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Daron Acemoglu named Institute Professor

Versatile economist awarded MIT’s highest faculty honor.

July 10, 2019

Mingman Zhao, a PhD student in EECS, spoke to the inaugural 6.883/6.S083 class about common issues in using machine learning tools to address problems.

Machine learning for everyone

A new EECS course on applications of machine learning teaches students from a variety of disciplines about one of today’s hottest topics.

July 9, 2019

The GANpaint system developed at MIT can easily add features to an existing image. At left, the original photo of a kitchen; at right, the same kitchen with the addition of a window. Co-author Jun-Yan Zhu believes better understanding of GANs will help researchers be able to better stamp out fakery: “This understanding may potentially help us detect fake images more easily.”

Teaching artificial intelligence to create visuals with more common sense

An MIT/IBM system could help artists and designers make quick tweaks to visuals while also helping researchers identify “fake” images.

July 1, 2019

For years, researchers from MIT and Brown University have been developing an interactive system that lets users drag-and-drop and manipulate data on any touchscreen, including smartphones and interactive whiteboards. Now, they’ve included a tool that instantly and automatically generates machine-learning models to run prediction tasks on that data.

Drag-and-drop data analytics

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

June 27, 2019

Users feed Gen relatively short code defining a target task, and the system automatically generates the results.

New AI programming language goes beyond deep learning

General-purpose language works for computer vision, robotics, statistics, and more.

June 26, 2019

Artist’s impression depicts the conversion of the structure of a protein molecule into a musical passage, as is done in the MIT researchers’ system.

Translating proteins into music, and back

By turning molecular structures into sounds, researchers gain insight into protein structures and create new variations.

June 26, 2019

The MIT Machine Intelligence Community board and executive committee

Want to learn how to train an artificial intelligence model? Ask a friend.

MIT Machine Intelligence Community introduces students to nuts and bolts of machine learning.

June 25, 2019

The 2019 Young AFCEA 40 Under 40 award winners from Lincoln Laboratory are (left to right): Anu Myne, Mark Veillette, Meredith Drennan, and Alexander Stolyarov.

Four 2019 40 Under 40 award winners are from Lincoln Laboratory

The Armed Forces Communications and Electronics Association recognizes innovation and leadership in science and technology.

June 19, 2019

"As an engineer and historian, I’ve been 'bilingual' my entire career,” says David Mindell, the Dibner Professor of the History of Engineering and Manufacturing; professor of aeronautics and astronautics; and co-founder and CEO of Humatics Corporation. “Dual competence is a good model for undergraduates at MIT as well."

3Q: David Mindell on his vision for human-centered robotics

Engineer and historian discusses how the MIT Schwarzman College of Computing might integrate technical and humanistic research and education.

June 18, 2019

Yunzhu Li is a PhD student at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

Teaching artificial intelligence to connect senses like vision and touch

MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.

June 17, 2019

Researchers have developed a flexible way of combining deep learning and symbolic reasoning to teach computers to write short computer programs. Here, Armando Solar-Lezama (left), a professor at CSAIL, speaks with graduate student Maxwell Nye.

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.

June 14, 2019

PhD student Clare Kim studies the history of mathematics and the ways that mathematicians interacted with artists, humanists, and philosophers throughout the 20th century.

A scholar and teacher re-examines moments in the history of STEM

“I love teaching,” says PhD student Clare Kim. “It’s not that I’m just imparting knowledge, but I want [my students] to develop a critical way of thinking.”

June 13, 2019

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.

June 5, 2019

Researchers from MIT and elsewhere have developed an interactive tool that, for the first time, lets users see and control how increasingly popular automated machine-learning (AutoML) systems work.

Cracking open the black box of automated machine learning

Interactive tool lets users see and control how automated model searches work.

May 31, 2019

Phillip Isola is an expert in generative adversarial networks, a form of deep learning that is changing how we look at images and inspiring applications far beyond computer vision. Isola helped organize GANocracy, a day-long workshop at MIT on the art and science of GANs.

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.

May 30, 2019

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