Suggestions or feedback?

Browse By

Topics

View All →

Explore:

Departments

View All →

Explore:

Centers, Labs, & Programs

View All →

Explore:

Schools

View all news coverage of MIT in the media →

Listen to audio content from MIT News →

Close

Topic

Artificial intelligence

Download RSS feed: News Articles / In the Media / Audio

MIT researchers have developed a new automated AI system with improved computational efficiency and a much smaller carbon footprint. The researchers’ system trains one large neural network comprising many pretrained subnetworks of different sizes that can be tailored to diverse hardware platforms without retraining.

Reducing the carbon footprint of artificial intelligence

MIT system cuts the energy required for training and running neural networks.

April 23, 2020

In this lidar map, AI algorithms have identified roads (red). By pairing this map with OpenStreetMaps, users can plan routes around roads that are deemed impassable and can do so at the scale of an entire sortie, which here covers about 400 square miles.

With lidar and artificial intelligence, road status clears up after a disaster

Automated tools can help emergency managers make decisions, plan routes, and quantify road damage at city scales.

April 21, 2020

Daniela Rus is the director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), deputy dean of research for the MIT Schwarzman College of Computing, and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT.

Professor Daniela Rus named to White House science council

CSAIL director and MIT Schwarzman College of Computing deputy dean of research will serve on the President’s Council of Advisors on Science and Technology.

April 21, 2020

The startup Posh has created chat bots that use conversational memory to hold more natural conversations. Posh’s chat bots are currently used by about a dozen credit unions across a variety of voice and text platforms.

Deploying more conversational chatbots

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

April 17, 2020

To reduce lag times and increase quality in video streaming, mobile gaming, and other web services, researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have designed a congestion-control scheme for time-varying wireless links, such as cellular networks.

Reducing delays in wireless networks

Congestion control system could help streaming video, mobile games, and other applications run more smoothly.

April 9, 2020

A mural of hopes and questions about artificial intelligence from a middle school workshop

Learning about artificial intelligence: A hub of MIT resources for K-12 students

New website offers a combination of learning units, hands-on activities, and mentor guides to foster AI literacy.

April 7, 2020

Left to right: Department of Mathematics Professor Alan Edelman, his co-instructor and family Corgi Philip, and visiting professor and longtime Julia lab collaborator David Sanders have altered their computational thinking course to encourage input on COVID-19 responses.

Computational thinking class enables students to engage in Covid-19 response

Nearly 300 students join an open course that applies data science, artificial intelligence, and mathematical modeling using the Julia language to study Covid-19.

April 7, 2020

MIT Professor Markus Buehler designs new proteins with the help of artificial intelligence. He recently translated the spike protein of the novel coronavirus (SARS-Cov-2) into sound to visualize its vibrational properties, as seen here, which could help in finding ways to stop the virus. Primary colors represent the spike’s three protein chains.

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.

April 2, 2020

An iterative, multi-step process for training a neural network, as depicted at top left, leads to an assessment of the tradeoffs between two competing qualities, as depicted in graph at center. The blue line represents a so-called Pareto front, defining the cases beyond which the materials selection cannot be further improved. This makes it possible to identify specific categories of promising new...

Neural networks facilitate optimization in the search for new materials

Sorting through millions of possibilities, a search for battery materials delivered results in five weeks instead of 50 years.

March 26, 2020

An algorithm designed to predict the biological effects of 800 “inactive” pill ingredients uncovered thousands of previously undocumented effects. In this visualization of the researchers’ results, inactive ingredients are shown in blue and their protein targets, in red. The number of predicted, and yet-to-be-verified, interactions (gray edges) outnumber those documented so far (in black).

“Inactive” pill ingredients could raise the dose of your medication

With help from artificial intelligence, researchers identify hidden power of vitamin A and ordinary chewing gum glaze.

March 17, 2020

An international research team used an advanced neural network machine-learning system to improve the accuracy of tests probing the plastic properties of materials — which can be important in a wide variety of industrial applications.

Deep learning for mechanical property evaluation

New technique allows for more precise measurements of deformation characteristics using nanoindentation tools.

March 16, 2020

Catherine D’Ignazio is the co-author of a new book, “Data Feminism,” published by MIT Press in March 2020.

The elephant in the server room

Catherine D’Ignazio’s new book, “Data Feminism,” examines problems of bias and power that beset modern information.

March 9, 2020

Alexander Madry

“Doing machine learning the right way”

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

March 7, 2020

Roboticists are developing automated robots that can learn new tasks solely by observing humans. At home, you might someday show a domestic robot how to do routine chores.

Showing robots how to do your chores

By observing humans, robots learn to perform complex tasks, such as setting a table.

March 5, 2020

MIT cognitive scientists have developed a computer model of face recognition that performs a series of computations that reverse the steps that a computer graphics program would use to generate a 2D representation of a face.

A new model of vision

Computer model of face processing could reveal how the brain produces richly detailed visual representations so quickly.

March 4, 2020