Artificial intelligence

MIT Professor Regina Barzilay (left) and CSAIL PhD student Tal Schuster are studying detectors of machine-generated text.

Better fact-checking for fake news

New research reveals biases in fake news datasets and improves the use of automatic detectors.

October 17, 2019

A new technique for training video recognition models is up to three times faster than current state-of-the-art methods while improving runtime performance on mobile devices. The work was recently highlighted by Dario Gil (above), director of IBM Research, at the MIT-IBM Watson AI Lab’s AI Research Week in Cambridge, Massachusetts.

Faster video recognition for the smartphone era

MIT and IBM researchers offer a new method to train and run deep learning models more efficiently.

October 11, 2019

Catalia Health uses a personal robot assistant, Mabu, to help patients managing chronic diseases.

Robots help patients manage chronic illness at home

Move over, Alexa and Siri. Talking Mabu robot provides one-to-one support while relaying information to doctors.

October 10, 2019

Left to right: senior research scientist David Clark, graduate student Cecilia Testart, and postdoc Philipp Richter

Using machine learning to hunt down cybercriminals

Model from the Computer Science and Artificial Intelligence Laboratory identifies “serial hijackers” of internet IP addresses.

October 8, 2019

Traditional structure-based representations of the many forms of zeolites, some of which are illustrated here, provide little guidance as to how they can convert to other forms, but a new graph-based system does a much better job.

A new mathematical approach to understanding zeolites

Study of minerals widely used in industrial processes could lead to discovery of new materials for catalysis and filtering.

October 7, 2019

MIT Associate Professor of Materials Science and Engineering Juejun (JJ) Hu

3 Questions: How artificial intelligence is supercharging materials science

Associate Professor Juejun Hu shines a light on the impact machine learning and AI are having on materials science and engineering.

October 3, 2019

The MIT.nano Immersion Lab will provide an array of software and hardware for NCSOFT seed grant recipients and other researchers at MIT who are investigating augmented reality, virtual reality, and the display and analysis of spatially related data.

MIT.nano awards inaugural NCSOFT seed grants for gaming technologies

Five software and hardware projects will launch the MIT.nano Immersion Lab Gaming Program.

September 30, 2019

TX-GAIA is housed inside of a new EcoPOD, manufactured by Hewlett Packard Enterprise, at the site of the Lincoln Laboratory Supercomputing Center in Holyoke, Massachusetts.

Lincoln Laboratory's new artificial intelligence supercomputer is the most powerful at a university

TX-GAIA is tailor-made for crunching through deep neural network operations.

September 27, 2019

Computing and artificial intelligence: Humanistic perspectives from MIT

How the humanities, arts, and social science fields can help shape the MIT Schwarzman College of Computing — and benefit from advanced computing.

September 24, 2019

Worlds orbiting stars other than our sun are “exoplanets,” and they come in many sizes, from gas giants larger than Jupiter to small, rocky planets. This illustration of a "super-Earth" represents the type of planet that the TESS mission aims to find outside our solar system.

Computing and the search for new planets

MIT planetary scientists partner with computer scientists to find exoplanets.

September 23, 2019

In BigSMILES, polymeric fragments are represented by a list of repeating units enclosed by curly brackets. The chemical structures of the repeating units are encoded using normal SMILES syntax, but with additional bonding descriptors that specify how different repeating units are connected to form polymers. This simple design of syntax would enable the encoding of macromolecules over a wide range ...

Notation system allows scientists to communicate polymers more easily

BigSMILES language allows computers and researchers to convey stochastic configurations more clearly.

September 18, 2019

MIT researchers are training a pair of generative adversarial networks, or GANs, to mimic the land, sea, and cloud textures seen in satellite images with the goal of eventually visualizing real-world sea-level rise. It’s one of many artificial intelligence research projects made possible by IBM and Google-donated cloud credits.

What a little more computing power can do

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

September 16, 2019

Using just the first 15 minutes of a patient's electrocardiogram (ECG) signal, an MIT system produces a score that places patients into different risk categories.

Using machine learning to estimate risk of cardiovascular death

CSAIL system uses a patient's ECG signal to estimate potential for cardiovascular death.

September 12, 2019

Researchers from MIT and elsewhere have developed a system that detects pain in patients by analyzing brain activity from a wearable neuroimaging device, which could help doctors diagnose and treat pain in unconscious and noncommunicative patients.

Detecting patients’ pain levels via their brain signals

System could help with diagnosing and treating noncommunicative patients.

September 12, 2019

Course 18C student Sonia Reilly (right) stands with her UROP research advisor, Sai Ravela, in the Department of Earth, Atmospheric and Planetary Sciences, where she worked on a machine learning project this summer.

Computing in Earth science: a non-linear path

UROP student Sonia Reilly studies the math of machine learning to improve predictions of natural disasters.

September 11, 2019

MIT News | Massachusetts Institute of Technology

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