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MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015

by MIT OpenCourseWare · 60 videos

Total watch time

1d 22h 30m

at 1× speed · exactly 1 day, 22 hours, 30 minutes, 27 seconds at 1×

1×1d 22h 30m 27s
1.25×1d 13h 12m 22s
1.5×1d 7h 18s
1.75×1d 2h 34m 33s
2×23h 15m 14s
Average video46m 30s
Longest1h 16m 16s
Shortest2m 39s
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About 47 days at an hour a day

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Days

At one hour a day, every day, this playlist takes about 47 days. Turn on JavaScript to plan around your week.

Videos (60)

1d 22h 30m in total · tick what you've watched

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Videos to
Watched
1 Lecture 0: Tomaso Poggio - Introduction to Brains, Minds, and Machines 11:12 2018-04-03
2 Lecture 1.1: Nancy Kanwisher - Human Cognitive Neuroscience 46:09 2018-04-03
3 Lecture 1.2: Gabriel Kreiman - Computational Roles of Neural Feedback 55:18 2018-04-03
4 Lecture 1.3: James DiCarlo - Neural Mechanisms of Recognition Part 1 1:02:37 2018-04-03
5 Lecture 1.4: Neural Mechanisms of Recognition, Part 2 51:20 2018-04-03
6 Lecture 1.5: Winrich Freiwald - Primates, Faces, & Intelligence 59:31 2018-04-03
7 Lecture 1.6: Matt Wilson - Hippocampus, Memory, & Sleep Part 1 51:36 2018-04-03
8 Lecture 1.7: Hippocampus, Memory, & Sleep, Part 2 28:12 2018-04-03
9 Seminar 1: Larry Abbott - Mind in the Fly Brain 52:45 2018-04-03
10 Lecture 2.1: Josh Tenenbaum - Computational Cognitive Science Part 1 1:01:27 2018-04-03
11 Lecture 2.2: Josh Tenenbaum - Computational Cognitive Science Part 2 1:10:12 2018-04-03
12 Lecture 2.3: Josh Tenenbaum - Computational Cognitive Science Part 3 1:06:49 2018-04-03
13 Lecture 3.1: Liz Spelke - Cognition in Infancy (Part 1) 1:03:15 2018-04-03
14 Lecture 3.2: Cognition in Infancy, Part 2 45:27 2018-04-03
15 Lecture 3.3: Alia Martin - Developing an Understanding of Communication 46:18 2018-04-03
16 Lecture 3.4: Laura Schulz - Childrens' Sensitivity to Cost and Value of Information 55:32 2018-04-03
17 Seminar 3: Jessica Sommerville - Infants' Sensitivity to Cost and Benefit 39:11 2018-04-03
18 Lecture 3.5: Josh Tenenbaum - The Child as Scientist 30:27 2018-04-03
19 Unit 3 Debate: Tomer Ullman and Laura Schulz 1:16:16 2018-04-03
20 Lecture 4.1: Shimon Ullman - Development of Visual Concepts 58:03 2018-04-03
21 Lecture 4.2: Shimon Ullman - Atoms of Recognition 49:32 2018-04-03
22 Lecture 4.3. Aude Oliva - Predicting Visual Memory 59:53 2018-04-03
23 Seminar 4.1: Eero Simoncelli: Probing Sensory Representations 56:45 2018-04-03
24 Seminar 4.2: Anmon Shashua - Applications of Vision 56:13 2018-04-03
25 Lecture 5.1: Vision and Language 54:44 2018-04-03
26 Lecture 5.2: Andrei Barbu - From Language to Vision and Back Again 1:05:06 2018-04-03
27 Lecture 5.3: Patrick Winston - Story Understanding 1:00:31 2018-04-03
28 Seminar 5: Tom Mitchell - Neural Representations of Language 46:49 2018-04-03
29 Lecture 6.1: Nancy Kanwisher - Introduction to Social Intelligence 27:49 2018-04-03
30 Lecture 6.2: Ken Nakayama - The Social Mind 47:11 2018-04-03
31 Lecture 6.3: Rebecca Saxe - MVPA: Window on the Mind via fMRI Part 1 52:28 2018-04-03
32 Lecture 6.4: MVPA: Window on the Mind via fMRI, Part 2 34:08 2018-04-03
33 Lecture 7.1: Josh McDermott - Introduction to Audition, Part 1 1:05:51 2018-04-03
34 Lecture 7.2: Josh McDermott - Introduction to Audition, Part 2 45:45 2018-04-03
35 Lecture 7.3: Nancy Kanwisher - Human Auditory Cortex 17:39 2018-04-03
36 Lecture 7.4: Hynek Hermansky - Auditory Perception in Speech Technology, Part 1 1:03:55 2018-04-03
37 Lecture 7.5: Hynek Hermansky - Auditory Perception in Speech Technology, Part 2 1:01:33 2018-04-03
38 Unit 7 Panel: Vision and Audition 1:06:58 2018-04-03
39 Lecture 8.1: Russ Tedrake - MIT's Entry in the DARPA Robotics Challenge 26:30 2018-04-03
40 Lecture 8.2: John Leonard - Mapping, Localization and Self Driving Vehicles 31:02 2018-04-03
41 Lecture 8.3: Tony Prescott - Control Architecture in Mammals and Robots 32:15 2018-04-03
42 Lecture 8.4: Stefanie Tellex - Human-Robot Collaboration 24:03 2018-04-03
43 Lecture 8.5: Giorgio Metta - Introduction to the iCub Robot 34:05 2018-04-03
44 Lecture 8.6: iCub Team - Overview of Research on the iCub Robot 1:05:36 2018-04-03
45 Unit 8 Panel: Robotics 55:09 2018-04-03
46 Lecture 9.1: Tomaso Poggio - iTheory: Visual Cortex & Deep Networks 46:12 2018-04-03
47 Seminar 9: Surya Ganguli - Statistical Physics of Deep Learning 1:03:42 2018-04-03
48 Lecture 9.2: Haim Sompolinksy - Sensory Representations in Deep Networks 53:14 2018-04-03
49 Tutorial 1: Leyla Isik - Introduction to Visual Neuroscience 19:55 2018-04-03
50 Tutorial 3.1: Lorenzo Rosasco - Machine Learning Part 1 58:34 2018-04-03
51 Tutorial 3.2: Lorenzo Rosasco - Machine Learning Part 2 55:04 2018-04-03
52 Tutorial 3.3: Lorenzo Rosasco - Machine Learning Part 3 41:43 2018-04-03
53 Tutorial 4: Ethan Meyers - Understanding Neural Content via Population Decoding 56:22 2018-04-03
54 Tutorial 5.1: Tomer Ullman - Church Programming Language Part 1 52:47 2018-04-03
55 Tutorial 5.2: Tomer Ullman - Church Programming Language Part 2 53:55 2018-04-03
56 Tutorial 6: Tomer Ullman - Amazon Mechanical Turk 41:38 2018-04-03
57 Nick Cheney: Capturing Neural Plasticity in Deep Networks 3:28 2018-04-03
58 Danny Jeck: Impact of Attention on Cortical Models of Visual Recognition 2:39 2018-04-03
59 Alon Baram & Laurie Bayet: Learning to Recognize Digits and Faces from Few Examples 4:21 2018-04-03
60 David Rolnick & Ishita Dasgupta: Modeling Dynamic Memory with Hopfield Networks 3:46 2018-04-03

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