3 Questions: Artificial intelligence for health care equity

Regina Barzilay, Fotini Christia, and Collin Stultz describe how artificial intelligence and machine learning can support fairness, personalization, and inclusiveness in health care.

More transparency and understanding into machine behaviors

A new tool helps humans better understand and develop artificial intelligence models by searching and highlighting representative scenarios.

Researchers’ algorithm designs soft robots that sense

Deep-learning technique optimizes the arrangement of sensors on a robot’s body to ensure efficient operation.

Using artificial intelligence to generate 3D holograms in real-time

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.

Retrofitting MIT’s deep learning “boot camp” for the virtual world

With technology new and old, instructors try to recreate the interactivity of their pre-Covid classroom.

A machine-learning approach to finding treatment options for Covid-19

Researchers develop a system to identify drugs that might be repurposed to fight the coronavirus in elderly patients.

Examining the world through signals and systems

Assistant Professor Cathy Wu aims to help autonomous vehicles fulfill their promise by better understanding how to integrate them into the transportation system.

Robust artificial intelligence tools to predict future cancer 

Researchers created a risk-assessment algorithm that shows consistent performance across datasets from US, Europe, and Asia.

Professor Antonio Torralba elected 2021 AAAI Fellow

EECS faculty head of artificial intelligence and decision making honored for significant and extended contributions to the field of AI.

Making smart thermostats more efficient

A smart thermostat quickly learns to optimize building microclimates for both energy consumption and user preference.

A neural network learns when it should not be trusted

A faster way to estimate uncertainty in AI-assisted decision-making could lead to safer outcomes.

Report outlines route toward better jobs, wider prosperity

MIT Task Force on the Work of the Future identifies ways to align new technologies with durable careers.

System brings deep learning to “internet of things” devices

Advance could enable artificial intelligence on household appliances while enhancing data security and energy efficiency.

Algorithm reduces use of riskier antibiotics for UTIs

Machine learning model predicts probability that a particular urinary tract infection can be treated by specific antibiotics. 

Translating lost languages using machine learning

System developed at MIT CSAIL aims to help linguists decipher languages that have been lost to history.

MIT undergraduates pursue research opportunities through the pandemic

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.

Helping robots avoid collisions

Realtime Robotics has created a controller that helps robots safely move around on the fly.

Making health care more personal

The company Health at Scale uses machine learning to improve outcomes for individual patients.

Six strategic areas identified for shared faculty hiring in computing

New faculty in these areas will connect the MIT Schwarzman College of Computing and a department or school.

Real-time data for a better response to disease outbreaks

The startup Kinsa uses its smart thermometers to detect and track the spread of contagious illness before patients go to the hospital.

Rewriting the rules of machine-generated art

An artificial intelligence tool lets users edit generative adversarial network models with simple copy-and-paste commands.

An automated health care system that understands when to step in

Machine learning system from MIT CSAIL can look at chest X-rays to diagnose pneumonia — and also knows when to defer to a radiologist.

Algorithm finds hidden connections between paintings at the Met

A team from MIT helped create an image retrieval system to find the closest matches of paintings from different artists and cultures.

Faculty receive funding to develop artificial intelligence techniques to combat Covid-19

C3.ai Digital Transformation Institute awards $5.4 million to top researchers to steer how society responds to the pandemic.

What is the Covid-19 data tsunami telling policymakers?

A global team of researchers searches for insights during a weeklong virtual “datathon.”

Identifying a melody by studying a musician’s body language

Music gesture artificial intelligence tool developed at the MIT-IBM Watson AI Lab uses body movements to isolate the sounds of individual instruments.

Machine learning helps map global ocean communities

An MIT-developed technique could aid in tracking the ocean’s health and productivity.

Deep learning accurately stains digital biopsy slides

Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.

Machine-learning tool could help develop tougher materials

Engineers develop a rapid screening system to test fracture resistance in billions of potential materials.

Marshaling artificial intelligence in the fight against Covid-19

The MIT-IBM Watson AI Lab is funding 10 research projects aimed at addressing the health and economic consequences of the pandemic.

Visualizing the world beyond the frame

Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.

Automating the search for entirely new “curiosity” algorithms

Researchers show that computers can “write” algorithms that adapt to radically different environments better than algorithms designed by humans.

AI Could Save the World, If It Doesn’t Ruin the Environment First

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.

Deploying more conversational chatbots

Startup Posh has created chatbots that use “conversational memory” to have more natural exchanges.

Model quantifies the impact of quarantine measures on Covid-19’s spread

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.

Q&A: Markus Buehler on setting coronavirus and AI-inspired proteins to music

Translated into sound, SARS-CoV-2 tricks our ear in the same way the virus tricks our cells.

“Doing machine learning the right way”

Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.

Bringing deep learning to life

MIT duo uses music, videos, and real-world examples to teach students the foundations of artificial intelligence.

A human-machine collaboration to defend against cyberattacks

PatternEx merges human and machine expertise to spot and respond to hacks.

Bringing artificial intelligence into the classroom, research lab, and beyond

Through the Undergraduate Research Opportunities Program, students work to build AI tools with impact.

Automated system can rewrite outdated sentences in Wikipedia articles

Text-generating tool pinpoints and replaces specific information in sentences while retaining humanlike grammar and style.

Using artificial intelligence to enrich digital maps

Model tags road features based on satellite images, to improve GPS navigation in places with limited map data.

How well can computers connect symptoms to diseases?

Models that map these relationships based on patient data require fine-tuning for certain conditions, study shows.

Tool predicts how fast code will run on a chip

Machine-learning system should enable developers to improve computing efficiency in a range of applications.

The mind-bending confusion of ‘hammer on a bed’ shows computer vision is far from solved

The ObjectNet dataset compiled by scientists from MIT and IBM is testing the limits of AI vision.

An Obstacle Course to Make AI Better

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."

This object-recognition dataset stumped the world’s best computer vision models

Objects are posed in varied positions and shot at odd angles to spur new AI techniques.

Autonomous system improves environmental sampling at sea

Robotic boats could more rapidly locate the most valuable sampling spots in uncharted waters.

Better autonomous “reasoning” at tricky intersections

Model alerts driverless cars when it’s safest to merge into traffic at intersections with obstructed views.

Technique helps robots find the front door

Navigation method may speed up autonomous last-mile delivery.

What makes an image memorable? Ask a computer

An artificial intelligence model developed at MIT shows in striking detail what makes some images stick in our minds.

Pushy robots learn the fundamentals of object manipulation

Systems “learn” from novel dataset that captures how pushed objects move, to improve their physical interactions with new objects.

Deep learning with point clouds

Research aims to make it easier for self-driving cars, robotics, and other applications to understand the 3D world.

Recovering “lost dimensions” of images and video

Model could recreate video from motion-blurred images and “corner cameras,” may someday retrieve 3D data from 2D medical images.

System helps smart devices find their position

Connected devices can now share position information, even in noisy, GPS-denied areas.

What a little more computing power can do

Commercial cloud service providers give artificial intelligence computing at MIT a boost.

MIT report examines how to make technology work for society

Task force calls for bold public and private action to harness technology for shared prosperity.

Artificial intelligence could help data centers run far more efficiently

MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.

Automating artificial intelligence for medical decision-making

Model replaces the laborious process of annotating massive patient datasets by hand.

Why did my classifier just mistake a turtle for a rifle?

Two longtime friends explore how computer vision systems go awry.

Want to know what software-driven health care looks like? This class offers some clues.

A course that combines machine learning and health care explores the promise of applying artificial intelligence to medicine.

Drag-and-drop data analytics

System lets nonspecialists use machine-learning models to make predictions for medical research, sales, and more.

From one brain scan, more information for medical artificial intelligence

System helps machine-learning models glean training information for diagnosing and treating brain conditions.

Toward artificial intelligence that learns to write code

Researchers combine deep learning and symbolic reasoning for a more flexible way of teaching computers to program.

Chip design drastically reduces energy needed to compute with light

Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.

A 3-D printer powered by machine vision and artificial intelligence

MIT startup Inkbit is overcoming traditional constraints to 3-D printing by giving its machines “eyes and brains.”

Q&A: Phillip Isola on the art and science of generative models

Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.

Teaching language models grammar really does make them smarter

Researchers submit deep learning models to a set of psychology tests to see which ones grasp key linguistic rules.

Sensor-packed glove learns signatures of the human grasp

Signals help neural network identify objects by touch; system could aid robotics and prosthetics design.

3 Questions: The social implications and responsibilities of computing

In helping envision the MIT Schwarzman College of Computing, working group is focusing on ethical and societal questions.

3 Questions: Faculty appointments and the MIT Schwarzman College of Computing

Working group studies options for creating a new set of faculty hires for MIT’s new college.

Developing artificial intelligence tools for all

MIT Quest for Intelligence-sponsored undergraduate research projects demystify AI.

Artificial intelligence shines light on the dark web

New tools can find patterns in vast online data to track and identify users on illicit forums.

How to tell whether machine-learning systems are robust enough for the real world

New method quickly detects instances when neural networks make mistakes they shouldn’t.

Painting a fuller picture of how antibiotics kill

Machine learning reveals metabolic pathways disrupted by the drugs, offering new targets to combat resistance.

Wireless movement-tracking system could collect health and behavioral data

In some cases, radio frequency signals may be more useful for caregivers than cameras or other data-collection methods.

Smarter training of neural networks

MIT CSAIL project shows the neural nets we typically train contain smaller “subnetworks” that can learn just as well, and often faster.

Merging cell datasets, panorama style

Algorithm stitches multiple datasets into a single “panorama,” which could provide new insights for medical and biological studies.

New approach could accelerate efforts to catalogue vast numbers of cells

Data-sampling method makes “sketches” of unwieldy biological datasets while still capturing the full diversity of cell types.

J-Clinic names 18 grant recipients from across Institute

Projects will develop new AI technologies that detect and prevent diseases.

Can science writing be automated?

A neural network can read scientific papers and render a plain-English summary.

The future of agriculture is computerized

Machine learning can reveal optimal growing conditions to maximize taste and other features.

Machine learning moves popular data elements into a bucket of their own

Counting search queries isn’t easy, but MIT CSAIL’s new LearnedSketch system for “frequency-estimation” aims to help.

Teaching machines to reason about what they see

Researchers combine statistical and symbolic artificial intelligence techniques to speed learning and improve transparency.

Model learns how individual amino acids determine protein function

Technique could improve machine-learning tasks in protein design, drug testing, and other applications.

Using machine learning for medical solutions

Master’s student and Marshall Scholar Kyle Swanson uses computer science to help make drug development more efficient.

Combining artificial intelligence with their passions

Research projects show creative ways MIT students are connecting computing to other fields.

Addressing the promises and challenges of AI

Final day of the MIT Schwarzman College of Computing celebration explores enthusiasm, caution about AI’s rising prominence in society.

For founders of new college of computing, the human element is paramount

Stephen A. Schwarzman and MIT President L. Rafael Reif discuss the Institute’s historic new endeavor.

Oxygen-tracking method could improve diabetes treatment

Measurements could help scientists develop better designs for a bioartificial pancreas.

Dan Huttenlocher named inaugural dean of MIT Schwarzman College of Computing

Alumnus and founding dean of Cornell Tech in New York City will return to MIT this summer.

3Q: Machine learning and climate modeling

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.”

New collaboration sparks global connections to art through artificial intelligence

MIT designers, researchers, and students collaborate with The Metropolitan Museum of Art and Microsoft to improve the connection between people and art.

Putting neural networks under the microscope

Researchers pinpoint the “neurons” in machine-learning systems that capture specific linguistic features during language-processing tasks.

Learning to teach to speed up learning

An algorithm that teaches robot agents how to exchange advice to complete a task helps them learn faster.

Filling the gaps in a patient’s medical data

Neural network assimilates multiple types of health data to help doctors make decisions with incomplete information.

AI, the law, and our future

MIT “Policy Congress” examines the complex terrain of artificial intelligence regulation.

Democratizing artificial intelligence in health care

Hackathons promote doctor-data scientist collaboration and expanded access to electronic medical-records to improve patient care.

Fortifying the future of cryptography

Vinod Vaikuntanathan aims to improve encryption in a world with growing applications and evolving adversaries.

Reproducing paintings that make an impression

CSAIL's new RePaint system aims to faithfully recreate your favorite paintings using deep learning and 3-D printing.

Student group explores the ethical dimensions of artificial intelligence

MIT AI Ethics Reading Group was founded by students who saw firsthand how technology developed with good intentions could be problematic.

Machine-learning system could aid critical decisions in sepsis care

Model predicts whether ER patients suffering from sepsis urgently need a change in therapy.

Q&A: Climate change, tough tech startups, and the future of energy intelligence

MIT Energy Initiative Director Robert Armstrong offers his perspective on the takeaways from MITEI’s annual research conference.

Cryptographic protocol enables greater collaboration in drug discovery

Neural network that securely finds potential drugs could encourage large-scale pooling of sensitive data.

MIT reshapes itself to shape the future

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.

Science as the foundation and future of artificial intelligence

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.

Model can more naturally detect depression in conversations

Neural network learns speech patterns that predict depression in clinical interviews.

Model improves prediction of mortality risk in ICU patients

By training on patients grouped by health status, neural network can better estimate if patients will die in the hospital.

Engineers design artificial synapse for “brain-on-a-chip” hardware

Design is major stepping stone toward portable artificial-intelligence devices.

New MIT-IBM Watson AI Lab: 5 things to know

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.