Laboratory for Information and Decision Systems (LIDS)
Laboratory for Information and Decision Systems (LIDS)

Laboratory for Information and Decision Systems (LIDS)

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mathematics MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Research School of Engineering

Study: Platforms that rank the latest LLMs can be unreliable

Removing just a tiny fraction of the crowdsourced data that informs online ranking platforms can significantly change the results.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Health Care Institute for Medical Engineering and Science (IMES) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering Technology and society

Why it’s critical to move beyond overly aggregated machine-learning metrics

New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.

Algorithms Alternative energy Artificial Intelligence Batteries Climate change Computer science and technology Electrical engineering and computer science (EECS) Energy Energy storage Faculty Interview Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Pollution Research School of Engineering Sustainability Sustainable computing

3 Questions: How AI could optimize the power grid

While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.

Artificial Intelligence Broad Institute Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology cybersecurity Electrical engineering and computer science (EECS) Ethics Health Care Health sciences and technology Human-computer interaction Institute for Medical Engineering and Science (IMES) Jameel Clinic Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Privacy Public health Research School of Engineering Technology and society

MIT scientists investigate memorization risk in the age of clinical AI

New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mathematics MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

New method improves the reliability of statistical estimations

The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.

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

A smarter way for large language models to think about hard problems

This new technique enables LLMs to dynamically adjust the amount of computation they use for reasoning, based on the difficulty of the question.

Aeronautical and astronautical engineering Artificial Intelligence Bioinspiration Drones Electrical engineering and computer science (EECS) Electronics Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research Research Laboratory of Electronics Robotics School of Engineering

MIT engineers design an aerial microrobot that can fly as fast as a bumblebee

With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.

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

New control system teaches soft robots the art of staying safe

MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits.

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction Institute for Medical Engineering and Science (IMES) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Technology and society

Researchers discover a shortcoming that makes LLMs less reliable

Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.

Algorithms Artificial Intelligence Classes and programs Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Graduate, postdoctoral Institute for Medical Engineering and Science (IMES) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering Students

Charting the future of AI, from safer answers to faster thinking

MIT PhD students who interned with the MIT-IBM Watson AI Lab Summer Program are pushing AI tools to be more flexible, efficient, and grounded in truth.