Algorithms
Algorithms

Algorithms

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Defense Advanced Research Projects Agency (DARPA) Electrical engineering and computer science (EECS) Ethics Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

Evaluating the ethics of autonomous systems

MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.

Algorithms Artificial Intelligence Civil and environmental engineering Computer science and technology Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) Logistics machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering Supply chains

AI system learns to keep warehouse robot traffic running smoothly

This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Careers Collaboration Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Industry Laboratory for Information and Decision Systems (LIDS) machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Natural language processing Research Robotics School of Engineering

MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact

Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.

Algorithms Artificial Intelligence Astronomy and astrophysics chemistry Computer science and technology Data Faculty IDSS Interview Laboratory for Nuclear Science machine learning Materials science and engineering Mathematics MIT Schwarzman College of Computing National Science Foundation (NSF) Physics Research School of Science

3 Questions: On the future of AI and the mathematical and physical sciences

Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Computer science and technology computer-vision Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research Robotics School of Engineering

A better method for planning complex visual tasks

A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.

Algorithms Artificial Intelligence Computer science and technology Design machine learning Mechanical engineering MIT Schwarzman College of Computing Research School of Engineering Systems design

A “ChatGPT for spreadsheets” helps solve difficult engineering challenges faster

The approach could help engineers tackle extremely complex design problems, from power grid optimization to vehicle design.

Algorithms Artificial Intelligence Autonomous Underwater Vehicles (AUV) Lincoln Laboratory Programming Robotics Students Woods Hole

Featured video: Coding for underwater robotics

Lincoln Laboratory intern Ivy Mahncke developed and tested algorithms to help human divers and robots navigate underwater.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Energy machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Research Research Laboratory of Electronics School of Engineering

New method could increase LLM training efficiency

By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.

Algorithms Artificial Intelligence Biological engineering Biology Broad Institute Cells Computer science and technology Diagnostics Electrical engineering and computer science (EECS) Genetics health IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Medicine MIT Schwarzman College of Computing National Institutes of Health (NIH) Research School of Engineering

AI to help researchers see the bigger picture in cell biology

By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.

Algorithms Artificial Intelligence Computer science and technology Data machine learning Mathematics Research School of Science Software

Exposing biases, moods, personalities, and abstract concepts hidden in large language models

A new method developed at MIT could root out vulnerabilities and improve LLM safety and performance.