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MIT-IBM Computing Research Lab @MITIBMLab

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

Joined February 2019
  • Tweets 687
  • Following 690
  • Followers 7,500
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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. news.mit.edu/2026/mit-ibm-co…

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

IBM and MIT announced the launch of the MIT-IBM Computing Research Lab, advancing their long-standing collaboration to shape the next era of computing that combines AI, algorithms, and quantum...

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The new ChartNet training dataset from MIT and @MITIBMLab could improve the accuracy of vision-language models that help analyze business trends or interpret scientific figures. news.mit.edu/2026/mit-resear…

MIT researchers teach AI models to interpret charts

Researchers used a novel data generation pipeline to build ChartNet, a large synthetic dataset of chart images paired with corresponding information. They used this training dataset to improve the...

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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. news.mit.edu/2026/new-method…

New method could increase LLM training efficiency

A new technique leverages computing downtime to accelerate the training process for reasoning large language models (LLMs) without any additional computational overhead.

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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. news.mit.edu/2026/mixing-ai-…

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

A system known as PhysiOpt complements generative AI models with physics simulations to create 3D models of personal items. Users can prompt the system using text or images, and get a blueprint that...

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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. news.mit.edu/2026/ai-help-re…

AI to help researchers see the bigger picture in cell biology

A new AI framework identifies which data about a cell are captured by one measurement modality and which are shared across multiple modalities. This gives researchers a more complete picture of the...

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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. news.mit.edu/2026/study-plat…

Study: Platforms that rank the latest LLMs can be unreliable

The results of popular LLM ranking platforms can be skewed by just a few data points, possibly providing an unreliable report about which LLM would perform best in real situations, according MIT...

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MIT researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method. news.mit.edu/2025/guided-lea…

Guided learning lets “untrainable” neural networks realize their potential

MIT CSAIL study suggests that neural network architectures considered unsuitable for modern tasks can improve with short-term guidance. The method encourages a target network to match a guide...

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MIT-IBM Computing Research Lab retweeted
Massachusetts Institute of Technology (MIT)
@MIT
Mar 12
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.
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MIT-IBM Computing Research Lab retweeted
MIT School of Engineering@MITEngineering
Jan 6
Tess Smidt, an associate professor in @MITEECS, has been named to the 2025 cohort of AI2050 Early Career Fellows. eecs.mit.edu/tess-smidt-name…
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MIT and @MITIBMLab researchers have developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts. news.mit.edu/2025/new-way-to…

A new way to increase the capabilities of large language models

MIT-IBM Watson AI Lab researchers developed an AI expressive architecture called PaTH Attention, increasing the capabilities of large language models that can perform better state tracking and...

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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. news.mit.edu/2025/enabling-s…

Enabling small language models to solve complex reasoning tasks

MIT CSAIL's “DisCIPL” uses an LLM to steer smaller language models to collaborate on complex reasoning tasks. These less-powerful systems are collectively more accurate than leading LLMs, almost as...

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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. news.mit.edu/2025/smarter-wa…

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

MIT researchers developed a smarter way for an LLM to allocate computation while it reasons about a problem. Their method lets the model dynamically adjust its computational budget based on the...

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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. news.mit.edu/2025/charting-t…
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ALT Portrait photos of five interns
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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. news.mit.edu/2025/teaching-l…

Teaching large language models how to absorb new knowledge

MIT researchers developed a technique that enables LLMs to permanently absorb new knowledge by generating study sheets based on data the model uses to memorize important information.

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Creating AI that matters: How the MIT-IBM Watson AI Lab is shaping AI-sociotechnical systems for the future. news.mit.edu/2025/creating-a…

Creating AI that matters

The MIT-IBM Watson AI Lab bridges research and deployment in AI through advances like smaller, efficient foundation models, vision and multimodal systems, and causal discovery.

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A new training method from MIT and @MITIBMLab teaches vision-language generative AI models (VLMs) to localize a personalized object. news.mit.edu/2025/method-tea…

Method teaches generative AI models to locate personalized objects

MIT researchers developed a training method that teaches vision-language generative AI models to localize a specific object, like a person’s pet, in a new scene.

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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. news.mit.edu/2025/how-build-…

How to build AI scaling laws for efficient LLM training and budget maximization

MIT and MIT-IBM Watson AI Lab researchers have developed a universal guide for estimating how large language models (LLMs) will perform based on smaller models in the same family.

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MIT-IBM Computing Research Lab retweeted
Massachusetts Institute of Technology (MIT)
@MIT
17 Jul 2025
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.” news.mit.edu/2025/smart-coac…

This “smart coach” helps LLMs switch between text and code

CodeSteer is a smart assistant from MIT that automatically guides large language models to switch between generating text and code, and to refine its response, until it answers a query correctly.

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MIT School of Engineering@MITEngineering
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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. news.mit.edu/2025/anantha-ch…

Anantha Chandrakasan named MIT provost

Anantha Chandrakasan, a professor of electrical engineering and computer science who has held multiple leadership roles at MIT, has been named the Institute’s new provost, effective July 1.

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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. news.mit.edu/2025/inroads-pe…

Inroads to personalized AI trip planning

Researchers from MIT and the MIT-IBM Watson AI Lab developed a framework that combines a large language model and a satisfiability modulo theories (SMT) solver to create complete and accurate travel...

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