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CBMM videos marked with a 3PlayMedia have an interactive transcript feature enabled, which appears below the video when playing. Viewers can search for keywords in the video or click on any word in the transcript to jump to that point in the video. When searching, a dark bar with white vertical lines appears below the video frame. Each white line is an occurrence of the searched term and can be clicked on to jump to that spot in the video.

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Common Sense Physics and Structured Representation in the Era of Deep Learning

Recorded:

Mar 2, 2021

Uploaded:

March 3, 2021

Part of

All Captioned Videos, Brains, Minds and Machines Seminar Series

Speaker(s):

Prof. Murray Shanahan, Imperial College London / Google DeepMind

The challenge of endowing computers with common sense remains one of the major obstacles to achieving the sort of general artificial intelligence envisioned by the field’s founders. A large part of human common sense pertains to the physics of the...

Computation and Learning with Assemblies of Neurons

Recorded:

Feb 23, 2021

Uploaded:

February 24, 2021

Part of

All Captioned Videos, Brains, Minds and Machines Seminar Series

Speaker(s):

Santosh Vempala, Georgia Tech

Prof. Santosh Vempala, Georgia Tech Abstract: Despite great advances in ML, and in our understanding of the brain at the level of neurons, synapses, and neural circuits, we still have no satisfactory explanation for the brain's performance in...

Module 2 Research Update

Recorded:

Feb 16, 2021

Uploaded:

February 17, 2021

Part of

All Captioned Videos, CBMM Research

CBMM Speaker(s):

Gabriel Kreiman, Mengmi Zhang, Will Xiao

Speaker(s):

Jie Zheng

Abstracts: Speaker: Mengmi Zhang
Title: The combination of eccentricity, bottom-up, and top-down cues explain conjunction and asymmetric visual search
Abstract: Visual search requires complex interactions between visual processing, eye...

Modular Learning and Reasoning on ARC

Recorded:

Feb 9, 2021

Uploaded:

February 11, 2021

Part of

All Captioned Videos, CBMM Research

CBMM Speaker(s):

Andrzej Banburski, Simon Alford

Abstract: Current machine learning algorithms are highly specialized to whatever it is they are meant to do — e.g. playing chess, picking up objects, or object recognition. How can we extend this to a system that could solve a wide range of problems...

Join the Reach Out Science Communication Challenge!

Recorded:

Jan 6, 2021

Uploaded:

January 7, 2021

Speaker(s):

Museum of Science

Calling All NSF Science and Technology Center Students and Postdocs! Sharpen Your Skills, Share Your Story Would you like to share your science with a wider audience? Brush up your storytelling skills? Ace your virtual presentation game? And... are...