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MIT News - Machine learning
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Showing 1-50 of 149 entries
The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.
New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that's essential to fertilizer and other products.
18 Aug
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors.
An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.
Researchers developed an automated framework that helps AI models generate CAD programs more accurately and efficiently.
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
14 Jul
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.
MIT and Tec de Monterrey will expand FrED curriculum to universities across Mexico.
Computer scientist Phillip Isola cuts through the hype to explain how AI agents work and what the future might hold for this rapidly advancing technology.
Inaugural Music Technology Research Showcase celebrates work of new graduate program’s initial students
29 Jun
Associate Professor Anna Huang delivers the keynote address, “In Search of Human-AI Resonance,” to a capacity crowd.
In a new Keller Gallery exhibition, Alexandros Haridis SM ’17, PhD ’22 traces centuries of ideas about aesthetic judgment and explores how design can make complex computational systems visible.
To help robots do chores in places like homes and factories, a new approach from MIT uses one language model to clarify users’ instructions, then another to ignore irrelevant info.
A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.
Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power.
MIT researchers’ approach captures subtle atomic patterns, improving predictions of material properties.
Researchers show that for certain kinds of games, an overlooked class of algorithms performs much better than expected.
A new spatial memory system for robots efficiently captures details about the objects they see while exploring their environment.
MIT researchers provide a major upgrade to the nearly century-old idea of random utility models.
Using technology invented at MIT, Cartesian’s system for locating objects could also find uses in manufacturing, logistics, and robotics.
IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics.
MIT researchers use the classic game as a test bed for AI agents, finding a small AI model can outperform the biggest ones at 1 percent of the cost.
The new ChartNet training dataset could improve the accuracy of vision-language models that help analyze business trends or interpret scientific figures.
Newey has been a leading figure in econometric theory for more than four decades, shaping both research and training in the field.
Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.
MIT faculty member in electrical engineering and computer science to focus on innovation in engineering education and new pedagogical approaches.
12 May
New AI education program from MIT Open Learning debuts with AI-powered personalization and a free introductory course for learners everywhere.
Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.
Founded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.
A new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone
24 Apr
New dataset of 30,000-plus competition math problems from 47 countries gives AI researchers a harder test — and students worldwide a better training ground.
A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.
The associate professors of EECS and chemistry, respectively, are honored for exceptional contributions to teaching, research, and service at MIT.
Founded by Tristan Bepler PhD ’20 and former MIT professor Tim Lu PhD ’07, OpenProtein.AI offers researchers open-source models and other tools for protein engineering.
Researchers are developing hardware and algorithms to improve collaboration between divers and autonomous underwater vehicles engaged in maritime missions.
Researchers use control theory to shed unnecessary complexity from AI models during training, cutting compute costs without sacrificing performance.
Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.
Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.
MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.
By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.
31 Mar
Computational biologist Sergei Kotelnikov is working to develop new methods in protein modeling as part of the School of Science Dean’s Postdoctoral Fellowship.
A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.
This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.