# click the up-left corner to select videos from the playlist
source: Harvard University 2016年11月22日
From Sea to Changing Sea || Radcliffe Institute
Linda N. Cabot Science Symposium
This symposium focuses on important new research on the changing nature of the world’s oceans and the questions that arise from that change.
The program begins with a study of new data about the formation of oceans and the origins of early life. Speakers then examine how oceans have transformed over climate epochs as water temperatures have fluctuated and ice sheets have formed and melted. Leading scientists and policymakers also consider how human behavior is affecting the seas, and they explore the impact of these shifts on marine life, islands, coastal areas, and climate change overall. The symposium concludes by asking what role the scientific community and others can play in understanding and stewarding this critical global resource.
Early Life in the Oceans || Radcliffe Institute 1:12:38
The Role of Oceans in Climate || Radcliffe Institute 1:22:23
Impact of Sea-Level Rise on Greater Boston || Radcliffe Institute 42:17
Marine Life || Radcliffe Institute 1:23:09
The Future of Oceans || Radcliffe Institute 51:58
2016-12-01
Election 2016
source: Stanford 2016年10月11日
Election 2016 will attempt, with the help of experts, to make sense of an election that defies all historical precedent and to take stock of the health of American democracy.
For more on Election 2016, visit:
http://election2016.stanford.edu
https://medium.com/@election2016stanford
View the entire Election 2016 video series: https://www.youtube.com/playlist?list...
1. Campaign Strategy 1:29:07
2. Existential Security Threats to the United States 1:29:58
3. Inequality and Opportunity 1:31:10
4. Tomorrow’s Workplace 1:30:47
5. Future of Democracy 1:33:11
6. Election Recap 1:33:18
Martha Gillette: Biological Rhythms in Health and Disease (Spring 2013 at U of Illinois)
# click the upper-left icon to select videos from the playlist
source: NanoBio Node 2013年3月2日
Molecular and Cellular Biology 529: Biological Rhythms in Health and Disease
MCB529 2-6-13: Why Do You Sleep at Night? 1:05:19
MCB529 2-13-13: How and Why Do We Sleep? 1:06:37
MCB529 2-20-13: Nocturnal and Diurnal Adaptations 1:23:31
MCB529 2-27-13: Circadian Control of Liver Function 56:31
MCB529 3-6-13: Drugs of Abuse and Circadian Rhythms 1:01:56
MCB529 3-13-13: Circadian Rhythms of the Immune System 58:57
MCB529 4-10-13: Reproductive Rhythms 51:35
source: NanoBio Node 2013年3月2日
Molecular and Cellular Biology 529: Biological Rhythms in Health and Disease
MCB529 2-6-13: Why Do You Sleep at Night? 1:05:19
MCB529 2-13-13: How and Why Do We Sleep? 1:06:37
MCB529 2-20-13: Nocturnal and Diurnal Adaptations 1:23:31
MCB529 2-27-13: Circadian Control of Liver Function 56:31
MCB529 3-6-13: Drugs of Abuse and Circadian Rhythms 1:01:56
MCB529 3-13-13: Circadian Rhythms of the Immune System 58:57
MCB529 4-10-13: Reproductive Rhythms 51:35
AI with Demis Hassabis
source: The RSA 2016年10月20日
AI with Demis Hassabis, co-founder and CEO of DeepMind. How far can AI really take us? Demis Hassabis offers a unique insight from the frontiers of artificial intelligence research, and shares his latest thoughts on AI’s potential to help solve our biggest current and future challenges.
Watch Demis Hassabis, co-founder and CEO of DeepMind, in our latest RSA Spotlight - the edits which take you straight to the heart of the event! Loved this snippet? Watch his full speech here: https://youtu.be/i3lEG6aRGm8 or listen to the full podcast: https://soundcloud.com/the_rsa/artifi...
Follow the RSA on Twitter: https://twitter.com/RSAEvents
Like RSA Events on Facebook: https://www.facebook.com/RSAEventsoff...
Listen to RSA podcasts: https://soundcloud.com/the_rsa
See RSA Events behind the scenes: https://instagram.com/rsa_events/
Can machines read your emotions? - Kostas Karpouzis
source: TED-Ed 2016年11月29日
View full lesson: http://ed.ted.com/lessons/can-machine...
Computers can beat us in board games, transcribe speech, and instantly identify almost any object. But will future robots go further by learning to figure out what we’re feeling? Kostas Karpouzis imagines a future where machines and the people who run them can accurately read our emotional states — and explains how that could allow them to assist us, or manipulate us, at unprecedented scales.
Lesson by Kostas Karpouzis, animation by Lasse Rützou Bruntse.
Hume's Legacy (SchAdvStudy)
# click the up-left corner to select videos from the playlist
source: SchAdvStudy
Hume and Civil Society 1:31:20
Relishing Fine Strokes: From Sentiments to Standards 1:32:27
Hume's Contribution to Psychology 1:23:57
Misunderstanding Hume: The Case of Practical Reason 1:29:04
source: SchAdvStudy
Hume and Civil Society 1:31:20
Relishing Fine Strokes: From Sentiments to Standards 1:32:27
Hume's Contribution to Psychology 1:23:57
Misunderstanding Hume: The Case of Practical Reason 1:29:04
Helen Pilcher: "Bring Back the King: The New Science of De-extinction" |...
source: Talks at Google 2016年11月1日
Helen Pilcher has a PhD in cell biology and is an avid science writer, but she also performs comedy, comperes live events, and trains people to write and talk about science.
She paid Google a visit to talk about de-extinction: Bringing back extinct animals through modern technology. With lots of humor and knowledge she discusses what is possible today, what might be possible in the future, and which of these possibilities we should use. What about certain types of frogs? The woolly mammoth? Or Elvis Presley? And what would be the consequences of bringing back these animals?
Brain-inspired Computing by Karlheinz Meier at Hamburg University
# click the up-left corner to select videos from the playlist
source: Karlheinz Meier 上次更新日期：2016年5月22日
Computer simulations of complex systems provide an opportunity to study their time evolution under user control. Simulations of neural circuits are an established tool in computational neuroscience. Through systematic simplification on spatial and temporal scales they provide important insights in the time evolution of networks which in turn leads to an improved understanding of brain functions like learning, memory or behavior. Simulations of large networks are exploiting the concept of weak scaling where the massively parallel biological network structure is naturally mapped on computers with very large numbers of compute nodes. However, this approach is suffering from fundamental limitations. The power consumption is approaching prohibitive levels and, more seriously, the bridging of time-scales from millisecond to years, present in the neurobiology of plasticity, learning and development is inaccessible to classical computers. In the keynote I will argue that these limitations can be overcome by extreme approaches to weak and strong scaling based on brain-inspired computing architectures.
Bio: Karlheinz Meier received his PhD in physics in 1984 from Hamburg University in Germany. He has more than 25years of experience in experimental particle physics with contributions to 4 major experiments at particle colliders at DESY in Hamburg and CERN in Geneva. For the ATLAS experiment at the Large Hadron Collider (LHC) he led a 15 year effort to design, build and operate an electronics data processing system providing on-the-fly data reduction by 3 orders of magnitude enabling among other achievements the discovery of the Higgs Boson. Following scientific staff positions at DESY and CERN he was appointed full professor of physics at Heidelberg university in 1992. In Heidelberg he co-founded the Kirchhoff-Institute for Physics and a laboratory for the development of microelectronic circuits for science experiments. In particle physics he took a leading international role in shaping the future of the field as president of the European Committee for Future Accelerators (ECFA). Around 2005 he gradually shifted his scientific interests towards large-scale electronic implementations of brain-inspired computer architectures. His group pioneered several innovations in the field like the conception of a description language for neural circuits (PyNN), time-compressed mixed-signal neuromorphic computing systems and wafer-scale integration for their implementation. He led 2 major European initiatives, FACETS and BrainScaleS, that both demonstrated the rewarding interdisciplinary collaboration of neuroscience and information science. In 2009 he was one of the initiators of the European Human Brain Project (HBP) that was approved in 2013. In the HBP he leads the subproject on neuromorphic computing with the goal of establishing brain-inspired computing paradigms as tools for neuroscience and generic methods for inference from large data volumes.
Neuromorphic Computing - Extreme Approaches to weak and strong scaling 1:02:28
From BrainScales to Human Brain Project: Neuromorphic Computing Coming of Age 24:33
Brain science in the information age, Prof. Karlheinz Meier 19:56
Keynote - Karlheinz Meier at SAI Conference 2015 - Neuromorphic Computing in the Human Brain Project 44:53
Karlheinz Meier - The EU Human Brain Project - Scientific foundations and plans (2013) 53:19
Karlheinz Meier - From Ions to Electrons: Physical Models of Brain Circuits 1:27:22
The HBP Mixed Doubles: Computing for Neuroscience and Neuroscience for Computing 47:20
The Human Brain Project SP 9: Neuromorphic Computing Platform 2:39
Das Gehirn als Bausatz 21:24
Talking Heads 4:01
Karlheinz Meier -- Breaking the Wall of Traditional Computing @Falling Walls 2013 14:34
BrainScaleS - Demonstration of the Hybrid Multiscale Facility 9:39
Learning from the brain 2:52
151120 Maier v2 1:06:06
source: Karlheinz Meier 上次更新日期：2016年5月22日
Computer simulations of complex systems provide an opportunity to study their time evolution under user control. Simulations of neural circuits are an established tool in computational neuroscience. Through systematic simplification on spatial and temporal scales they provide important insights in the time evolution of networks which in turn leads to an improved understanding of brain functions like learning, memory or behavior. Simulations of large networks are exploiting the concept of weak scaling where the massively parallel biological network structure is naturally mapped on computers with very large numbers of compute nodes. However, this approach is suffering from fundamental limitations. The power consumption is approaching prohibitive levels and, more seriously, the bridging of time-scales from millisecond to years, present in the neurobiology of plasticity, learning and development is inaccessible to classical computers. In the keynote I will argue that these limitations can be overcome by extreme approaches to weak and strong scaling based on brain-inspired computing architectures.
Bio: Karlheinz Meier received his PhD in physics in 1984 from Hamburg University in Germany. He has more than 25years of experience in experimental particle physics with contributions to 4 major experiments at particle colliders at DESY in Hamburg and CERN in Geneva. For the ATLAS experiment at the Large Hadron Collider (LHC) he led a 15 year effort to design, build and operate an electronics data processing system providing on-the-fly data reduction by 3 orders of magnitude enabling among other achievements the discovery of the Higgs Boson. Following scientific staff positions at DESY and CERN he was appointed full professor of physics at Heidelberg university in 1992. In Heidelberg he co-founded the Kirchhoff-Institute for Physics and a laboratory for the development of microelectronic circuits for science experiments. In particle physics he took a leading international role in shaping the future of the field as president of the European Committee for Future Accelerators (ECFA). Around 2005 he gradually shifted his scientific interests towards large-scale electronic implementations of brain-inspired computer architectures. His group pioneered several innovations in the field like the conception of a description language for neural circuits (PyNN), time-compressed mixed-signal neuromorphic computing systems and wafer-scale integration for their implementation. He led 2 major European initiatives, FACETS and BrainScaleS, that both demonstrated the rewarding interdisciplinary collaboration of neuroscience and information science. In 2009 he was one of the initiators of the European Human Brain Project (HBP) that was approved in 2013. In the HBP he leads the subproject on neuromorphic computing with the goal of establishing brain-inspired computing paradigms as tools for neuroscience and generic methods for inference from large data volumes.
Neuromorphic Computing - Extreme Approaches to weak and strong scaling 1:02:28
From BrainScales to Human Brain Project: Neuromorphic Computing Coming of Age 24:33
Brain science in the information age, Prof. Karlheinz Meier 19:56
Keynote - Karlheinz Meier at SAI Conference 2015 - Neuromorphic Computing in the Human Brain Project 44:53
Karlheinz Meier - The EU Human Brain Project - Scientific foundations and plans (2013) 53:19
Karlheinz Meier - From Ions to Electrons: Physical Models of Brain Circuits 1:27:22
The HBP Mixed Doubles: Computing for Neuroscience and Neuroscience for Computing 47:20
The Human Brain Project SP 9: Neuromorphic Computing Platform 2:39
Das Gehirn als Bausatz 21:24
Talking Heads 4:01
Karlheinz Meier -- Breaking the Wall of Traditional Computing @Falling Walls 2013 14:34
BrainScaleS - Demonstration of the Hybrid Multiscale Facility 9:39
Learning from the brain 2:52
151120 Maier v2 1:06:06
Image Analysis Class (lectures 2013/2015) by Fred Hamprecht at at Universität Heidelberg
# click the upper-left icon to select videos from the playlist
source: Universität Heidelberg 2013年4月19日
The Image Analysis Class 2013 by Prof. Fred Hamprecht. It took place at the HCI / Heidelberg University during the summer term of 2013.
1.1 Introduction - Examples 11:03
1.2 Human early vision 48:45
1.3 Image representations 1:09:20
2.1 Patches in Image Analysis 38:31
2.2 Texture Synthesis 43:58
2.3 Non-Local Means for Image Denoising 37:38
2.4 BM3D for Image Denoising 9:56
3.1 Unitary transformations 12:05
3.2 The Fourier Transform 53:27
3.3 The Discrete Fourier Transform (DFT) 1:05:10
3.4 2D-DFT: Application to Images 40:17
4.1 Fourier Transform 51:22
4.2 Time Frequency Decompositions 35:17
4.3 The Wavelet Transform 1:36:43
5.1 Watershed 53:07
5.2 Maximally Stable Extremal Regions 18:47
5.3 Mathematical Morphology 13:33
5.4 Minkowski Functionals 14:52
6.1 Markov Random Fields (MRFs) 57:16
6.2 Gaussian Markov Random Fields (GMRF) 25:13
6.3 Intrinsic GMRFs (IGMRF) 1:22:31
7.1 Factor Graphs 26:18
7.2 Fields of Experts 1:17:24
7.3 Discrete-Valued MRFs 28:14
7.4 MAP inference via Integer Linear Programming (ILP) 52:35
8.1 Integer Linear Programs (continued) 51:25
8.2 Pseudo Boolean Functions (PBFs) 21:20
8.3 Quadratic PBFs with submodular terms 5:15
8.4 Max-Flow / Min-Cut 29:32
8.5 Graph Cuts 1:05:56
9.1 Introduction 7:32
9.2 Example model: Tracking by assignment 36:13
9.3 Structured Support Vector Machine (structSVM) 56:25
9.4 Structured Learning: Applications 23:15
10.1 Light Fields 1:05:24
10.2 Coded Aperture Imaging 21:50
10.3 Compressive Sensing 21:53
9.1 Markov Random Fields 39:22
9.2 Markov Random Fields (cont.) 37:31
10.1 Branch-and-Bound Method for Integer Linear Programming 45:31
10.2 Interior Point Methods for LPs 44:06
12.1 Markov Random Fields with Non-Binary Random Variables 52:04
12.2 Markov Random Fields with Non-Submodular Pairwise Factors 38:13
13 Solving Tree-Shaped MRFs 43:28
14.1 LP Relaxation in Primal and Dual Space 44:56
14.2 LP Relaxation in Dual Space (cont.) 42:21
15.1 Gaussian Markov Random Fields 43:55
15.2 Gaussian Markov Random Fields (cont.) 44:01
16 Gaussian Markov Random Fields (cont.) 1:08:16
source: Universität Heidelberg 2013年4月19日
The Image Analysis Class 2013 by Prof. Fred Hamprecht. It took place at the HCI / Heidelberg University during the summer term of 2013.
1.1 Introduction - Examples 11:03
1.2 Human early vision 48:45
1.3 Image representations 1:09:20
2.1 Patches in Image Analysis 38:31
2.2 Texture Synthesis 43:58
2.3 Non-Local Means for Image Denoising 37:38
2.4 BM3D for Image Denoising 9:56
3.1 Unitary transformations 12:05
3.2 The Fourier Transform 53:27
3.3 The Discrete Fourier Transform (DFT) 1:05:10
3.4 2D-DFT: Application to Images 40:17
4.1 Fourier Transform 51:22
4.2 Time Frequency Decompositions 35:17
4.3 The Wavelet Transform 1:36:43
5.1 Watershed 53:07
5.2 Maximally Stable Extremal Regions 18:47
5.3 Mathematical Morphology 13:33
5.4 Minkowski Functionals 14:52
6.1 Markov Random Fields (MRFs) 57:16
6.2 Gaussian Markov Random Fields (GMRF) 25:13
6.3 Intrinsic GMRFs (IGMRF) 1:22:31
7.1 Factor Graphs 26:18
7.2 Fields of Experts 1:17:24
7.3 Discrete-Valued MRFs 28:14
7.4 MAP inference via Integer Linear Programming (ILP) 52:35
8.1 Integer Linear Programs (continued) 51:25
8.2 Pseudo Boolean Functions (PBFs) 21:20
8.3 Quadratic PBFs with submodular terms 5:15
8.4 Max-Flow / Min-Cut 29:32
8.5 Graph Cuts 1:05:56
9.1 Introduction 7:32
9.2 Example model: Tracking by assignment 36:13
9.3 Structured Support Vector Machine (structSVM) 56:25
9.4 Structured Learning: Applications 23:15
10.1 Light Fields 1:05:24
10.2 Coded Aperture Imaging 21:50
10.3 Compressive Sensing 21:53
9.1 Markov Random Fields 39:22
9.2 Markov Random Fields (cont.) 37:31
10.1 Branch-and-Bound Method for Integer Linear Programming 45:31
10.2 Interior Point Methods for LPs 44:06
12.1 Markov Random Fields with Non-Binary Random Variables 52:04
12.2 Markov Random Fields with Non-Submodular Pairwise Factors 38:13
13 Solving Tree-Shaped MRFs 43:28
14.1 LP Relaxation in Primal and Dual Space 44:56
14.2 LP Relaxation in Dual Space (cont.) 42:21
15.1 Gaussian Markov Random Fields 43:55
15.2 Gaussian Markov Random Fields (cont.) 44:01
16 Gaussian Markov Random Fields (cont.) 1:08:16
A Universe of Black Holes (at KITP, Jul. 1-Sep.20, 2013)
# click the up-left corner to select videos from the playlist
source: GraduatePhysics 2016年2月16日
Lectures held at KITP, Jul.1-Sep.20, 2013. Note that the talks are rather astro instead of mathematical. Event website: http://online.kitp.ucsb.edu/online/bholes13/
Christian Reisswig - Supermassive Black Hole Binaries in Supermassive Star Collapse 1:04:12
Jillian Bellovary - No accounting for Taste, Black Holes Will Eat Anything 54:58
John Baker - An overview of BH mergers in numerical relativity simulations 1:15:30
Chris Carilli - Dust, gas and star formation in z6 quasar host galaxies 1:10:56
Jenny Greene - Black Hole Demographics at Low Mass 57:27
Julie Comerford - Observations of Dual Supermassive Black Holes 56:29
Raffaella Schneider - The growth of the first QSOs, Constraints from the host galaxies 55:39
Kevin Schawinski - Observational constraints on black hole seed formation and early growth 1:10:02
Remco van den Bosch - The extremities of the local black hole scaling relations 51:02
Michael Eracleous - How supermassive black holes alter the evolution of their host galaxy 1:01:58
Richard Mushotzky - Host galaxies of a hard X ray low redshift sample 1:23:54
Kimitake Hayasaki - Tidal disruption flares from stars on bound orbits 43:24
Pau Amaro Seoane - Stellar dynamics around massive black holes 1:07:17
Arif Babul - AGN Feedback in Clusters of Galaxies 1:13:01
Gregory Novak - Issues surrounding implementation of AGN feedback in numerical simulations 56:46
Cole Miller - The universe of black holes that will be revealed with gravitational waves 1:05:44
Jong-Hak Woo - Probing the M-sigma relation using active galaxies 52:52
source: GraduatePhysics 2016年2月16日
Lectures held at KITP, Jul.1-Sep.20, 2013. Note that the talks are rather astro instead of mathematical. Event website: http://online.kitp.ucsb.edu/online/bholes13/
Christian Reisswig - Supermassive Black Hole Binaries in Supermassive Star Collapse 1:04:12
Jillian Bellovary - No accounting for Taste, Black Holes Will Eat Anything 54:58
John Baker - An overview of BH mergers in numerical relativity simulations 1:15:30
Chris Carilli - Dust, gas and star formation in z6 quasar host galaxies 1:10:56
Jenny Greene - Black Hole Demographics at Low Mass 57:27
Julie Comerford - Observations of Dual Supermassive Black Holes 56:29
Raffaella Schneider - The growth of the first QSOs, Constraints from the host galaxies 55:39
Kevin Schawinski - Observational constraints on black hole seed formation and early growth 1:10:02
Remco van den Bosch - The extremities of the local black hole scaling relations 51:02
Michael Eracleous - How supermassive black holes alter the evolution of their host galaxy 1:01:58
Richard Mushotzky - Host galaxies of a hard X ray low redshift sample 1:23:54
Kimitake Hayasaki - Tidal disruption flares from stars on bound orbits 43:24
Pau Amaro Seoane - Stellar dynamics around massive black holes 1:07:17
Arif Babul - AGN Feedback in Clusters of Galaxies 1:13:01
Gregory Novak - Issues surrounding implementation of AGN feedback in numerical simulations 56:46
Cole Miller - The universe of black holes that will be revealed with gravitational waves 1:05:44
Jong-Hak Woo - Probing the M-sigma relation using active galaxies 52:52
Black Holes: Complementarity, Fuzz, or Fire? (at KITP, Aug. 19-30, 2013)
# click the up-left corner to select videos from the playlist
source: GraduatePhysics 2016年2月25日
Lectures held at KITP, Aug. 19-30, 2013.
Event website: http://online.kitp.ucsb.edu/online/fuzzorfire-m13/
Raphael Bousso - The Case for Firewalls 1:01:51
Don Marolf - The Case for Firewalls 1:01:19
Mark van Raamsdonk - Spacetime from Entanglement 1:08:48
Douglas Stanford - Perturbed black hole bridges and the butterfly effect 1:00:51
Juan Maldacena - Spacetime from Entanglement 1:15:03
Leonard Susskind - ER=EPR 1:15:01
Joe Polchinski - Can AdS/CFT see the black hole interior? 1:29:30
David Turton - The Fuzzball Program and Black Hole Complementarity 1:14:30
Samir Mathur - The Black Hole Story in 4 Steps 1:17:45
Iosif Bena - Black hole microstate geometries and the mechanism for hovering above the horizon 1:07:34
Scott Aaronson - Computational complexity underpinnings of the Harlow-Hayden argument 1:17:38
Daniel Harlow - Some comments on the zone-Horizon Decomposition 1:00:43
Jonathan Oppenheim - Quantum Information 1:07:29
John Preskill - Quantum Information 1:19:35
Stephen Hawking - The view from GR 48:54
Ted Jacobson - Boundary unitarity without firewalls 1:22:37
William Unruh - The view from GR 1:17:33
Bob Wald - Information Loss 55:58
Eva Silverstein - String and brane dynamics in black holes and time-dependent AdS/CFT 1:13:28
Lenny Susskind - Inside Black Holes 1:10:33
Erik Verlinde & Herman Verlinde - A=RB 1:25:33
Yasunori Nomura - A=RB 59:43
Suvrat Raju - An Infalling Observer and the Black Hole Information Paradox in AdS/CFT 59:14
David Lowe - Black Hole Complementarity 1:06:44
Tom Banks - Holographic space-time: Is unitarity compatible with information loss? 1:18:31
Steve Giddings - Rescuing Quantum Mechanics and (Approximate) Spacetime 1:15:55
David Berenstein - Numerical Evidence for Firewalls 55:51
Alexei Kitaev - Short talk on black hole problems 44:05
Mark Srednicki - The Eigenstate Thermalization Hypothesis 38:56
Borun Chowdhury - Unitarity: The Cost of Cool Horizons 33:10
Bartek Czech - Short talk on black hole horizon 41:11
Andrea Puhm - Young Black Hole Hair 47:06
source: GraduatePhysics 2016年2月25日
Lectures held at KITP, Aug. 19-30, 2013.
Event website: http://online.kitp.ucsb.edu/online/fuzzorfire-m13/
Raphael Bousso - The Case for Firewalls 1:01:51
Don Marolf - The Case for Firewalls 1:01:19
Mark van Raamsdonk - Spacetime from Entanglement 1:08:48
Douglas Stanford - Perturbed black hole bridges and the butterfly effect 1:00:51
Juan Maldacena - Spacetime from Entanglement 1:15:03
Leonard Susskind - ER=EPR 1:15:01
Joe Polchinski - Can AdS/CFT see the black hole interior? 1:29:30
David Turton - The Fuzzball Program and Black Hole Complementarity 1:14:30
Samir Mathur - The Black Hole Story in 4 Steps 1:17:45
Iosif Bena - Black hole microstate geometries and the mechanism for hovering above the horizon 1:07:34
Scott Aaronson - Computational complexity underpinnings of the Harlow-Hayden argument 1:17:38
Daniel Harlow - Some comments on the zone-Horizon Decomposition 1:00:43
Jonathan Oppenheim - Quantum Information 1:07:29
John Preskill - Quantum Information 1:19:35
Stephen Hawking - The view from GR 48:54
Ted Jacobson - Boundary unitarity without firewalls 1:22:37
William Unruh - The view from GR 1:17:33
Bob Wald - Information Loss 55:58
Eva Silverstein - String and brane dynamics in black holes and time-dependent AdS/CFT 1:13:28
Lenny Susskind - Inside Black Holes 1:10:33
Erik Verlinde & Herman Verlinde - A=RB 1:25:33
Yasunori Nomura - A=RB 59:43
Suvrat Raju - An Infalling Observer and the Black Hole Information Paradox in AdS/CFT 59:14
David Lowe - Black Hole Complementarity 1:06:44
Tom Banks - Holographic space-time: Is unitarity compatible with information loss? 1:18:31
Steve Giddings - Rescuing Quantum Mechanics and (Approximate) Spacetime 1:15:55
David Berenstein - Numerical Evidence for Firewalls 55:51
Alexei Kitaev - Short talk on black hole problems 44:05
Mark Srednicki - The Eigenstate Thermalization Hypothesis 38:56
Borun Chowdhury - Unitarity: The Cost of Cool Horizons 33:10
Bartek Czech - Short talk on black hole horizon 41:11
Andrea Puhm - Young Black Hole Hair 47:06
Dangerous Work: An Evening with Toni Morrison | The New School
source: The New School 2016年10月28日
Sponsored by the Creative Writing Program (http://newschool.edu/writing) at The New School (http://newschool.edu) and PEN America (https://pen.org), a tribute to Toni Morrison as she joins PEN America and The New School to receive the 2016 PEN/Saul Bellow Award for Achievement in American Fiction.
With performances by actress Adepero Oduye, actor Delroy Lindo, jazz pianist Jason Moran, mezzo-soprano Alicia Hall Moran, and Master of Ceremonies Kevin Young, Director of the Schomburg Center for Research in Black Culture.
Location: The Auditorium, Alvin Johnson/J.M. Kaplan Hall
Thursday, October 27, 2016 at 7:00 pm to 8:30 pm
Truth, Absolutism, & Relativism (Simon Blackburn)
source: Philosophical Overdose 2013年1月21日
Simon Blackburn gives a talk on the notion of truth and some of the philosophical approaches, as well as the anti-epistemological postmodern climate. According to one kind of view, our beliefs or statements are true insofar as they "mirror" or correspond to an independent external reality. Others understand the notion of truth differently, as an internal coherence of fitting with other beliefs, or alternatively as what simply works -- a useful tool for coping with the world ("coping not copying" as Richard Rorty liked to say, since he rejected the notion of representation altogether). However, each of these kinds of theories has its own serious problems. In opposition to both absolutism and relativism, Blackburn presents a minimalist or deflationary view, which falls within the pragmatist tradition. He also spends much time discussing the work of Richard Rorty.
This talk was given at the University of Toronto, in 2005. I don't own it.
The Practical Applications of Precognition, Part Three: Psychology, with Marty Rosenblatt
source: New Thinking Allowed 2016年1月29日
Marty Rosenblatt, MS, is a computational physicist who spent his career working in the military and industrial sectors. He is the president of the Applied Precognition Project.Here he introduces the notion of “backwards causality” and suggests various psychological strategies for letting go of resistance and skepticism regarding the possibility of precognition. He describes the quantum mechanical concepts of “non-locality”, “entanglement”, and “zero point energy” and their possible relationship to precognition. He shares his model of “collective consciousness” that helps people in the Applied Precognition Project to accept that their consciousness is far greater than they normally imagine it to be.
New Thinking Allowed host, Jeffrey Mishlove, PhD, is author of The Roots of Consciousness, Psi Development Systems, and The PK Man. Between 1986 and 2002 he hosted and co-produced the original Thinking Allowed public television series. He is the recipient of the only doctoral diploma in "parapsychology" ever awarded by an accredited university (University of California, Berkeley, 1980). He serves as dean of transformational psychology at the University of Philosophical Research. He teaches parapsychology for ministers in training with the Centers for Spiritual Living through the Holmes Institute. He has served as vice-president of the Association for Humanistic Psychology, and is the recipient of its Pathfinder Award for outstanding contributions to the field of human consciousness. He is also past-president of the non-profit Intuition Network, an organization dedicated to creating a world in which all people are encouraged to cultivate and apply their inner, intuitive abilities.
(Recorded on January 6, 2016)
R. KrishnaKumar: Mechanical - Advanced Finite Elements Analysis (IIT Madras)
# click the up-left corner to select videos from the playlist
source: nptelhrd 2009年3月12日
Mechanical - Advanced Finite Elements Analysis by Prof. R. KrishnaKumar, Department of Mechanical Engineering, IIT Madras.
Lecture - 1 49:42
Lecture - 2 50:56
Lecture - 3 50:38
Lecture - 4 50:18
Lecture - 5 50:26
Lecture - 6 50:10
Lecture - 7 48:06
Lecture - 8 48:28
Lecture - 9 45:49
Lecture - 10 47:42
Lecture - 11 49:30
Lecture - 12 48:43
Lecture - 13 49:25
Lecture - 14 49:31
Lecture - 15 48:25
Lecture - 16 48:46
Lecture - 17 49:20
Lecture - 18 45:31
Lecture - 19 49:25
Lecture - 20 48:11
Lecture - 21 51:14
Lecture - 22 46:35
Lecture - 23 45:02
Lecture - 24 48:48
Lecture - 25 47:18
Lecture - 26 48:21
Lecture - 27 47:02
Lecture - 28 48:14
Lecture - 29 50:06
Lecture - 30 49:16
source: nptelhrd 2009年3月12日
Mechanical - Advanced Finite Elements Analysis by Prof. R. KrishnaKumar, Department of Mechanical Engineering, IIT Madras.
Lecture - 1 49:42
Lecture - 2 50:56
Lecture - 3 50:38
Lecture - 4 50:18
Lecture - 5 50:26
Lecture - 6 50:10
Lecture - 7 48:06
Lecture - 8 48:28
Lecture - 9 45:49
Lecture - 10 47:42
Lecture - 11 49:30
Lecture - 12 48:43
Lecture - 13 49:25
Lecture - 14 49:31
Lecture - 15 48:25
Lecture - 16 48:46
Lecture - 17 49:20
Lecture - 18 45:31
Lecture - 19 49:25
Lecture - 20 48:11
Lecture - 21 51:14
Lecture - 22 46:35
Lecture - 23 45:02
Lecture - 24 48:48
Lecture - 25 47:18
Lecture - 26 48:21
Lecture - 27 47:02
Lecture - 28 48:14
Lecture - 29 50:06
Lecture - 30 49:16
Electronics - Coding Theory by Andrew Thangaraj (IIT Madras)
# click the upper-left icon to select videos from the playlist
source: nptelhrd 2012年7月26日
Electronics - Coding Theory by Dr. Andrew Thangaraj, Department of Electronics & Communication Engineering, IIT Madras. For more details on NPTEL visit http://nptel.iitm.ac.in
01 Introduction to Linear Block Codes 1:03:24
02 Properties of Linear Block Codes 53:05
03 Dual of Linear Block Codes 49:16
04 Minimum Distance of Codes 51:00
05 Operations on Codes 50:01
06 Bounds on Code Parameters 50:32
07 Optimal Decoders 49:21
08 Syndrome Decoder, Basics of Finite Fields 1:15:25
09 Construction of Finite Fields 1:15:21
10 Computations in Finite Fields 51:20
11 Codes over Finite Fields, Minimal Polynomials 1:15:22
12 BCH Codes 1:14:52
13 BCH and RS Codes I 1:14:29
14 BCH and RS Codes II 51:54
15 Decoding BCH Codes 1:12:45
16 Decoding RS Codes 49:28
17 Coded Modulation and Soft Decision Decoding 1:12:34
18 Optimal Decoders for BPSK over AWGN 49:40
19 Bitwise MAP Decoder for BPSK over AWGN 1:14:32
20 Bitwise MAP Decoder from the Dual Code 1:14:02
21 Simulating Coded Modulation 49:40
22 Union Bound, Introduction to LDPC Codes 1:15:00
23 LDPC Codes 1:13:12
24 Message Passing, Density Evolution Analysis 51:23
25 Thresholds of LDPC Codes 1:14:29
26 Irregular LDPC Codes 52:26
27 Optimized Irregular LDPC Codes, Soft Message Passing Decoders 50:10
28 Density Evolution for Soft Message Passing Decoding of LDPC Codes 52:24
29 LDPC Codes in Practice 50:40
30 Introduction to Convolutional Codes 50:59
31 Viterbi Decoding of Convolutional Codes 50:09
32 Union Bound, Recursive Convolutional Encoders 51:52
33 Convolutional Codes in Practice 51:27
34 BCJR Decoder 49:36
35 BCJR and Max-Log-MAP Decoder, Introduction to Turbo Codes 50:15
36 Turbo Decoder 48:52
37 Turbo Codes in Practice 52:20
38 Modern Codes 49:33
source: nptelhrd 2012年7月26日
Electronics - Coding Theory by Dr. Andrew Thangaraj, Department of Electronics & Communication Engineering, IIT Madras. For more details on NPTEL visit http://nptel.iitm.ac.in
01 Introduction to Linear Block Codes 1:03:24
02 Properties of Linear Block Codes 53:05
03 Dual of Linear Block Codes 49:16
04 Minimum Distance of Codes 51:00
05 Operations on Codes 50:01
06 Bounds on Code Parameters 50:32
07 Optimal Decoders 49:21
08 Syndrome Decoder, Basics of Finite Fields 1:15:25
09 Construction of Finite Fields 1:15:21
10 Computations in Finite Fields 51:20
11 Codes over Finite Fields, Minimal Polynomials 1:15:22
12 BCH Codes 1:14:52
13 BCH and RS Codes I 1:14:29
14 BCH and RS Codes II 51:54
15 Decoding BCH Codes 1:12:45
16 Decoding RS Codes 49:28
17 Coded Modulation and Soft Decision Decoding 1:12:34
18 Optimal Decoders for BPSK over AWGN 49:40
19 Bitwise MAP Decoder for BPSK over AWGN 1:14:32
20 Bitwise MAP Decoder from the Dual Code 1:14:02
21 Simulating Coded Modulation 49:40
22 Union Bound, Introduction to LDPC Codes 1:15:00
23 LDPC Codes 1:13:12
24 Message Passing, Density Evolution Analysis 51:23
25 Thresholds of LDPC Codes 1:14:29
26 Irregular LDPC Codes 52:26
27 Optimized Irregular LDPC Codes, Soft Message Passing Decoders 50:10
28 Density Evolution for Soft Message Passing Decoding of LDPC Codes 52:24
29 LDPC Codes in Practice 50:40
30 Introduction to Convolutional Codes 50:59
31 Viterbi Decoding of Convolutional Codes 50:09
32 Union Bound, Recursive Convolutional Encoders 51:52
33 Convolutional Codes in Practice 51:27
34 BCJR Decoder 49:36
35 BCJR and Max-Log-MAP Decoder, Introduction to Turbo Codes 50:15
36 Turbo Decoder 48:52
37 Turbo Codes in Practice 52:20
38 Modern Codes 49:33
Semiconductor Device Modeling by S. Karmalkar (IIT Madras)
# click the upper-left icon to select videos from the playlist
source: nptelhrd 2013年11月11日
Electronics - Semiconductor Device Modeling by Prof. S. Karmalkar, Department of Electronics & Communication Engineering, IIT Madras. For more details on NPTEL visit http://nptel.iitm.ac.in
Mod-01 Lec-01 Introduction 49:29
Mod-0 Lec-01 Motivation, Contents and Learning outcomes 51:17
Mod-02 Lec-01 Qualitative model of transport 49:27
Mod-02 Lec-02 Qualitative model of transport 49:52
Mod-02 Lec-03 Qualitative model of transport 56:26
Mod-02 Lec-04 Qualitative model of transport 54:55
Mod-02 Lec-05 Qualitative model of transport 57:57
Mod-03 Lec-01 EM field and transport equations 51:36
Mod-03 Lec-02 EM field and transport equations 53:57
Mod-03 Lec-03 EM field and transport equations 54:49
Mod-03 Lec-04 EM field and transport equations 53:13
Mod03 Lec-05 EM field and transport equations 52:32
Mod-03 Lec-06 EM field and transport equations 50:03
Mod-03 Lec-07 EM field and transport equations 56:22
Mod-03 Lec-08 Semi-classical Bulk Transport -- EM field and Transport Equations 57:01
Mod-04 Lec-01 Drift-diffusion transport model 55:18
Mod-04 Lec-02 Drift-diffusion transport model 50:12
Mod-04 Lec-03 Drift-diffusion transport model 57:51
Mod04 Lec-04 Drift-diffusion transport model 54:30
Mod-04 Lec-05 Drift-diffusion transport model 40:46
Mod-05 Lec-01 Characteristic times and lengths 54:32
Mod-05 Lec-02 Characteristic times and lengths 54:00
Mod-05 Lec-03 Characteristic times and lengths 54:43
Mod-05 Lec-04 Characteristic times and lengths 55:42
Mod 05 Lec-05 Characteristic times and lengths 51:58
Mod-05 Lec-06 Characteristic times and lengths 51:41
Mod-06 Lec-01 Energy band diagrams 55:39
Mod-06 Lec-02 Energy band diagrams 48:11
Mod-06 Lec-03 Energy band diagrams 53:42
Mod-06 Lec-04 Energy band diagrams 55:55
Mod-06 Lec-05 Energy band diagrams 50:34
Mod-06 Lec-06 Energy band diagrams 59:13
Mod-06 Lec-07 Energy band diagrams 52:01
Mod-07 Lec-01 SQEBASTIP -- nine steps of model derivation 53:42
Mod-07 Lec-02 SQEBASTIP -- nine steps of model derivation 53:33
Mod-07 Lec-03 SQEBASTIP -- nine steps of model derivation 56:27
Mod08 Lec-01 Types of device models 56:44
Mod-08 Lec-02 Types of device models 52:09
Mod-09 Lec-01 MOSFET : Device Structures and Characteristics 51:56
Mod-09 Lec-02 MOSFET : Device Structures and Characteristics 49:08
Mod-10 Lec-01 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 52:12
Mod-10 Lec-02 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 56:23
Mod-10 Lec-03 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 50:12
Mod-10 Lec-04 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 43:11
Mod-10 Lec-05 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 44:05
Mod-10 Lec-06 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 51:08
source: nptelhrd 2013年11月11日
Electronics - Semiconductor Device Modeling by Prof. S. Karmalkar, Department of Electronics & Communication Engineering, IIT Madras. For more details on NPTEL visit http://nptel.iitm.ac.in
Mod-01 Lec-01 Introduction 49:29
Mod-0 Lec-01 Motivation, Contents and Learning outcomes 51:17
Mod-02 Lec-01 Qualitative model of transport 49:27
Mod-02 Lec-02 Qualitative model of transport 49:52
Mod-02 Lec-03 Qualitative model of transport 56:26
Mod-02 Lec-04 Qualitative model of transport 54:55
Mod-02 Lec-05 Qualitative model of transport 57:57
Mod-03 Lec-01 EM field and transport equations 51:36
Mod-03 Lec-02 EM field and transport equations 53:57
Mod-03 Lec-03 EM field and transport equations 54:49
Mod-03 Lec-04 EM field and transport equations 53:13
Mod03 Lec-05 EM field and transport equations 52:32
Mod-03 Lec-06 EM field and transport equations 50:03
Mod-03 Lec-07 EM field and transport equations 56:22
Mod-03 Lec-08 Semi-classical Bulk Transport -- EM field and Transport Equations 57:01
Mod-04 Lec-01 Drift-diffusion transport model 55:18
Mod-04 Lec-02 Drift-diffusion transport model 50:12
Mod-04 Lec-03 Drift-diffusion transport model 57:51
Mod04 Lec-04 Drift-diffusion transport model 54:30
Mod-04 Lec-05 Drift-diffusion transport model 40:46
Mod-05 Lec-01 Characteristic times and lengths 54:32
Mod-05 Lec-02 Characteristic times and lengths 54:00
Mod-05 Lec-03 Characteristic times and lengths 54:43
Mod-05 Lec-04 Characteristic times and lengths 55:42
Mod 05 Lec-05 Characteristic times and lengths 51:58
Mod-05 Lec-06 Characteristic times and lengths 51:41
Mod-06 Lec-01 Energy band diagrams 55:39
Mod-06 Lec-02 Energy band diagrams 48:11
Mod-06 Lec-03 Energy band diagrams 53:42
Mod-06 Lec-04 Energy band diagrams 55:55
Mod-06 Lec-05 Energy band diagrams 50:34
Mod-06 Lec-06 Energy band diagrams 59:13
Mod-06 Lec-07 Energy band diagrams 52:01
Mod-07 Lec-01 SQEBASTIP -- nine steps of model derivation 53:42
Mod-07 Lec-02 SQEBASTIP -- nine steps of model derivation 53:33
Mod-07 Lec-03 SQEBASTIP -- nine steps of model derivation 56:27
Mod08 Lec-01 Types of device models 56:44
Mod-08 Lec-02 Types of device models 52:09
Mod-09 Lec-01 MOSFET : Device Structures and Characteristics 51:56
Mod-09 Lec-02 MOSFET : Device Structures and Characteristics 49:08
Mod-10 Lec-01 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 52:12
Mod-10 Lec-02 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 56:23
Mod-10 Lec-03 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 50:12
Mod-10 Lec-04 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 43:11
Mod-10 Lec-05 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 44:05
Mod-10 Lec-06 DC Model of a Large Uniformly Doped Bulk MOSFET: Qualitative Theory 51:08
Subscribe to:
Posts (Atom)