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Artificial Intelligence Computer science and technology Data Electrical Engineering & Computer Science (eecs) Human-computer interaction IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering Wind

MIT researchers use large language models to flag problems in complex systems

The approach can detect anomalies in data recorded over time, without the need for any training.

Algorithms Artificial Intelligence Data Electrical Engineering & Computer Science (eecs) Human-computer interaction machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research Research Laboratory of Electronics School of Engineering

Method prevents an AI model from being overconfident about wrong answers

More efficient than other approaches, the “Thermometer” technique could help someone know when they should trust a large language model.

Algorithms Artificial Intelligence Computer science and technology Data Electrical Engineering & Computer Science (eecs) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

Study: When allocating scarce resources with AI, randomization can improve fairness

Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.

Algorithms Artificial Intelligence Computer science and technology Data Human-computer interaction IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mechanical engineering MIT Schwarzman College of Computing Research School of Engineering

How to assess a general-purpose AI model’s reliability before it’s deployed

A new technique enables users to compare several large models and choose the one that works best for their task.

Artificial Intelligence Computer science and technology Data Electrical Engineering & Computer Science (eecs) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering Technology and society

When to trust an AI model

More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.

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MIT ARCLab announces winners of inaugural Prize for AI Innovation in Space

The challenge asked teams to develop AI algorithms to track and predict satellites’ patterns of life in orbit using passively collected data

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“They can see themselves shaping the world they live in”

Developed by MIT RAISE, the Day of AI curriculum empowers K-12 students to collaborate on local and global challenges using AI.

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MIT researchers introduce generative AI for databases

This new tool offers an easier way for people to analyze complex tabular data.

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MIT-Takeda Program wraps up with 16 publications, a patent, and nearly two dozen projects completed

The program focused on AI in health care, drawing on Takeda’s R&D experience in drug development and MIT’s deep expertise in AI.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research Robotics Robots School of Engineering

Researchers use large language models to help robots navigate

The method uses language-based inputs instead of costly visual data to direct a robot through a multistep navigation task.