Regina Barzilay, Fotini Christia, and Collin Stultz describe how artificial intelligence and machine learning can support fairness, personalization, and inclusiveness in health care.
A new tool helps humans better understand and develop artificial intelligence models by searching and highlighting representative scenarios.
Deep-learning technique optimizes the arrangement of sensors on a robot’s body to ensure efficient operation.
A new method called tensor holography could enable the creation of holograms for virtual reality, 3D printing, medical imaging, and more — and it can run on a smartphone.
With technology new and old, instructors try to recreate the interactivity of their pre-Covid classroom.
Researchers develop a system to identify drugs that might be repurposed to fight the coronavirus in elderly patients.
Assistant Professor Cathy Wu aims to help autonomous vehicles fulfill their promise by better understanding how to integrate them into the transportation system.
Researchers created a risk-assessment algorithm that shows consistent performance across datasets from US, Europe, and Asia.
EECS faculty head of artificial intelligence and decision making honored for significant and extended contributions to the field of AI.
A smart thermostat quickly learns to optimize building microclimates for both energy consumption and user preference.
A faster way to estimate uncertainty in AI-assisted decision-making could lead to safer outcomes.
MIT Task Force on the Work of the Future identifies ways to align new technologies with durable careers.
Advance could enable artificial intelligence on household appliances while enhancing data security and energy efficiency.
Machine learning model predicts probability that a particular urinary tract infection can be treated by specific antibiotics.
System developed at MIT CSAIL aims to help linguists decipher languages that have been lost to history.
Working remotely this summer, students worked to better understand human intelligence and to advance machine learning applications.
Regina Barzilay wins $1M Association for the Advancement of Artificial Intelligence Squirrel AI award
MIT professor announced as award’s first recipient for work in cancer diagnosis and drug synthesis.
Realtime Robotics has created a controller that helps robots safely move around on the fly.
The company Health at Scale uses machine learning to improve outcomes for individual patients.
New faculty in these areas will connect the MIT Schwarzman College of Computing and a department or school.
The startup Kinsa uses its smart thermometers to detect and track the spread of contagious illness before patients go to the hospital.
An artificial intelligence tool lets users edit generative adversarial network models with simple copy-and-paste commands.
Machine learning system from MIT CSAIL can look at chest X-rays to diagnose pneumonia — and also knows when to defer to a radiologist.
A team from MIT helped create an image retrieval system to find the closest matches of paintings from different artists and cultures.
C3.ai Digital Transformation Institute awards $5.4 million to top researchers to steer how society responds to the pandemic.
A global team of researchers searches for insights during a weeklong virtual “datathon.”
Music gesture artificial intelligence tool developed at the MIT-IBM Watson AI Lab uses body movements to isolate the sounds of individual instruments.
An MIT-developed technique could aid in tracking the ocean’s health and productivity.
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
Engineers develop a rapid screening system to test fracture resistance in billions of potential materials.
The MIT-IBM Watson AI Lab is funding 10 research projects aimed at addressing the health and economic consequences of the pandemic.
Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.
Researchers show that computers can “write” algorithms that adapt to radically different environments better than algorithms designed by humans.
The growing use of energy-intensive AI applications has led to a push for smaller, more efficient AI models. The MIT Quest for Intelligence and MIT-IBM Watson AI Lab recently sponsored a "Green AI" hackathon to spur innovation in this area.
Startup Posh has created chatbots that use “conversational memory” to have more natural exchanges.
A machine learning algorithm combines data on the disease's spread with a neural network, to help predict when infections will slow down in each country.
Translated into sound, SARS-CoV-2 tricks our ear in the same way the virus tricks our cells.
Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.
MIT duo uses music, videos, and real-world examples to teach students the foundations of artificial intelligence.
PatternEx merges human and machine expertise to spot and respond to hacks.
Through the Undergraduate Research Opportunities Program, students work to build AI tools with impact.
Text-generating tool pinpoints and replaces specific information in sentences while retaining humanlike grammar and style.
Model tags road features based on satellite images, to improve GPS navigation in places with limited map data.
Models that map these relationships based on patient data require fine-tuning for certain conditions, study shows.
Machine-learning system should enable developers to improve computing efficiency in a range of applications.
The ObjectNet dataset compiled by scientists from MIT and IBM is testing the limits of AI vision.
MIT and IBM researchers have developed a new dataset aimed at improving how AI systems identify objects. "We don’t want them to only recognize what is very common," says MIT's Boris Katz. "We want [a robot] to recognize a chair that is upside down on the floor and not say it is a backpack."
Objects are posed in varied positions and shot at odd angles to spur new AI techniques.
Robotic boats could more rapidly locate the most valuable sampling spots in uncharted waters.
Model alerts driverless cars when it’s safest to merge into traffic at intersections with obstructed views.
Navigation method may speed up autonomous last-mile delivery.
An artificial intelligence model developed at MIT shows in striking detail what makes some images stick in our minds.
Systems “learn” from novel dataset that captures how pushed objects move, to improve their physical interactions with new objects.
Research aims to make it easier for self-driving cars, robotics, and other applications to understand the 3D world.
Model could recreate video from motion-blurred images and “corner cameras,” may someday retrieve 3D data from 2D medical images.
Connected devices can now share position information, even in noisy, GPS-denied areas.
Commercial cloud service providers give artificial intelligence computing at MIT a boost.
Task force calls for bold public and private action to harness technology for shared prosperity.
MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.
Model replaces the laborious process of annotating massive patient datasets by hand.
Two longtime friends explore how computer vision systems go awry.
A course that combines machine learning and health care explores the promise of applying artificial intelligence to medicine.
System lets nonspecialists use machine-learning models to make predictions for medical research, sales, and more.
System helps machine-learning models glean training information for diagnosing and treating brain conditions.
Researchers combine deep learning and symbolic reasoning for a more flexible way of teaching computers to program.
Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.
MIT startup Inkbit is overcoming traditional constraints to 3-D printing by giving its machines “eyes and brains.”
Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.
Researchers submit deep learning models to a set of psychology tests to see which ones grasp key linguistic rules.
Signals help neural network identify objects by touch; system could aid robotics and prosthetics design.
In helping envision the MIT Schwarzman College of Computing, working group is focusing on ethical and societal questions.
Working group studies options for creating a new set of faculty hires for MIT’s new college.
MIT Quest for Intelligence-sponsored undergraduate research projects demystify AI.
New tools can find patterns in vast online data to track and identify users on illicit forums.
New method quickly detects instances when neural networks make mistakes they shouldn’t.
Machine learning reveals metabolic pathways disrupted by the drugs, offering new targets to combat resistance.
In some cases, radio frequency signals may be more useful for caregivers than cameras or other data-collection methods.
MIT CSAIL project shows the neural nets we typically train contain smaller “subnetworks” that can learn just as well, and often faster.
Algorithm stitches multiple datasets into a single “panorama,” which could provide new insights for medical and biological studies.
Data-sampling method makes “sketches” of unwieldy biological datasets while still capturing the full diversity of cell types.
Projects will develop new AI technologies that detect and prevent diseases.
A neural network can read scientific papers and render a plain-English summary.
Machine learning can reveal optimal growing conditions to maximize taste and other features.
Counting search queries isn’t easy, but MIT CSAIL’s new LearnedSketch system for “frequency-estimation” aims to help.
Researchers combine statistical and symbolic artificial intelligence techniques to speed learning and improve transparency.
Technique could improve machine-learning tasks in protein design, drug testing, and other applications.
Master’s student and Marshall Scholar Kyle Swanson uses computer science to help make drug development more efficient.
Research projects show creative ways MIT students are connecting computing to other fields.
Final day of the MIT Schwarzman College of Computing celebration explores enthusiasm, caution about AI’s rising prominence in society.
Stephen A. Schwarzman and MIT President L. Rafael Reif discuss the Institute’s historic new endeavor.
Measurements could help scientists develop better designs for a bioartificial pancreas.
Alumnus and founding dean of Cornell Tech in New York City will return to MIT this summer.
As machine learning expands into climate modeling, EAPS Associate Professor Paul O’Gorman answers what that looks like and why it's important now.
President Reif calls for federal funding, focused education to address “opportunity and threat” of AI
In Financial Times op-ed, MIT president says higher education must teach students to be “AI bilingual.”
MIT designers, researchers, and students collaborate with The Metropolitan Museum of Art and Microsoft to improve the connection between people and art.
Researchers pinpoint the “neurons” in machine-learning systems that capture specific linguistic features during language-processing tasks.
An algorithm that teaches robot agents how to exchange advice to complete a task helps them learn faster.
Neural network assimilates multiple types of health data to help doctors make decisions with incomplete information.
MIT “Policy Congress” examines the complex terrain of artificial intelligence regulation.
Hackathons promote doctor-data scientist collaboration and expanded access to electronic medical-records to improve patient care.
Vinod Vaikuntanathan aims to improve encryption in a world with growing applications and evolving adversaries.
CSAIL's new RePaint system aims to faithfully recreate your favorite paintings using deep learning and 3-D printing.
MIT AI Ethics Reading Group was founded by students who saw firsthand how technology developed with good intentions could be problematic.
Model predicts whether ER patients suffering from sepsis urgently need a change in therapy.
MIT Energy Initiative Director Robert Armstrong offers his perspective on the takeaways from MITEI’s annual research conference.
Neural network that securely finds potential drugs could encourage large-scale pooling of sensitive data.
Gift of $350 million establishes the MIT Stephen A. Schwarzman College of Computing, an unprecedented, $1 billion commitment to world-changing breakthroughs and their ethical application.
Inspired by its tradition of leadership in the fields of artificial intelligence and biological intelligence, MIT has established new Institute-wide efforts committed to the convergence of science and engineering on the problem of intelligence.
Abdul Latif Jameel Clinic for Machine Learning in Health at MIT aims to revolutionize disease prevention, detection, and treatment
A key part of the MIT Quest for Intelligence, J-Clinic builds on MIT expertise across multiple scientific disciplines.
Neural network learns speech patterns that predict depression in clinical interviews.
By training on patients grouped by health status, neural network can better estimate if patients will die in the hospital.
Design is major stepping stone toward portable artificial-intelligence devices.
IBM plans to make a 10-year, $240 million investment to create the MIT–IBM Watson AI Lab in partnership with MIT, where fundamental AI research will be conducted to unlock the potential of AI. Here are 5 key things to know about the new Lab.