# SimonsTV

Our videos can also be found on YouTube.
May. 2022

Leonard Susskind (Stanford University)

https://simons.berkeley.edu/events/quantum-colloquium-black-holes-and-quantum-extended-church-turing-thesis

Quantum Colloquium

A few years ago three computer scientists named Adam Bouland, Bill Fefferman, and Umesh Vazirani, wrote a paper that promises to radically change the way we think about the interiors of black holes. Inspired by their paper I will explain how black holes threaten the QECTT, and how the properties of horizons rescue the thesis, and eventually make predictions for the complexity of extracting information from behind the black hole horizon. I'll try my best to explain enough about black holes to keep the lecture self contained.

Panel featuring Scott Aaronson (UT Austin), Geoffrey Penington (UC Berkeley), and Edward Witten (IAS); Umesh Vazirani (UC Berkeley; moderator). 1:27:30

https://simons.berkeley.edu/events/quantum-colloquium-black-holes-and-quantum-extended-church-turing-thesis

Quantum Colloquium

A few years ago three computer scientists named Adam Bouland, Bill Fefferman, and Umesh Vazirani, wrote a paper that promises to radically change the way we think about the interiors of black holes. Inspired by their paper I will explain how black holes threaten the QECTT, and how the properties of horizons rescue the thesis, and eventually make predictions for the complexity of extracting information from behind the black hole horizon. I'll try my best to explain enough about black holes to keep the lecture self contained.

Panel featuring Scott Aaronson (UT Austin), Geoffrey Penington (UC Berkeley), and Edward Witten (IAS); Umesh Vazirani (UC Berkeley; moderator). 1:27:30

Apr. 2022

Sean Carroll (Caltech and Santa Fe Institute)

https://simons.berkeley.edu/events/causality-program-external-speaker-sean-carroll-caltech-and-santa-fe-institute

Causality

Abstract:

A macroscopic arrow of time can be derived from reversible and time-symmetric fundamental laws if we assume an appropriate notion of coarse-graining and a Past Hypothesis of low entropy at early times. It is an ongoing project to show how familiar aspects of time's arrow, such as the fact that causes precede effects, can be derived from such a formalism. I will argue that the causal arrow arises naturally when we describe macroscopic systems in terms of a causal network, and make some suggestions about how to fit prediction and memory into this framework.

Sean Carroll is a Research Professor of theoretical physics at the California Institute of Technology, and Fractal Faculty at the Santa Fe Institute. He received his Ph.D. in 1993 from Harvard University. His research focuses on foundational questions in quantum mechanics, spacetime, cosmology, emergence, entropy, and complexity, occasionally touching on issues of dark matter, dark energy, symmetry, and the origin of the universe. Carroll is the author of Something Deeply Hidden, The Big Picture, The Particle at the End of the Universe, From Eternity to Here, and Spacetime and Geometry: An Introduction to General Relativity. He has been awarded prizes and fellowships by the National Science Foundation, NASA, the Sloan Foundation, the Packard Foundation, the American Physical Society, the American Institute of Physics, the American Association for the Advancement of Science, the Freedom From Religion Foundation, the Royal Society of London, and the Guggenheim Foundation. Carroll has appeared on TV shows such as The Colbert Report, PBS's NOVA, and Through the Wormhole with Morgan Freeman, and frequently serves as a science consultant for film and television. He is host of the weekly Mindscape podcast. He lives in Los Angeles with his wife, writer Jennifer Ouellette.

https://simons.berkeley.edu/events/causality-program-external-speaker-sean-carroll-caltech-and-santa-fe-institute

Causality

Abstract:

A macroscopic arrow of time can be derived from reversible and time-symmetric fundamental laws if we assume an appropriate notion of coarse-graining and a Past Hypothesis of low entropy at early times. It is an ongoing project to show how familiar aspects of time's arrow, such as the fact that causes precede effects, can be derived from such a formalism. I will argue that the causal arrow arises naturally when we describe macroscopic systems in terms of a causal network, and make some suggestions about how to fit prediction and memory into this framework.

Sean Carroll is a Research Professor of theoretical physics at the California Institute of Technology, and Fractal Faculty at the Santa Fe Institute. He received his Ph.D. in 1993 from Harvard University. His research focuses on foundational questions in quantum mechanics, spacetime, cosmology, emergence, entropy, and complexity, occasionally touching on issues of dark matter, dark energy, symmetry, and the origin of the universe. Carroll is the author of Something Deeply Hidden, The Big Picture, The Particle at the End of the Universe, From Eternity to Here, and Spacetime and Geometry: An Introduction to General Relativity. He has been awarded prizes and fellowships by the National Science Foundation, NASA, the Sloan Foundation, the Packard Foundation, the American Physical Society, the American Institute of Physics, the American Association for the Advancement of Science, the Freedom From Religion Foundation, the Royal Society of London, and the Guggenheim Foundation. Carroll has appeared on TV shows such as The Colbert Report, PBS's NOVA, and Through the Wormhole with Morgan Freeman, and frequently serves as a science consultant for film and television. He is host of the weekly Mindscape podcast. He lives in Los Angeles with his wife, writer Jennifer Ouellette.

13th Innovations in Theoretical Computer Science Conference (ITCS 2022)

Playlist: 26 videos

Jan. 2022

Nika Haghtalab (UC Berkeley)

https://simons.berkeley.edu/talks/learning-and-incentives-part-i

Learning and Games Boot Camp

https://simons.berkeley.edu/talks/learning-and-incentives-part-i

Learning and Games Boot Camp

Playlist: 51 videos

Playlist: 20 videos

Playlist: 6 videos

Mar. 2021

Playlist: 22 videos

Aug. 2020

Alan Malek (DeepMind) & Wouter Koolen (Centrum Wiskunde & Informatica)

https://simons.berkeley.edu/talks/tbd-181

Theory of Reinforcement Learning Boot Camp

https://simons.berkeley.edu/talks/tbd-181

Theory of Reinforcement Learning Boot Camp

Playlist: 11 videos

May. 2020

The Women of Theory of Computer Science rock to our version of I Will Survive!

WIT: https://womenintheory.wordpress.com/

I Will Survive

Lyrics: Avi Wigderson (IAS)

At first I was afraid, I was petrified

I worried I could never fit this proof on just one slide

But then I spent so many nights thinking why it is so long

And I grew strong

And learned exactly what went wrong

A problem wor-thy, of attack

Just proves its worth by vigorously fighting back

I should have used error correction, should have sampled yet again

I should have stayed the course and found there is so much that I can gain

So do come back, problems galore

I am much more ready to attack you than I was before

I’ll fight you guiltless when at work, forget you guiltless when at home

And if you’re fun then in the pastures of the TCS we’ll roam

So I’ll survive, and I will thrive,

By Nash’s equilibrium, there must be balance to my life

I’ve got all my life to live,

And I’ve got all my Math to give

So I’ll survive,

and I will thrive, hey, hey

It took all the strength I had, I was nearly spent,

Trying hard to mend, the errors, in my argument

I put each pigeon in its hole, consulted every oracle

My upper bound

Turned up below my lower bound

Then I came up, with something new

I thought outside the blackbox, found what others never knew

That polynomials with a small degree have small number of roots

That few cryptogra-phic assumptions no one’s likely to dispute

So do come back, problems galore

I am much more ready to attack you than I was before

As I have wit and I have WIT and having both is pretty neat

Indeed a convex combination that is very hard to beat

So I’ll survive, and I will thrive,

Because (in theory, at least) this is a perfect life

You pick the problems that you love

To fit your brain just like a glove

So I’ll survive,

and I will thrive, hey, hey

Singers:

Dahlia Malkhi (Calibra, Facebook)

Elette Boyle (IDC, Israel)

Irit Dveer Dinur (Weizmann Institute, Israel)

Julia Chuzhoy (Toyota Technological Institute at Chicago, USA)

Katrina Ligett (Hebrew University, Israel)

Keren Censor-Hillel (Technion, Israel)

Lisa Zhang (Bell-Labs, USA)

Mary Wooters (Stanford University, USA)

Michal Feldman (Tel-Aviv University, Israel)

Nicole Immorlica (Microsoft Research, New England, USA)

Orna Kupferman (Hebrew University, Israel)

Rebecca Wright (Barnard College, USA)

Ronitt Rubinfeld (MIT, USA)

Shafi Goldwasser (Simons Institute at UC Berkeley, USA)

Shubhangi Saraf (Rutgers University, USA)

Shuchi Chawla (University of Wisconsin, Madison, USA)

Sofya Raskhodnikova (Boston University, USA)

Tal Malkin (Columbia University, USA)

Tal Rabin (Algorand Foundation, USA)

Yael Tauman Kalai (Microsoft Research, New England, USA)

WIT: https://womenintheory.wordpress.com/

I Will Survive

Lyrics: Avi Wigderson (IAS)

At first I was afraid, I was petrified

I worried I could never fit this proof on just one slide

But then I spent so many nights thinking why it is so long

And I grew strong

And learned exactly what went wrong

A problem wor-thy, of attack

Just proves its worth by vigorously fighting back

I should have used error correction, should have sampled yet again

I should have stayed the course and found there is so much that I can gain

So do come back, problems galore

I am much more ready to attack you than I was before

I’ll fight you guiltless when at work, forget you guiltless when at home

And if you’re fun then in the pastures of the TCS we’ll roam

So I’ll survive, and I will thrive,

By Nash’s equilibrium, there must be balance to my life

I’ve got all my life to live,

And I’ve got all my Math to give

So I’ll survive,

and I will thrive, hey, hey

It took all the strength I had, I was nearly spent,

Trying hard to mend, the errors, in my argument

I put each pigeon in its hole, consulted every oracle

My upper bound

Turned up below my lower bound

Then I came up, with something new

I thought outside the blackbox, found what others never knew

That polynomials with a small degree have small number of roots

That few cryptogra-phic assumptions no one’s likely to dispute

So do come back, problems galore

I am much more ready to attack you than I was before

As I have wit and I have WIT and having both is pretty neat

Indeed a convex combination that is very hard to beat

So I’ll survive, and I will thrive,

Because (in theory, at least) this is a perfect life

You pick the problems that you love

To fit your brain just like a glove

So I’ll survive,

and I will thrive, hey, hey

Singers:

Dahlia Malkhi (Calibra, Facebook)

Elette Boyle (IDC, Israel)

Irit Dveer Dinur (Weizmann Institute, Israel)

Julia Chuzhoy (Toyota Technological Institute at Chicago, USA)

Katrina Ligett (Hebrew University, Israel)

Keren Censor-Hillel (Technion, Israel)

Lisa Zhang (Bell-Labs, USA)

Mary Wooters (Stanford University, USA)

Michal Feldman (Tel-Aviv University, Israel)

Nicole Immorlica (Microsoft Research, New England, USA)

Orna Kupferman (Hebrew University, Israel)

Rebecca Wright (Barnard College, USA)

Ronitt Rubinfeld (MIT, USA)

Shafi Goldwasser (Simons Institute at UC Berkeley, USA)

Shubhangi Saraf (Rutgers University, USA)

Shuchi Chawla (University of Wisconsin, Madison, USA)

Sofya Raskhodnikova (Boston University, USA)

Tal Malkin (Columbia University, USA)

Tal Rabin (Algorand Foundation, USA)

Yael Tauman Kalai (Microsoft Research, New England, USA)

Apr. 2020

Theory Shorts is a documentary web series that explores topics from the Simons Institute’s research programs.

Episode 1, “Perception as Inference: The Brain and Computation,” explores the computational processes by which the brain builds visual models of the external world, based on noisy or incomplete data from patterns of light sensed on the retinae.

HOST

Bruno Olshausen

DIRECTOR

Christoph Drösser

EDITOR

Michaelle McGaraghan

PRODUCERS

Kristin Kane

Michaelle McGaraghan

SCIENTIFIC ADVISOR

Shafi Goldwasser

ANIMATORS

Caresse Haaser

Christoph Drösser

Lukas Engelhardt

GRAPHIC DESIGNER

Barry Bödeker

VIDEOGRAPHERS

Drew Mason

Omied Far

Michaelle McGaraghan

Matt Beardsley

PRODUCTION ASSISTANTS

Christine Wang

Bexia Shi

Lior Shavit

THEME MUSIC

“Plastic” by Purple Moons

Courtesy of Marmoset in Portland, Oregon

OTHER MEDIA COURTESY OF

Bruce Damonte

Arash Fazl

Anders Garm

Jean Lorenceau and Maggie Shiffrar

Beau Lotto

A. L. Yarbus

Bruno Olshausen

videocobra / Pond5

BlackBoxGuild / Pond5

nechaevkon / Pond5

DaveWeeks / Pond5

CinematicStockVideo / Pond5

BananaRepublic / Pond5

MicroStockTube / Pond5

shelllink / Pond5

AudioQuattro / Envato Market

HitsLab / Envato Market

FlossieWood / Envato Market

plaincask / Envato Market

MusicDog / Envato Market

Loopmaster / Envato Market

Ryokosan / Envato Market

Images used under license from Shutterstock.com

© Simons Institute for the Theory of Computing, 2019

Episode 1, “Perception as Inference: The Brain and Computation,” explores the computational processes by which the brain builds visual models of the external world, based on noisy or incomplete data from patterns of light sensed on the retinae.

HOST

Bruno Olshausen

DIRECTOR

Christoph Drösser

EDITOR

Michaelle McGaraghan

PRODUCERS

Kristin Kane

Michaelle McGaraghan

SCIENTIFIC ADVISOR

Shafi Goldwasser

ANIMATORS

Caresse Haaser

Christoph Drösser

Lukas Engelhardt

GRAPHIC DESIGNER

Barry Bödeker

VIDEOGRAPHERS

Drew Mason

Omied Far

Michaelle McGaraghan

Matt Beardsley

PRODUCTION ASSISTANTS

Christine Wang

Bexia Shi

Lior Shavit

THEME MUSIC

“Plastic” by Purple Moons

Courtesy of Marmoset in Portland, Oregon

OTHER MEDIA COURTESY OF

Bruce Damonte

Arash Fazl

Anders Garm

Jean Lorenceau and Maggie Shiffrar

Beau Lotto

A. L. Yarbus

Bruno Olshausen

videocobra / Pond5

BlackBoxGuild / Pond5

nechaevkon / Pond5

DaveWeeks / Pond5

CinematicStockVideo / Pond5

BananaRepublic / Pond5

MicroStockTube / Pond5

shelllink / Pond5

AudioQuattro / Envato Market

HitsLab / Envato Market

FlossieWood / Envato Market

plaincask / Envato Market

MusicDog / Envato Market

Loopmaster / Envato Market

Ryokosan / Envato Market

Images used under license from Shutterstock.com

© Simons Institute for the Theory of Computing, 2019

Jul. 2019

Mikhail Belkin (The Ohio State University)

https://simons.berkeley.edu/talks/tbd-65

Frontiers of Deep Learning

https://simons.berkeley.edu/talks/tbd-65

Frontiers of Deep Learning

Feb. 2019

Yuri Tschinkel (Simons Foundation / NYU)

https://simons.berkeley.edu/events/effective-arithmetic-geometry

https://simons.berkeley.edu/events/effective-arithmetic-geometry

Playlist: 20 videos

Jun. 2018

Urmila Mahadev, UC Berkeley

https://simons.berkeley.edu/talks/urmila-mahadev-06-15-18

Challenges in Quantum Computation

https://simons.berkeley.edu/talks/urmila-mahadev-06-15-18

Challenges in Quantum Computation

This workshop will focus on the problem of inferring structure from neuroscience data, including the following specific themes:

Playlist: 13 videos

Apr. 11 – Apr. 15, 2016

Playlist: 28 videos

Jan. 15 – Jan. 18, 2014

Playlist: 16 videos