News

February 24, 2020
BEHIND THE PAPER
Moving away from alchemy into the age of science for deep learning
by Andrzej Banburski
Imagine you’re back in elementary school and just took your first statistics course on fitting models to data. One thing you...
February 14, 2020
Professor Tomaso Poggio, Dr. Andrzej Banburski and M.Sc. Qianli Liao from the Center for Brains, Minds and Machines, located at the Massachusetts Institute of Technology, won the first edition of the international Scientific...
February 11, 2020
Researchers develop a more robust machine-vision architecture by studying how human vision responds to changing viewpoints of objects.
Kris Brewer | Center for Brains, Minds and Machines
Suppose you look briefly from a few feet...
connected bright lines forming a brain
January 15, 2020
by Sabbi Lall
Visual art has found many ways of representing objects, from the ornate Baroque period to modernist simplicity. Artificial visual systems are somewhat analogous: from relatively simple beginnings inspired by key...
January 14, 2020
Princeton’s Joshua Peterson and Harvard’s Arturo Deza flew earlier that week to Vancouver, British Columbia for the Neural Information Processing Systems (NeurIPS) conference, the world’s premiere machine learning venue, where...
December 20, 2019
A new algorithm wins multi-player, hidden role games.
Kenneth I. Blum | Center for Brains, Minds and Machines
In the wilds of the schoolyard, alliances and conflicts are in flux every day, amid the screams and laughter. How do...
December 19, 2019
As you read this line, you’re bringing each word into clear view for a brief moment while blurring out the rest, perhaps even ignoring the roar of a leaf blower outside. It may seem like a trivial skill, but it’s actually...
December 12, 2019
Stimuli that sound or look like gibberish to humans are indistinguishable from naturalistic stimuli to deep networks.
Kenneth I. Blum | Center for Brains, Minds and Machines
When your mother calls your name, you know it’s her...
December 10, 2019
Objects are posed in varied positions and shot at odd angles to spur new AI techniques.


Kim Martineau | MIT Quest for Intelligence


Computer vision models have learned to identify objects in photos so accurately that some can...
December 10, 2019
Object recognition models have improved by leaps and bounds over the past decade, but they’ve got a long way to go where accuracy is concerned. That’s the conclusion of a joint team from the Massachusetts Institute of Technology...

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