“GeoPT” helps AI models understand the basics of physics so they can simulate how objects respond to things like wind and water more efficiently and accurately.
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“GeoPT” helps AI models understand the basics of physics so they can simulate how objects respond to things like wind and water more efficiently and accurately.
MIT CSAIL director Daniela Rus has been awarded the 2026 High-Tech Prize of the Bavarian Minister-President for her contributions to robotics, AI, and autonomous systems, one of Germany's most prestigious tech awards.
The prize is jointly awarded by the Bavarian State Government and the Bavarian Academy of Sciences and Humanities, and is the highest-endowed tech award in Germany.
Rus's work spans self-organizing robot collectives, soft robotics, autonomous mobility, and brain-inspired AI.
This spring, 25 MIT students and postdocs traveled to Washington to meet with congressional staffers and advocate for sustained federal investment in scientific research. They visited 62 congressional offices across 32 states, discussing science funding, AI privacy, deep-sea mining, and more. The program, organized by the MIT Science Policy Initiative, aims to train the next generation of scientists in policy advocacy.
MIT students and postdocs met with congressional staffers to advocate for federal research funding. They visited 62 offices in 32 states, discussing AI, environmental, and other policies. Participants noted bipartisan support for science and the importance of scientist engagement in government.
The visionary PhysioNet platform launched 25 years ago, based on a system developed at MIT in the 1970s. It has become one of the most comprehensive biomedical and clinical data repositories in existence, now hosting hundreds of databases, cited by over 15,000 papers last year, and used by researchers from more than 180 countries. The platform lowered the barrier for high-risk research and became a cornerstone for AI in healthcare.
PhysioNet originated from a 1975 MIT-Beth Israel hospital project to digitize and share ECG data.
The platform launched in 1999, evolving from mailed tapes to CDs to internet-based distribution.
Known for his clear and elegant writing style, Bertsekas shaped fields from control and optimization to large-scale computation and artificial intelligence.
Dimitri Bertsekas, MIT professor emeritus, passed away on June 3 at age 83.
He authored over 20 influential books on optimization, control, and AI.
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.
Neural transparency tool visualizes internal activation directions to preview AI personality traits before conversation begins.
Study shows users frequently misjudge AI behavior, overestimating positive traits and underestimating harmful ones like sycophancy.
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
Devavrat Shah develops AI methods for real-time decision-making with limited resources.
He co-founded Ikigai Labs, which built a foundation model for tabular time-series data.
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems. The challenge revealed that while AI can accelerate design-build-test cycles, human engineering judgment and experience remain decisive. Teams with stronger fundamentals outperformed those relying heavily on AI.
MIT's JARVIS Challenge pitted student teams against a four-week jet engine design-build-test sprint with AI as their primary engineering partner.
The competition showed AI can speed up hardware engineering, but manufacturing and vendor relationships remain key bottlenecks.
MIT and Toyota Research Institute researchers developed 'SceneSmith,' a system using three AI agents to generate realistic 3D indoor scenes like kitchens, hotels, and living rooms. These virtual environments provide rich training data for robots, helping them practice everyday tasks in simulation, reducing real-world testing time and cost.
SceneSmith uses three AI agents (designer, critic, orchestrator) based on vision-language models to generate 3D scenes.
Generated scenes contain up to six times more objects than prior methods, enabling interactions like opening cabinets and placing items.
Researchers from MIT and Thorn have developed an auditing technique that detects whether generative AI models can produce child sexual abuse material (CSAM) by analyzing internal model adaptations, without generating any outputs. The method achieved 100% accuracy in tests and is scalable, offering a practical tool for platforms and law enforcement.
The new audit method uses Gaussian probing on LoRA adaptors to detect CSAM capabilities without generating any content.
In tests, it identified models specialized for CSAM generation with 100% accuracy.
A US Air Force cadet, with guidance from an MIT Lincoln Laboratory researcher, used AI chatbots via 'vibe-coding' to develop a functional military application prototype despite having no coding experience. The project demonstrated AI's potential to empower nontechnical service members, while also highlighting security and limitation issues.
Cadet Joshua Lynch built ROMAD-AI prototype from scratch using AI chatbots
Project scaled down from battlefield assistance to document processing, proving rapid prototyping capability
The professor of physics and inaugural director of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions will lead LNS and continue his research in particle physics.
Jesse Thaler appointed director of MIT's Laboratory for Nuclear Science (LNS), effective Aug. 1.
He is a theoretical particle physicist pioneering the combination of AI and machine learning with particle physics.
During a "Washington Post Live" panel discussion with ASU President Michael Crow, President Sally Kornbluth explored how universities are preparing the next generation of scientists to lead in America’s rapidly changing technological landscape.
MIT President Sally Kornbluth warns that without federal support for curiosity-driven research, the innovation pipeline may dry up.
MIT's new curriculum integrates STEM with moral, civic, and ethical education to develop responsible technologists.
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.
Agentic AI is AI that takes actions, distinct from generative AI.
35% of businesses have deployed AI agents; 44% plan to.
MIT’s Music Technology and Computation Graduate Program, launched in fall 2024, held its inaugural research showcase on May 13, featuring projects from its first five students, including EEG-based music decoding and AI improvisation visualization. Director Eran Egozy announced 10 new students for the next academic year from a broader applicant pool.
MIT’s Music Technology and Computation program started in fall 2024 and hosted its first showcase on May 13.
The five initial students, all MIT alumni, presented projects such as decoding imagined music from EEG signals and interactive music-driven visualizations.
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.
The exhibition, on view through June 30, examines 20th- and 21st-century efforts to transform computing into a medium for creative production and aesthetic judgment.
It draws on philosophy, mathematics, computer science, and design computation to translate algorithms and theories into physical installations.
David Autor, a leading researcher in AI and the future of work, has been named head of MIT's Department of Economics, effective July 1. His work focuses on labor market impacts of technological change and globalization.
David Autor, MIT economics professor since 1999, appointed department head.
He is a leading expert on AI and the future of work, studying technology's impact on jobs and inequality.
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.
Masked IRL uses one LLM to elaborate on ambiguous prompts and another to ignore irrelevant environment details.
The method reduces required demonstration data by nearly five times.
Researchers from MIT and Microsoft developed Murakkab, a system that optimizes agentic workflows (AI-powered multistep tasks). It lets developers describe intent in plain language, automatically selects models, tools, and hardware, and dynamically adjusts configurations to prioritize speed or cost. Tests show it uses only ~35% computation, ~27% energy, and <25% cost versus traditional methods, without performance loss.
Murakkab automates optimization of multi-step AI workflows to reduce resource waste.
Developers specify tasks in natural language; the system dynamically chooses models, tools, and hardware.
At the AI and Society Forum at MIT, experts discussed AI's effects on employment and democracy. Economist David Autor challenged the notion that AI will eliminate jobs, while others explored AI's potential for collaboration and its risks to democratic processes.
Economist David Autor argues AI's impact depends on how it changes the scarcity of human expertise, potentially creating specialized jobs.
Panelists emphasized human judgment remains critical in decision-making, with AI as a collaborative tool.
MIT researchers combined an efficient algorithm with dedicated hardware to develop a low-power chip that enables tiny UAVs and other devices to build real-time 3D maps and navigate using only about 6 milliwatts of power.
Uses ellipsoid Gaussians instead of voxels to represent obstacles, reducing memory and power.
Algorithm processes depth images in a single pass without storing full images.
MIT researchers have developed a machine-learning approach that improves the accuracy of material simulations by constructing training datasets that capture the diversity of atomic environments in chemically disordered metal alloys, potentially accelerating materials discovery.
New method uses information theory to build diverse training datasets for machine-learning models, capturing subtle atomic patterns in disordered alloys.
Outperforms brute-force methods and large-scale models from Google and Microsoft in predicting material properties.
Leaders, faculty across MIT discuss fostering innovation and talent in Greater Boston in special series of articles published alongside the outlet's annual list of 'Tech Power Players'
Eight MIT affiliates named to Boston Globe 2026 Tech Power Players list.
MIT pushes AI advancement through free online courses and entrepreneurship support.
A new spatial memory system for robots efficiently captures details about the objects they see while exploring their environment, enabling them to answer queries like 'Where did I leave my keys?' with high accuracy.
MIT researchers developed DAAAM, a long-term memory framework that combines 3D maps with rich object descriptions.
Robots can form and recall detailed mental models of large-scale environments in real-time.