Episode 45: Leonard Susskind on Quantum Information, Quantum Gravity, and Holography
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For decades now physicists have been struggling to reconcile two great ideas from a century ago: general relativity and quantum mechanics. We don’t yet know the final answer, but the journey has taken us to some amazing places. A leader in this quest has been Leonard Susskind, who has helped illuminate some of the most mind-blowing ideas in quantum gravity: the holographic principle, the string theory landscape, black-hole complementarity, and others. He has also become celebrated as a writer, speaker, and expositor of mind-blowing ideas. We talk about black holes, quantum mechanics, and the most exciting new directions in quantum gravity.
Leonard Susskind received his Ph.D. in physics from Cornell University. He is currently the Felix Bloch Professor of Physics at Stanford University. He has made important contributions to numerous ideas in theoretical physics, including string theory, lattice gauge theory, dynamical symmetry breaking, the holographic principle, black hole complementarity, matrix theory, the cosmological multiverse, and quantum information. He is the author of several books, including a series of pedagogical physics texts called The Theoretical Minimum. Among his numerous awards are the J.J. Sakurai Prize and the Oskar Klein Medal.
I let algorithms randomize my life for two years | Max Hawkins
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What if everything in your life was randomized: from the food you ate to the things you did and the places you traveled? Computer scientist Max Hawkins created algorithms to make decisions like these for him -- and got hooked on the experience for two years. He shares how relinquishing choice sent him across the world and opened him up to the beautiful complexity and richness of life. It makes you wonder: What lies just outside your comfort zone?
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Max Hawkins - Mapping Activity Space - Adventures in Randomized Living
This talk is from the 2019 Roguelike Celebration - find out more at
Max Hawkins is an artist and computer scientist based in Los Angeles. For two years he let a randomized computer algorithm make all of his decisions including where to live, what to wear, who to talk to, and what to eat.
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StarTalk Podcast: Cosmic Queries – Black Holes & Dark Energy with Neil deGrasse Tyson, Part II
On this episode of StarTalk Radio, we bring you Part II of Cosmic Queries – Black Holes and Dark Energy. Neil deGrasse Tyson and comic co-host Chuck Nice are answering fan-submitted questions about what we know, and don’t know, about black holes and dark energy.
You’ll hear why a black hole’s consumption of matter does not overpower the evaporation caused by Hawking radiation. Neil tells us what’s actually “evaporating” during Hawking radiation. He also tells us two remarkable facts about black holes that are sure to blow your mind.
We discuss how a spy satellite accidently opened a new branch of astrophysics. Find out more about singularities. We investigate the singularity at the beginning of our universe and Neil explains when string theory needs to be brought to the table. Chuck shares how his son coined the word “ringularity.” We assess the possibility of black holes being used as an intergalactic highway system to connect one galaxy to the next.
Find out more about “white holes.” Discover more about supermassive black holes. We explore the nature of photons: how they can be pulled into black holes if they’re massless and why they travel along the fabric of spacetime. Adventure back in time to Sir Arthur Eddington’s expedition to uncover how light bends around the sun.
We ponder if dark energy and dark matter are “stuff” permeating from another universe into our own. Discover why light is trapped in our galaxy but gravity isn’t. We discuss the likelihood that intelligent life is more advanced than us. Lastly, Neil shares final thoughts on the delicate evolution of the tree of life.
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Science meets pop culture on StarTalk! Astrophysicist & Hayden Planetarium director Neil deGrasse Tyson, his comic co-hosts, guest celebrities & scientists discuss astronomy, physics, and everything else about life in the universe. Keep Looking Up!
Originally aired March 2, 2020.
Data Science & Machine Learning with Python || Demo - 3 || by Mrs. Sasmitha on 07-08-2020 @8:30PM
Data Science & Machine Learning with Python || Demo - 3 || by Mrs. Sasmitha on 07-08-2020 @8:30PM
You an see more Java videos following link:
Java tutorial by durga sir
Java 9 by durga sir
Java 1.8 Version New Features by Durga sir
Adv Java JDBC Tutorial by Durga sir
OCJA 1.8 Java SE 8 Programmer - I (1Z0 - 808 ) By Durga sir
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Max Tegmark—The Future of Life with AI (and Other Powerful Technologies)
March 31, 2015
The Future of Life with AI, Nuclear Weapons, and Other Powerful Technologies
Prof. Max Tegmark will explore how we humans have repeatedly underestimated not only the size of our cosmos (and hence our future opportunities), but also the power of our humans minds to understand it and develop technologies with the power to enrich or extinguish humanity.
Known as “Mad Max” for his unorthodox ideas and passion for adventure, Max Tegmark’s scientific interests range from precision cosmology to the ultimate nature of reality, all explored in his new popular book “Our Mathematical Universe.”
He is an MIT physics professor with more than two hundred technical papers and has featured in dozens of science documentaries. His work with the SDSS collaboration on galaxy clustering shared the first prize in Science magazine’s “Breakthrough of the Year: 2003.” He is also the president of the Future of Life Institute, which is launching a major research program supported by Elon Musk aimed at keeping artificial intelligence beneficial.
Two Years of Living Randomly | Max Hawkins | TEDxVienna
For two years Max let a randomized computer program determine the course of his life. Everything from what he ate and the music he played to the city where he lived was determined by the whim of the computer. The randomizer sent him everywhere from a shopping mall in Japan to a goat farm in rural Slovenia.
He tells the story of his randomly generated life: how he stumbled upon the concept of chance, why it became an obsession, and how he discovered that refusing to choose can be a radical act.
Max Hawkins is an artist and computer scientist working at the boundary between computation and culture. His projects deal with information, chance, automation, and atypical forms of communication. He is a graduate of the Computer Science & Art program at Carnegie Mellon University and an alumnus of Google’s Data Arts Team. Since 2015 he has been nomadic, traveling the world based on the output of a random number generator. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at
Black Holes and Random Matrices - Stephen Shenker
Natifest - September 17, 2016
Black Holes and Random Matrices
by Stephan Shenker
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2011 Ulam Memorial Lectures Part Three: All Watched Over by Machines of Loving Grace
Cognitive Ubiquity: The Evolution of Intelligence on Earth
Sept. 1, 2011
Finally, Krakauer will consider the future of biological intelligence in a world of distributed machine intelligence, where there is a prospect of new cultural mechanisms capable of eclipsing the analytical capabilities of our own species.
Understanding the Limitations of AI: When Algorithms Fail | Timnit Gebru | WiDS 2019
Timnit Gebru, Research Scientist on the Ethical AI Team, Google
Automated decision making tools are currently used in high stakes scenarios. From natural language processing tools used to automatically determine one’s suitability for a job, to health diagnostic systems trained to determine a patient’s outcome, machine learning models are used to make decisions that can have serious consequences on people’s lives. In spite of the consequential nature of these use cases, vendors of such models are not required to perform specific tests showing the suitability of their models for a given task. Nor are they required to provide documentation describing the characteristics of their models, or disclose the results of algorithmic audits to ensure that certain groups are not unfairly treated.
I will show some examples to examine the dire consequences of basing decisions entirely on machine learning based systems, and discuss recent work on auditing and exposing the gender and skin tone bias found in commercial gender classification systems. I will end with the concept of an AI datasheet to standardize information for datasets and pre-trained models, in order to push the field as a whole towards transparency and accountability.
Learn more: widsconference.org
Java Performance Puzzlers by Douglas Hawkins
Everyone worries about performance but few of us have the time to truly understand it. Fortunately, our modern JVMs and CPUs are capable of some amazing performance tricks, but those same tricks only make reasoning about performance that much harder.
In this talk, we'll take a look at some surprising and often unintuitive performance problems and solutions. Not simply with the goal of memorizing solutions but also to better understand the complexity that lies inside both JVMs and CPUs.
Rust and Tell Berlin - July
“Rust and Tell“ is a monthly event to share ideas, and learn about new things in and about Rust. Meet fellow Rustaceans, share your learnings, get motivated and inspired.
#1: 00:06:09 Implementing Fast Route Planning Algorithms in Rust by Payas Rajan
#2: 00:23:24 Rust'N'Games by Stephan Dilly
#3: 00:54:30 To the 90s and Back: Adventures in Rust COM Programming by Ryan Levick
#4: 01:24:20 zbus Announcement by Zeeshan
John Preskill “Quantum Computing and the Entanglement Frontier”
2016 Leigh Page Prize Lecture Series, hosted by Yale Department of Physics and Yale Quantum Institute
John Preskill, Richard P. Feynman Professor of Theoretical Physics, California Institute of Technology, “Quantum Computing and the Entanglement Frontier”
Abstract: The quantum laws governing atoms and other tiny objects seem to defy common sense, and information encoded in quantum systems has weird properties that baffle our feeble human minds. John Preskill will explain why he loves quantum entanglement, the elusive feature making quantum information fundamentally different from information in the macroscopic world. By exploiting quantum entanglement, quantum computers should be able to solve otherwise intractable problems, with far-reaching applications to cryptology, materials, and fundamental physical science. Preskill is less weird than a quantum computer, and easier to understand.
What's the Point of Maths? - with Nira Chamberlain
All around the world children, and even some adults, ask the question: ‘What is the point of mathematics?’. The field of mathematical modelling not only helps answer this question, it can help quench the human thirst for knowledge.
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Dr Nira Chamberlain is President of the Institute of Mathematics and its Applications and was the Winner of the Big Internet Math Off title – World’s Most Interesting Mathematician.
Nira has over 25 years of experience at writing mathematical models/simulation algorithms that solve complex industrial problems. Nira developed mathematical solutions within industries such as the defence, aerospace, automotive and energy sectors. This has included periods in France, the Netherlands, Germany and Israel. During his career he has chaired and organized a mini-symposium at an international mathematical modelling conference.
Nira was the highest new entrant in the 2018 PowerList in at Number 5 and holds the title as the 5th Most Influential Black Person in the UK. This is the first time a mathematician has made into the Top 100 Britain’s most influential people of African and African-Caribbean Heritage. He also made the list in 2019.
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10^500 Parallel Universes: Lecture 1 of Quantum Computation and Information at CMU
Quantum Computation and Quantum Information
Lecture 1: 10^500 Parallel Universes
Carnegie Mellon Course 15-859BB, Fall 2018
Course discussion board at
Email email@example.com for access
Taught by Ryan O'Donnell
Filmed by Dave A. for Panopto (
Thumbnail image by Eels and Ticha Sethapakdi
Replace Humans or Work with Them? | Alonso Vera | Talks at Google
Abstract Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, autonomous vehicles, internet-of-things, and continuing exponential growth in computing power (Moore’s Law). This talk addresses the nature human expertise in this context, arguing that although machine intelligence is starting to yield content that is similar to human expertise (e.g., natural language translation, Watson on Jeopardy), the way that the content is arrived at is different and therefore the ways those capabilities will continue to evolve are different. The design and development of advanced planning and scheduling tools for rover missions to Mars and planning of crew activity on the International Space Station are discussed as a specific example of the interactive nature of human and machine expertise.
Dr. Alonso Vera has been at Ames Research Center for 15 years and is currently Chief of the Human Systems Integration Division. His expertise is in human-computer interaction, info systems, artificial intelligence, and computational human performance modeling. He has led the design, development and deployment of mission software systems across NASA robotic and human space flight missions, including Mars Exploration Rovers, Phoenix Mars Lander, ISS, Constellation, and Exploration Systems. Vera has a BS with First Class Honors from McGill and a Ph.D. from Cornell. He went on to a Post-Doc Fellowship in CS at Carnegie Mellon.
How To Build A Human with Gemma Chan | Artificial Intelligence | Spark
In this programme the world’s leading experts attempt to build an artificial human based on actress Gemma Chan, star of the sci-fi series Humans, for a ground-breaking scientific stunt that will test just how far away we are from ‘synthetic’ humans.
Could science fiction be our reality much sooner than we think?
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Jil Meier: Connectome‐Based Propagation Model in Amyotrophic Lateral Sclerosis
How can a random walker on a network be helpful for patients suffering from amyotrophic lateral sclerosis (ALS)? Clinical trials in ALS continue to rely on survival or clinical functional scales as endpoints, since anatomical patterns of disease spread in ALS are poorly characterized in vivo. In this study, we generated individual brain networks of patients and controls based on cerebral magnetic resonance imaging (MRI) data. Then, we applied a computational model with a random walker to the brain MRI scan of patients to simulate this progressive network degeneration. We observe that computer‐simulated aggregation levels of the random walker mimic true disease patterns in ALS patients. Our results demonstrate the utility of computational network models in ALS to predict disease progression and underscore their potential as a prognostic biomarker.
After presenting this study on characterizing the structural changes in neurodegenerative diseases with network science, I will give an outlook on my new work on characterizing the dynamic changes in brain networks for Parkinson’s disease and counteracting these with (simulated) deep brain stimulation using the neuroinformatics platform The Virtual Brain ( .
Moiya McTier Public Thesis Presentation