MIT-IBM Computing Research Lab

A collaborative industrial-academic laboratory focused on charting the convergence of AI, algorithms, and quantum computing.

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT and IBM will expand our collaboration: The MIT-IBM Computing Research Lab will seek to leverage hybrid quantum and classical computing, with advanced algorithms and AI, to solve challenging problems in fundamentally new ways. https://t.co/2tIKRrAETY

[MIT-IBM Computing Research Lab @MITIBMLab]

A new method from MIT, the MIT-IBM Watson AI Lab, and others could increase the training efficiency of large language models: By leveraging idle computing time, it can double the speed of model training while preserving accuracy.
https://t.co/mtXqZy89tn

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT and MIT-IBM Watson AI Lab researchers are blending generative AI with physics simulations to make 3D designs that actually work in real life. The system, PhysiOpt, turns creative ideas into usable objects.

https://t.co/UaWZlPQWRm

[MIT-IBM Computing Research Lab @MITIBMLab]

AI research led by MIT provides an overall picture of the cell state by identifying which data measurements tell researchers about one or multiple components of the cell. This could help clinicians understand disease mechanisms and plan treatments.
https://t.co/0YRGDdJDeL

[MIT-IBM Computing Research Lab @MITIBMLab]

A study from MIT and the MIT-IBM Watson AI Lab finds that 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.

https://t.co/eCJ6w5NEZY

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method. https://t.co/7mF7wysaBL

[Massachusetts Institute of Technology (MIT) @MIT]

AI models are getting bigger but do they need to be?

🎧 Listen to the full episode of Curiosity Unbounded to learn how efficiency could be the next big breakthrough in AI.

[MIT School of Engineering @MITEngineering]

Tess Smidt, an associate professor in @MITEECS, has been named to the 2025 cohort of AI2050 Early Career Fellows.

https://t.co/969QLa4b81

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT and @MITIBMLab researchers have developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
https://t.co/b9yHSmsk4h

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT researchers have developed the “self-steering” DisCIPL system, which uses an LLM to plan how to answer complex reasoning tasks, like itinerary planning and budgeting, and then divides the legwork of that strategy among smaller language models.
https://t.co/kpmhgujNWF

[MIT-IBM Computing Research Lab @MITIBMLab]

A new technique from MIT and @MITIBMLab enables LLMs to dynamically adjust the amount of computation they use for reasoning, based on the difficulty of the question.
https://t.co/KhqeyS0nmH

[MIT-IBM Computing Research Lab @MITIBMLab]

Charting the future of AI, from safer answers to faster thinking: MIT PhD students in the @MITIBMLab Summer Program are pushing AI tools to be more flexible, efficient, and grounded in truth. https://t.co/7yHC0yLEot

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT researchers have developed a new method that lets LLMs integrate new knowledge efficiently by generating and applying their own “study notes,” enabling them to adapt over time.
https://t.co/ZdFPWkChnX

[MIT-IBM Computing Research Lab @MITIBMLab]

Creating AI that matters: How the MIT-IBM Watson AI Lab is shaping AI-sociotechnical systems for the future.
https://t.co/pkHtJd5BvE

[MIT-IBM Computing Research Lab @MITIBMLab]

A new training method from MIT and @MITIBMLab teaches vision-language generative AI models (VLMs) to localize a personalized object. https://t.co/ZiFQJ3GXn0

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT and @MITIBMLab researchers have developed a universal guide for estimating the performance of an LLM based on smaller models in the same family, saving time, money, and compute.
https://t.co/tPC92A11kc

[Massachusetts Institute of Technology (MIT) @MIT]

CodeSteer guides AI models to switch between text and code to solve tough problems. “A trainer may not be better than the star athlete … but the trainer can still give helpful suggestions,” Yongchao Chen says. “This steering method works for LLMs, too.” https://t.co/Xg2ey40juF

[MIT School of Engineering @MITEngineering]

Dean Anantha Chandrakasan has been named MIT’s new provost, effective July 1. He has served as the dean of the School of Engineering since 2017 and as MIT’s inaugural chief innovation and strategy officer since 2024.

https://t.co/eFRQpuhZRm

[MIT-IBM Computing Research Lab @MITIBMLab]

A new AI framework from @MIT and the @MITIBMLab supercharges language models, so they can reason over, interactively develop, and verify valid, complex travel agendas.
https://t.co/Yx4eqLDJWe

[MIT-IBM Computing Research Lab @MITIBMLab]

MIT researchers have unveiled an AI-driven adaptive control system for autonomous drones, significantly cutting trajectory errors in the face of unpredictable winds.
https://t.co/VewBwxV7mZ