MIT Siegel Family Quest for Intelligence

A new system developed at MIT and Brookhaven National Lab could provide a faster, more reliable and much more energy efficient approach to physical neural networks, by using analog ionic-electronic devices to mimic synapses.

Engineers design a device that operates like a brain synapse

Ion-based technology may enable energy-efficient simulations of the brain’s learning process, for neural network AI systems.

June 19, 2020

An MIT study shows viewers’ attention shifts the longer they gaze at an image. Given just a half-second to look at the photo at left, in online experiments, they focused on the elephant, as shown in this heat map.

What jumps out in a photo changes the longer we look

Researchers capture our shifting gaze in a model that suggests how to prioritize visual information based on viewing duration.

June 17, 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 developed a kind of creativity test for generative models to see how far they can go in visualizing objects in photos from various angles and in different colors. The tool shows how much the model's imagination depends on the variety of images it has seen.

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.

May 6, 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 used machine learning to find entirely new algorithms for encoding exploration. Their machine-designed algorithms outperformed human-designed algorithms on the wide range of simulated tasks and environments shown here.

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.

April 28, 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

School of Science announces 2020 Infinite Mile Awards

Ten staff members recognized for dedication to School of Science and to MIT.

March 16, 2020

“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

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

Students participating in MIT Quest for Intelligence-funded UROP projects include: (clockwise from top left) Nicole Thumma, Joanne Yuan, Julian Viera, Andrei Dumitrescu, Pablo Alejo-Aguirre, and Dolapo Adedokun.

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

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

February 13, 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

MIT Schwarzman College of Computing leadership team (left to right) David Kaiser, Daniela Rus, Dan Huttenlocher, Julie Shah, and Asu Ozdaglar

A college for the computing age

With the initial organizational structure in place, the MIT Schwarzman College of Computing moves forward with implementation.

February 4, 2020

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