Engineering Social justice Social sciences Technology and policy

Empowering systemic racism research at MIT and beyond

Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.

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.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Autonomous vehicles computer-vision Disaster response Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory machine learning MIT Schwarzman College of Computing Natural disasters Research Robotics School of Engineering

Helping robots zero in on the objects that matter

A new method called Clio enables robots to quickly map a scene and identify the items they need to complete a given set of tasks.