MIT-IBM Watson AI Lab

Face-specific brain area responds to faces even in people born blind

Study finds that the fusiform face area is active when blind people touch 3D models of faces.

August 26, 2020

Shrinking deep learning’s carbon footprint

Through innovation in software and hardware, researchers move to reduce the financial and environmental costs of modern artificial intelligence.

August 7, 2020

A close-up view of a new neuromorphic “brain-on-a-chip” that includes tens of thousands of memristors, or memory transistors.

Engineers put tens of thousands of artificial brain synapses on a single chip

The design could advance the development of small, portable AI devices.

June 8, 2020

Students participating in MIT Quest for Intelligence-funded UROP projects include: (clockwise from top left) Alon Kosowsky-Sachs, Isaac Wolverton, Kuan Wei Huang, and Karen Gu.

Undergraduates develop next-generation intelligence tools

UROP students explore applications in robotics, health care, language understanding, and nuclear engineering.

May 26, 2020

White blood cells are among the first to mount an attack against sepsis, a deadly complication of Covid-19. In a project led by MIT Professor Daniela Rus, researchers are developing a machine learning system to detect an activated immune response to sepsis which could lead to earlier, more aggressive treatment. Here, a white blood cell attacks malaria.

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.

May 19, 2020

MIT researchers have proposed a technique for shrinking deep learning models that they say is simpler and produces more accurate results than state-of-the-art methods. It works by retraining the smaller, pruned model at its faster, initial learning rate.

A foolproof way to shrink deep learning models

Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.

April 30, 2020

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

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 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

A crash course in deep learning organized and taught by grad students Alexander Amini (right) and Ava Soleimany reaches more than 350 MIT students each year; more than a million other people have watched their lectures online over the past three years.

Bringing deep learning to life

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

February 24, 2020

Several dozen students participated in the Green AI Hackathon, co-sponsored by the MIT Research Computing Project and MIT-IBM Watson AI Lab.

Brainstorming energy-saving hacks on Satori, MIT’s new supercomputer

Three-day hackathon explores methods for making artificial intelligence faster and more sustainable.

February 11, 2020

A PhD student in the MIT Department of Electrical Engineering and Computer Science, Natalie Lao has co-founded startups aimed at democratizing artificial intelligence and using AI to protect democracy by fighting false and misleading information.

Demystifying artificial intelligence

Doctoral candidate Natalie Lao wants to show that anyone can learn to use AI to make a better world.

January 29, 2020

In a new study, researchers at MIT and IBM combine three popular text-analysis tools — topic modeling, word embeddings, and optimal transport — to compare thousands of documents per second. Here, they show that their method (left) clusters newsgroup posts by category more tightly than a competing method.

Finding a good read among billions of choices

As natural language processing techniques improve, suggestions are getting speedier and more relevant.

December 20, 2019

“We believe that AI plays a key role now, and in the future development of the region, if it’s used in the right way,” says Omar Costilla Reyes, one of four MIT graduate students working to help Latin America adopt artificial intelligence technologies. Pictured here (left to right) are Costilla Reyes, Emilia Simison, Pedro Antonio Colon-Hernandez, and Guillermo Bernal.

Students push to speed up artificial intelligence adoption in Latin America

To help the region catch up, students organize summit to bring Latin policymakers and researchers to MIT.

November 19, 2019

A new tool reveals what AI models leave out in recreating a scene. Here, a GAN, or generative adversarial network, has dropped the pair of newlyweds from its reconstruction (right) of the photo it was asked to draw (left).

Visualizing an AI model’s blind spots

New tool highlights what generative models leave out when reconstructing a scene.

November 8, 2019

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