August 2, 2020 - 1:45 pm
MIT researchers’ new theory illuminates machine learning’s black box.
by Cami Rosso
The resurgence of artificial intelligence (AI) is largely due to advances in pattern-recognition due to deep learning, a form of machine learning that does not require explicit hard-coding. The architecture of deep neural networks is somewhat inspired by the biological brain and neuroscience. Like the biological brain, the inner workings of exactly why deep...
July 21, 2020 - 10:45 am
Recent advances give theoretical insight into why deep learning networks are successful
By Sabbi Lall, McGovern Institute
Deep learning systems are revolutionizing technology around us, from voice recognition that pairs you with your phone to autonomous vehicles that are increasingly able to see and recognize obstacles ahead. But much of this success involves trial and error when it comes to the deep learning networks themselves. A group of MIT...
July 14, 2020 - 8:45 am
The following article is about a science outreach programs organized by the CBMM Outreach Coordinator Mandana Sassanfar with the participation of our Nancy Kanwisher.
The science program for local high school students is remote this year, as MIT instructors create at-home lab experiences.
by Raleigh McElvery | Department of Biology
A kickoff event on June 24 commenced a summer of science for local high school students. Established in 2017 as a...
July 1, 2020 - 12:15 pm
Acoustic and biological constraints shape how we hear harmony across cultures.
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Sabbi Lall | McGovern Institute for Brain Research
Many forms of Western music make use of harmony, or the sound created by certain pairs of notes. A longstanding question is why some combinations of notes are perceived as pleasant while others sound jarring to the ear. Are the combinations we favor a universal phenomenon? Or are they specific to Western...
June 25, 2020 - 1:15 pm
The following story contains direct information on research efforts by CBMM PIs Antonio Torralba and Joshua Tenenbaum released in a jointly authored paper - https://arxiv.org/abs/2004.09476
Music gesture artificial intelligence tool developed at the MIT-IBM Watson AI Lab uses body movements to isolate the sounds of individual instruments.
Kim Martineau | MIT Quest for Intelligence
We listen to music with our ears, but also our eyes,...
June 23, 2020 - 2:00 pm
Zoom
Marco Baroni, Facebook AI Research (Paris) and Catalan Institute for Research and Advanced Studies (Barcelona...
Title:
Is compositionality over-rated? A view from emergent neural network language analysis
Abstract:
Compositionality is the property whereby linguistic expressions that denote new composite meanings are derived by a rule-based combination of expressions denoting their parts. Linguists agree that...
Is compositionality over-rated? A view from emergent neural network language analysis
Abstract:
Compositionality is the property whereby linguistic expressions that denote new composite meanings are derived by a rule-based combination of expressions denoting their parts. Linguists agree that...
June 22, 2020 - 1:15 pm
The following story contains information on infant research conducted by CBMM PI Rebecca Saxe. The Netflix series discussed also features CBMM PI Laura Schulz and her research with toddlers - https://www.netflix.com/babies.
Babies' brains light up when they see someone they love – plus more lessons learned from the show's second season
By Victoria Richards
...Babies’ brains are the same as adult brains.
Rebecca Saxe, Professor of Neuroscience at...
June 9, 2020 - 2:00 pm
Zoom
Hossein Mobahi, Google Research
TITLE:
Improving Generalization Performance by Self-Training and Self-Distillation
ABSTRACT:
In supervised learning we often seek a model which minimizes (to epsilon optimality) a loss function over a training set, possibly subject to some (implicit or explicit) regularization. Suppose you train...
Improving Generalization Performance by Self-Training and Self-Distillation
ABSTRACT:
In supervised learning we often seek a model which minimizes (to epsilon optimality) a loss function over a training set, possibly subject to some (implicit or explicit) regularization. Suppose you train...
June 9, 2020 - 1:30 pm
The following story contains direct information on research efforts by CBMM PI Laura Schulz, CBMM Research Collaborator and Alumnus Julian Jara-Ettinger and a platform that multiple CBMM sponsored research projects participate in.
Children Helping Science, co-led by Professor Laura Schulz, brings research to families, and families to research.
The impact of the Covid-19 pandemic on mobility and contact has prompted a group of researchers to...
May 19, 2020 - 2:30 pm
We’ve built machines that are capable of incredible feats, yet still they have nothing on a baby.
By Will Knight
Elizabeth Spelke, a cognitive psychologist at Harvard, has spent her career testing the world’s most sophisticated learning system—the mind of a baby.
Gurgling infants might seem like no match for artificial intelligence. They are terrible at labeling images, hopeless at mining text, and awful at videogames. Then again, babies can do...
May 19, 2020 - 2:00 pm
Noga Zaslavsky
Title: Efficient compression and linguistic meaning in humans and machines
Abstract: In this talk, I will argue that efficient compression may provide a fundamental principle underlying the human capacity to communicate and reason about meaning, and may help to inform machines with similar...
May 5, 2020 - 4:00 pm
Zoom
Max Tegmark, MIT
Title: AI for physics & physics for AI
Abstract: After briefly reviewing how machine learning is becoming ever-more widely used in physics, I explore how ideas and methods from physics can help improve machine learning, focusing on automated discovery of mathematical formulas from data. I...
April 28, 2020 - 2:00 pm
Zoom
Youssef Mroueh, MIT-IBM Watson AI lab
Title of the talk: Sobolev Independence Criterion: Non-Linear Feature Selection with False Discovery Control.
Abstract: In this talk I will show how learning gradients help us designing new non-linear algorithms for feature selection, black box sampling and also, in understanding neural...
April 21, 2020 - 4:00 pm
Luca Carlone
Abstract:
Spatial perception has witnessed an unprecedented progress in the last decade. Robots are now able to detect objects and create large-scale maps of an unknown environment, which are crucial capabilities for navigation and manipulation. Despite these advances, both researchers and...
Spatial perception has witnessed an unprecedented progress in the last decade. Robots are now able to detect objects and create large-scale maps of an unknown environment, which are crucial capabilities for navigation and manipulation. Despite these advances, both researchers and...
April 21, 2020 - 12:15 pm
Survey from the Saxe Lab aims to measure the toll of social isolation during the Covid-19 pandemic.
Julie Pryor | McGovern Institute for Brain Research
After being forced to relocate from their MIT dorms during the Covid19 crisis, two members of Professor Rebecca Saxe's lab at the McGovern Institute for Brain Research are now applying their psychology skills to study the impact of mandatory relocation and social isolation on mental health.
“When...