MIT-IBM Watson AI Lab
MIT-IBM Watson AI Lab

MIT-IBM Watson AI Lab

Algorithms Artificial Intelligence Collaboration Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Funding Industry machine learning MIT Schwarzman College of Computing MIT-IBM Computing Research Lab MIT-IBM Watson AI Lab Quantum Computing Research Supercomputing

The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing

Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Energy Environment machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering Sustainability Sustainable computing Technology and society

A faster way to estimate AI power consumption

The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.

Artificial Intelligence Biology Civil and environmental engineering Computational biology Health sciences and technology Materials science and engineering Mechanical engineering MIT-IBM Watson AI Lab Proteins Research School of Engineering Synthetic biology

MIT engineers design proteins by their motion, not just their shape

An AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.

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

A better method for identifying overconfident large language models

This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.

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.

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 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.

3-D printing Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Design Electrical engineering and computer science (EECS) Fabrication Human-computer interaction MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

Mixing generative AI with physics to create personal items that work in the real world

To help generative AI models create durable, real-world accessories and decor, the PhysiOpt system runs physics simulations and makes subtle tweaks to its 3D blueprints.

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.

Alumni/ae Artificial Intelligence Awards, honors and fellowships Center for Brains Minds and Machines Computer graphics Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) Faculty MIT Schwarzman College of Computing MIT Siegel Family Quest for Intelligence MIT-IBM Watson AI Lab School of Engineering

Antonio Torralba, three MIT alumni named 2025 ACM fellows

Torralba’s research focuses on computer vision, machine learning, and human visual perception.