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Confidentiality In A Post Quantum World: the case of LEDAkem and LEDApkc
 
57:50
A Google TechTalk, 2018-12-05, presented by Alessandro Barenghi ABSTRACT: This talk will present LEDAkem and LEDApkc, a key agreement scheme and a public key encryption scheme resistant against attacks with both classical and quantum computers. In this talk I will present the schemes and report recent results on how we can automatically generate key sizes and cryptosystem parameters tailored for a desired security level, providing practical performance figures. About the speaker: Alessandro Barenghi is currently assistant professor at Politecnico di Milano, and one of the proposers of the LEDAkem/LEDApkc cryptoschemes to the NIST post-quantum standardization initiative.
Views: 1128 GoogleTechTalks
Information is Quantum
 
01:02:18
IBM Fellow Charles Bennett on how weird physical phenomena discovered in the early 20th century have taught us the true nature of information, and how to process it.
Views: 15271 IBM Research
Research in Focus: Transforming Machine Learning and Optimization through Quantum Computing
 
26:10
Quantum computing is in its infancy, but Microsoft’s Krysta Svore and Nathan Wiebe talk about quantum techniques as applied to AI challenges. Quantum computing can leverage quantum effects, such as entanglement and quantum interference, to provide solutions to currently unsolvable problems, increasing data security. See more on this video at https://www.microsoft.com/en-us/research/event/faculty-summit-2017/
Views: 3884 Microsoft Research
15. Medical Software
 
01:15:31
MIT 6.858 Computer Systems Security, Fall 2014 View the complete course: http://ocw.mit.edu/6-858F14 Instructor: Kevin Fu In this lecture, Kevin Fu from the University of Michigan delivers a guest lecture on medical software. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 5497 MIT OpenCourseWare
On The Effectiveness Of Secret Key Extraction From Wireless Signal Strength In Real Environment
 
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Secret key establishment is a fundamental requirement for private communication between two entities. Currently, the most common method for establishing a secret key is by using public key cryptography. However, public key cryptography consumes significant amount of computing resources and power which might not be available in certain scenarios (e.g., Sensor networks). More importantly, concerns about the security of public keys in the future have spawned research on methods that do not use public keys. We use real world measurements of received signal strength (RSS) in a variety of environments and settings. Building on the strengths of existing secret key extraction approaches, we develop an environment adaptive secret key generation scheme that uses an adaptive lossy quantizer in conjunction with Cascade-based information reconciliation and privacy amplification.
Cryptography is a systems problem (or) 'Should we deploy TLS'
 
57:49
Cryptography is a systems problem (or) 'Should we deploy TLS' Given by Matthew Green, Johns Hopkins University
Views: 5757 Dartmouth
Alice and Bob
 
05:44
Intro Hello my friends. You are listening to the very first episode of “Explaining Cryptocurrency”. I am Jason Rigden and I am your host. Thank you so much for listening. On this episode we will be talking about the two of most famous people in cryptography. The pair have been working together for decades. The have worked with almost every cryptography researcher in the world. I am of course talking about, Alice and Bob. And the most interesting thing about Alice and Bob is that they are not even real people. But first let me tell you about "LiveOverflow". Interstitial This is not an paid advertisement. I don’t do those on this show. But, I do recognize the power of interstitials to punctuate a podcast episode. I’ll going to be doing short little recommendations, like this, to enable this punctuation. Are you interested in hacking and reverse engineering? Do you want to know more about how computer programs really work? Well there is a really cool YouTube channel called "LiveOverflow" that you should check out. There will be a link in the show notes. "LiveOverflow" has a bunch of videos about analyzing disassemble programs, memory leaks, fuzzing, and other hacking topics. I really love this channel. If you are looking for a YouTube channel about hacking, then I highly recommend checking out "LiveOverflow". Once again there will be a link to the channel in the show notes. Content Ok, back to Alice and Bob. If you are studying cryptocurrency, you need to study cryptography. And if you have studied cryptography you have probably noticed a strange pattern. The names of the people used in examples are always the same. The scenario goes something like this, "Alice wants to send Bob a secret message. So Alice uses Bob's public key to encrypt a message only he can read". Sounds straight forward. Using actual human names helps make the concepts seem less abstract. It is a bit better then saying, "A wants to send B a secret message. So A uses B's public key to encrypt a message only B can read". What is strange though is that everyone uses the same names. It is always Alice and Bob. It is never Ashley and Bruce. Or Adam and Bianca. Well it all started in 1978. An article was published by Rivest, Shamir, and Adleman. It was called, "A method for obtaining digital signatures and public-key cryptosystems". In it they wrote, "For our scenarios we suppose that A and B (also known as Alice and Bob) are two users of a public-key cryptosystem" This was new. Previously most cryptographers just used simple symbols to represent sender and receiver. Simple symbols like A and B. Cognitive load is a funny thing. Cryptography is a very complex topic. It takes quite a bit of mathematical knowledge just to understand how it works. Then there are long complex mathematical equations to understand. Yet people find that Alice is more memorable than A. For students especially, it helps with comprehension. It also helps us create a story. Humans love stories much more than abstractions. Although some might say that every story is an abstraction but that is a topic for another podcast show. So after 1978 the usage of Alice and Bob in academic papers steadily increased. And in 1988 a paper called, "Privacy Amplification by Public Discussion" by Bennet, Brassard, and Robert was published. In it the introduced a new character, Eve. Eve was an eavesdropper. While Alice and Bob are sending messages back and forth in our examples. Eve would be a passive attacker attempting to listen to those messages. Soon Alice, Bob, and Eve would be joined by a whole family of imaginary people. There would be Charlie, Grace, Heidi and many more. Each with their own special functions. For example Charlie is a third participant. So it would be Alice, Bob, and Charlie sending messages to each other. A, B, and C. Another example is Grace. Grace is a representative of the government. So Alice and Bob are sending messages back and forth but Grace has access to a government mandated back door. This lets Grace read all the messages. In real life many law enforcement agencies around the world want to have a back door into all encryption. Specifically, the FBI. They have been using fear tactics to lobby congress for decades. They want a software version of a golden key that will open any lock. Every legitimate cryptographer thinks this is a terrible idea. Anyhow, I'm not going to apologize for getting political here. It's impossible to talk about technology without talking about politics. Especially, when it comes to cryptocurrency. So, back to Alice and Bob and their cadre of associates. These imaginary characters are so popular that they have transcended academia and entered pop culture. Geek culture but pop culture none the less. They have appeared in comics like XKCD, there are t-shirts, and even rap songs. Folks have even written back stories about...
Views: 62 Jason Rigden
How Android Enterprise is Disrupting Mobility (Cloud Next '19)
 
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Enterprise Mobility is not new, but it's not the same old thing either. Mobile apps and architectures have changed, and enterprises are now doing things much differently than ever before. Technology and capabilities will only continue to evolve. Join us to hear from Accenture and Google on how Android Enterprise is disrupting the enterprise workforce and what that means for your organization. Android Enterprise Mobility Disruption → http://bit.ly/2TXnV2W Watch more: Next '19 Mobility & Devices Sessions here → https://bit.ly/Next19MobilityDevices Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform Speaker(s): Nisha Sharma, Eugene Yeh Moderator: Eugene Yeh Session ID: MD108 product:Android Enterprise; fullname:Eugene Yeh;
A Practical Method to Achieve Perfect Secrecy
 
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Electrical and computer engineering professor Amir Khandani explains his research that introduces a novel approach to unconditional security based on using a wireless channel to establish a secret key (one-time pad) between two legitimate parties. Follow us on social media! Twitter: twitter.com/waterlooeng Facebook: facebook.com/uWaterlooEngineering Instagram: instagram.com/uwaterlooeng/ LinkedIn: linkedin.com/groups/56527/ Ten Thousand Coffees: tenthousandcoffees.com/hub/waterlooengineering
LinkedIn Speaker Series:  Erik Brynjolfsson, Andrew McAfee, and Reid Hoffman
 
01:05:49
Interested in what the future will hold? Join us as LinkedIn Co-Founder and Partner at Greylock Reid Hoffman hosts a fireside chat with MIT Sloan School of Management’s faculty members Erik Brynjolfsson and Andrew McAfee. Erik and Andrew are co-authors of the 2014 NYTimes best-selling book, The Second Machine Age, and their latest book, Machine, Platform, Crowd: Harnessing Our Digital Future. Reid, Erik, and Andrew will discuss the fascinating times that we are living in today - a time where a machine can play the strategy game Go better than any human; upstarts like Apple and Google are destroying industry stalwarts such as Nokia; and ideas sourced from the crowd are infinitely more innovative than corporate research labs. Andrew and Erik know what it takes to master this digital-powered shift, and Reid will have a chance to discuss with them how we need to rethink the integration of minds and machines, of products and platforms, and of the core and the crowd.
Views: 4013 LinkedIn
Quantum computer
 
34:56
A quantum computer is a computation device that makes direct use of quantum-mechanical phenomena, such as superposition and entanglement, to perform operations on data. Quantum computers are different from digital computers based on transistors. Whereas digital computers require data to be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses qubits (quantum bits), which can be in superpositions of states. A theoretical model is the quantum Turing machine, also known as the universal quantum computer. Quantum computers share theoretical similarities with non-deterministic and probabilistic computers; one example is the ability to be in more than one state simultaneously. The field of quantum computing was first introduced by Yuri Manin in 1980 and Richard Feynman in 1982. A quantum computer with spins as quantum bits was also formulated for use as a quantum space--time in 1969. As of 2014 quantum computing is still in its infancy but experiments have been carried out in which quantum computational operations were executed on a very small number of qubits. Both practical and theoretical research continues, and many national governments and military funding agencies support quantum computing research to develop quantum computers for both civilian and national security purposes, such as cryptanalysis. This video is targeted to blind users. Attribution: Article text available under CC-BY-SA Creative Commons image source in video
Views: 284 Audiopedia
✅Las billeteras hardware de CRIPTOMONEDAS son ¡HACKEABLES!
 
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#Bitcoin #BTC #Criptomonedas #criptonoticias #criptodivisas En este video hablo sobre una presentación llamada wallet.fail de Computer Chaos Congress en Leipzig, donde intentaron demostrar que las carteras o billeteras hardware eran vulnerables a varios tipos de ataques. Con respecto a Ledger, presentaron 3 rutas de ataque que podrían dar la impresión de que se descubrieron vulnerabilidades críticas en los dispositivos Ledger. Esta presentación demostró finalmente que las Billeteras hardware o Carteras en frio se pueden hackear. Video original: https://www.youtube.com/watch?v=Y1OBIGslgGM Articulo de referencia: https://www.ledger.fr/2018/12/28/chaos-communication-congress-in-response-to-wallet-fails-presentation/ ●▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬● 🙏Muchas gracias por emplear tu tiempo en ver este video y por favor, no olvides darle ME GUSTA & SUSCRIBIRTE. Te veo en el próximo video.✌ Espero que hayas disfrutado el video. Si es así, por favor compártelo con tus amigos y familiares. ●▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬● 🙏Si te sientes [email protected], agradeceré cualquier ayuda a este canal. Gracias! 🙂 ✔️₿ITCOIN 1CKFuEeqzQR8Bv9cvVjtxFbnZkPueiRJwr ✔️ LITECOIN LcmJTKEz4LmZ7j7UaKCFB6zdmH2vKzWWyS ✔️ ETHEREUM 0x4cbe86df99bcd89b2016c3892e52c8fb9d4dc6c8 ✔️XRP rKfzfrk1RsUxWmHimWyNwk8AoWHoFneu4m/ Destination Tag: 963444220 ✔️DASH XukafF46YdoRvgYDHWJQHtFakZvcZtTQjD ✔️PayPal: paypal.me/BitcoinCryptoShow ●▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬● EXCHANGES QUE USO: ▶COINBASE: Por favor, únete usando este link para obtener $10 gratis: https://www.coinbase.com/join/5a3a545... ▶COIMAMA: http://go.coinmama.com/visit/?bta=531... Este es uno de los mejores exchange para comprar Bitcoin y otras Cripto Monedas Principales con TARJETA DE CRÉDITO, en la manera más rápida, fácil y segura! Compra BTC, ETH, XRP, BCH, LTC, ADA, ETC y QTUM en 3 simples pasos en Coinmama. ▶BINANCE: https://www.binance.com/?ref=13180000 Para empezar a comprar Altcoins, Binance ES EL MEJOR exchange de ahi fuera. ●▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬● MIS BILLETERAS DE ALMACENAMIENTO HARDWARE. 🔒 Trezor: https://shop.trezor.io?a=toksfmgl 🔒 Ledger Nano: https://www.ledger.com?r=2964dc525816 🔒 Ellipal: http://order.ellipal.com/?ref=bitcoin... 🔒 CoolWallet: https://coolwallet.io/product/coolwal... ●▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬● 🌎 Sígueme en Twiter: https://twitter.com/EsferaCripto ●▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬● 📌DESCARGO DE RESPONSABILIDAD: No soy un asesor financiero profesional. Todas las inversiones que usted haga son Únicamente responsabilidad suya. Por favor haga su propia investigación. #Bitcoin #BTC #XRP #Criptomonedas #criptonoticias #criptodivisas
Views: 2015 Cripto Esfera
Jeffrey Shapiro
 
01:48:51
Jeffrey H. Shapiro ’67 SM ’68 EE ’69 PhD ’70 Julius A. Stratton Professor of Electrical Engineering and Computer Science Director, Research Laboratory of Electronics Jeffrey Shapiro is the Julius A. Stratton professor of electrical engineering at MIT and the director of the Research Laboratory for Electronics. Professor Shapiro, four-time MIT alumnus, centers his research on the application of communication theory to optical systems. He is best known for his work on the generation, detection, and application of squeezed-state light beams, but he also works in the areas of atmospheric optical communication, coherent laser radar, and quantum information theory.
Quantum computation | Wikipedia audio article
 
54:30
This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Quantum_computing 00:03:09 1 Basics 00:06:07 2 Principles of operation 00:16:16 3 Operation 00:19:07 4 Potential 00:19:15 4.1 Cryptography 00:21:48 4.2 Quantum search 00:24:18 4.3 Quantum simulation 00:24:53 4.4 Quantum annealing and adiabatic optimisation 00:25:31 4.5 Solving linear equations 00:25:55 4.6 Quantum supremacy 00:27:36 5 Obstacles 00:28:20 5.1 Quantum decoherence 00:31:25 6 Developments 00:31:35 6.1 Quantum computing models 00:32:47 6.2 Physical realizations 00:35:35 6.3 Timeline 00:50:51 7 Relation to computational complexity theory Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.9914562960717304 Voice name: en-GB-Wavenet-D "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= Quantum computing is computing using quantum-mechanical phenomena, such as superposition and entanglement. A quantum computer is a device that performs quantum computing. Such a computer is completely different from binary digital electronic computers based on transistors and capacitors. Whereas common digital computing requires that the data be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits or qubits, which can be in superpositions of states. A quantum Turing machine is a theoretical model of such a computer and is also known as the universal quantum computer. The field of quantum computing was initiated by the work of Paul Benioff and Yuri Manin in 1980, Richard Feynman in 1982, and David Deutsch in 1985.As of 2018, the development of actual quantum computers is still in its infancy, but experiments have been carried out in which quantum computational operations were executed on a very small number of quantum bits. Both practical and theoretical research continues, and many national governments and military agencies are funding quantum computing research in additional effort to develop quantum computers for civilian, business, trade, environmental and national security purposes, such as cryptanalysis. Noisy devices with a small number of qubits, also dubbed noisy intermediate-scale quantum (NISQ) devices by John Preskill, have been developed by a number of companies, including IBM, Intel, and Google. IBM has made 5-qubit and 16-qubit quantum computing devices available to the public for experiments via the cloud on the IBM Q Experience. D-Wave Systems has been developing their own version of a quantum computer that uses annealing.Large-scale quantum computers would theoretically be able to solve certain problems much more quickly than any classical computers that use even the best currently known algorithms, like integer factorization using Shor's algorithm (which is a quantum algorithm) and the simulation of quantum many-body systems. There exist quantum algorithms, such as Simon's algorithm, that run faster than any possible probabilistic classical algorithm. A classical computer could in principle (with exponential resources) simulate a quantum algorithm, as quantum computation does not violate the Church–Turing thesis. On the other hand, quantum computers may be able to efficiently solve problems which are not practically feasible on classical computers. A recent review by Mikhail Dyakonov in IEEE Spectrum argues that practical quantum computers are not likely to be implemented. He says: "There is a tremendous gap between the rudimentary but very hard experiments that have been carried out with a few qubits and the extremely developed quantum-computing theory, which relies on manipulating thousands to millions of qubits to calculate anything useful. That gap is not likely to be closed anytime soon."
Views: 10 wikipedia tts
Google Cloud Next '18: Day 2 Next Live Show
 
09:55:23
Join us on July 24-26th to learn about the latest Google Cloud innovations and get an insider's view of Next 18. Featuring: Keynotes, Spotlight Sessions, Showcase demos, keynote recaps, interviews with industry experts, inspirational cloud stories and more. 9.00AM–10.30 AM: Keynote: Bringing the Cloud to You 10.30AM–11.00AM: Interviews with experts, product demos, and the latest news 11.00AM–11.50AM: Transform Work: Driving Culture Change, Productivity, and Efficiency 11.50AM–12.35PM: Interviews with experts, product demos, and the latest news 12.35PM–1.35PM: A Discussion with Two Pioneers of Computer Architecture: John Hennessy, Chairman of Alphabet and David Patterson, Distinguished Engineer, Google 1.35PM–2.30PM: Interviews with experts, product demos, and the latest news. 2.30PM–3.30PM: Customer Keynote: Google Cloud Customer Innovation Series 3.30PM–4.00PM: Interviews with experts, product demos, and the latest news. 4.00PM-4.50PM: Recording: Rethinking Big Data Analytics with Google Cloud 4.50PM–5.15PM: Interviews with experts, product demos, and the latest news 5.15PM–6.05PM: Recording: Cloud AI: How to Get Started Injecting AI Into Your Applications 6.05PM–6.20PM: Interviews with experts, product demos, and the latest news Learn more and view the event schedule → http://g.co/next18 Subscribe to the Google Cloud channel → http://bit.ly/NextSub
Views: 24407 Google Cloud
Week 0
 
47:01
Binary. ASCII. Algorithms. Pseudocode. Source code. Compiler. Object code. Scratch. Statements. Boolean expressions. Conditions. Loops. Variables. Functions. Arrays. Threads. Events.
Views: 564287 CS50
Quantum computing | Wikipedia audio article
 
50:28
This is an audio version of the Wikipedia Article: Quantum computing 00:02:24 1 Basics 00:05:05 2 Principles of operation 00:14:37 3 Operation 00:17:17 4 Potential 00:17:26 4.1 Cryptography 00:19:50 4.2 Quantum search 00:22:11 4.3 Quantum simulation 00:22:43 4.4 Quantum annealing and adiabatic optimisation 00:23:19 4.5 Solving linear equations 00:23:42 4.6 Quantum supremacy 00:25:15 5 Obstacles 00:25:57 5.1 Quantum decoherence 00:28:51 6 Developments 00:29:00 6.1 Quantum computing models 00:30:08 6.2 Physical realizations 00:32:48 6.3 Timeline 00:47:01 7 Relation to computational complexity theory Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. You can find other Wikipedia audio articles too at: https://www.youtube.com/channel/UCuKfABj2eGyjH3ntPxp4YeQ You can upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts "The only true wisdom is in knowing you know nothing." - Socrates SUMMARY ======= Quantum computing is computing using quantum-mechanical phenomena, such as superposition and entanglement. A quantum computer is a device that performs quantum computing. Such a computer is different from binary digital electronic computers based on transistors. Whereas common digital computing requires that the data be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits or qubits, which can be in superpositions of states. A quantum Turing machine is a theoretical model of such a computer and is also known as the universal quantum computer. The field of quantum computing was initiated by the work of Paul Benioff and Yuri Manin in 1980, Richard Feynman in 1982, and David Deutsch in 1985.As of 2018, the development of actual quantum computers is still in its infancy, but experiments have been carried out in which quantum computational operations were executed on a very small number of quantum bits. Both practical and theoretical research continues, and many national governments and military agencies are funding quantum computing research in additional effort to develop quantum computers for civilian, business, trade, environmental and national security purposes, such as cryptanalysis. Noisy devices with a small number of qubits have been developed by a number of companies, including IBM, Intel, and Google. IBM has made 5-qubit and 16-qubit quantum computing devices available to the public for experiments via the cloud on the IBM Q Experience. D-Wave Systems has been developing their own version of a quantum computer that uses annealing.Large-scale quantum computers would theoretically be able to solve certain problems much more quickly than any classical computers that use even the best currently known algorithms, like integer factorization using Shor's algorithm (which is a quantum algorithm) and the simulation of quantum many-body systems. There exist quantum algorithms, such as Simon's algorithm, that run faster than any possible probabilistic classical algorithm. A classical computer could in principle (with exponential resources) simulate a quantum algorithm, as quantum computation does not violate the Church–Turing thesis. On the other hand, quantum computers may be able to efficiently solve problems which are not practically feasible on classical computers.
Views: 15 wikipedia tts
Quantum computer | Wikipedia audio article
 
51:57
This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Quantum_computing 00:02:59 1 Basics 00:05:47 2 Principles of operation 00:15:25 3 Operation 00:18:09 4 Potential 00:18:18 4.1 Cryptography 00:20:44 4.2 Quantum search 00:23:05 4.3 Quantum simulation 00:23:39 4.4 Quantum annealing and adiabatic optimisation 00:24:15 4.5 Solving linear equations 00:24:39 4.6 Quantum supremacy 00:26:16 5 Obstacles 00:26:57 5.1 Quantum decoherence 00:29:56 6 Developments 00:30:05 6.1 Quantum computing models 00:31:14 6.2 Physical realizations 00:33:53 6.3 Timeline 00:48:27 7 Relation to computational complexity theory Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.9884976941951719 Voice name: en-AU-Wavenet-A "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= Quantum computing is computing using quantum-mechanical phenomena, such as superposition and entanglement. A quantum computer is a device that performs quantum computing. Such a computer is completely different from binary digital electronic computers based on transistors and capacitors. Whereas common digital computing requires that the data be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits or qubits, which can be in superpositions of states. A quantum Turing machine is a theoretical model of such a computer and is also known as the universal quantum computer. The field of quantum computing was initiated by the work of Paul Benioff and Yuri Manin in 1980, Richard Feynman in 1982, and David Deutsch in 1985.As of 2018, the development of actual quantum computers is still in its infancy, but experiments have been carried out in which quantum computational operations were executed on a very small number of quantum bits. Both practical and theoretical research continues, and many national governments and military agencies are funding quantum computing research in additional effort to develop quantum computers for civilian, business, trade, environmental and national security purposes, such as cryptanalysis. Noisy devices with a small number of qubits, also dubbed noisy intermediate-scale quantum (NISQ) devices by John Preskill, have been developed by a number of companies, including IBM, Intel, and Google. IBM has made 5-qubit and 16-qubit quantum computing devices available to the public for experiments via the cloud on the IBM Q Experience. D-Wave Systems has been developing their own version of a quantum computer that uses annealing.Large-scale quantum computers would theoretically be able to solve certain problems much more quickly than any classical computers that use even the best currently known algorithms, like integer factorization using Shor's algorithm (which is a quantum algorithm) and the simulation of quantum many-body systems. There exist quantum algorithms, such as Simon's algorithm, that run faster than any possible probabilistic classical algorithm. A classical computer could in principle (with exponential resources) simulate a quantum algorithm, as quantum computation does not violate the Church–Turing thesis. On the other hand, quantum computers may be able to efficiently solve problems which are not practically feasible on classical computers. A recent review by Mikhail Dyakonov in IEEE Spectrum argues that practical quantum computers are not likely to be implemented. He says: "There is a tremendous gap between the rudimentary but very hard experiments that have been carried out with a few qubits and the extremely developed quantum-computing theory, which relies on manipulating thousands to millions of qubits to calculate anything useful. That gap is not likely to be closed anytime soon."
Views: 11 wikipedia tts
Quantum computers | Wikipedia audio article
 
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This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Quantum_computing 00:03:23 1 Basics 00:06:36 2 Principles of operation 00:17:56 3 Operation 00:20:59 4 Potential 00:21:09 4.1 Cryptography 00:23:52 4.2 Quantum search 00:26:31 4.3 Quantum simulation 00:27:07 4.4 Quantum annealing and adiabatic optimisation 00:27:47 4.5 Solving linear equations 00:28:12 4.6 Quantum supremacy 00:30:00 5 Obstacles 00:30:47 5.1 Quantum decoherence 00:34:05 6 Developments 00:34:15 6.1 Quantum computing models 00:35:32 6.2 Physical realizations 00:38:37 6.3 Timeline 00:55:09 7 Relation to computational complexity theory Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.8283521720225513 Voice name: en-GB-Wavenet-B "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= Quantum computing is computing using quantum-mechanical phenomena, such as superposition and entanglement. A quantum computer is a device that performs quantum computing. Such a computer is completely different from binary digital electronic computers based on transistors and capacitors. Whereas common digital computing requires that the data be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits or qubits, which can be in superpositions of states. A quantum Turing machine is a theoretical model of such a computer and is also known as the universal quantum computer. The field of quantum computing was initiated by the work of Paul Benioff and Yuri Manin in 1980, Richard Feynman in 1982, and David Deutsch in 1985.As of 2018, the development of actual quantum computers is still in its infancy, but experiments have been carried out in which quantum computational operations were executed on a very small number of quantum bits. Both practical and theoretical research continues, and many national governments and military agencies are funding quantum computing research in additional effort to develop quantum computers for civilian, business, trade, environmental and national security purposes, such as cryptanalysis. Noisy devices with a small number of qubits, also dubbed noisy intermediate-scale quantum (NISQ) devices by John Preskill, have been developed by a number of companies, including IBM, Intel, and Google. IBM has made 5-qubit and 16-qubit quantum computing devices available to the public for experiments via the cloud on the IBM Q Experience. D-Wave Systems has been developing their own version of a quantum computer that uses annealing.Large-scale quantum computers would theoretically be able to solve certain problems much more quickly than any classical computers that use even the best currently known algorithms, like integer factorization using Shor's algorithm (which is a quantum algorithm) and the simulation of quantum many-body systems. There exist quantum algorithms, such as Simon's algorithm, that run faster than any possible probabilistic classical algorithm. A classical computer could in principle (with exponential resources) simulate a quantum algorithm, as quantum computation does not violate the Church–Turing thesis. On the other hand, quantum computers may be able to efficiently solve problems which are not practically feasible on classical computers. A recent review by Mikhail Dyakonov in IEEE Spectrum argues that practical quantum computers are not likely to be implemented. He says: "There is a tremendous gap between the rudimentary but very hard experiments that have been carried out with a few qubits and the extremely developed quantum-computing theory, which relies on manipulating thousands to millions of qubits to calculate anything useful. That gap is not likely to be closed anytime soon."
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Timeline of United States inventions (1946–91) | Wikipedia audio article
 
02:14:00
This is an audio version of the Wikipedia Article: Timeline of United States inventions (1946–91) Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. You can find other Wikipedia audio articles too at: https://www.youtube.com/channel/UCuKfABj2eGyjH3ntPxp4YeQ You can upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts "The only true wisdom is in knowing you know nothing." - Socrates SUMMARY ======= A timeline of United States inventions (1946–1991) encompasses the ingenuity and innovative advancements of the United States within a historical context, dating from the era of the Cold War, which have been achieved by inventors who are either native-born or naturalized citizens of the United States. Copyright protection secures a person's right to his or her first-to-invent claim of the original invention in question, highlighted in Article I, Section 8, Clause 8 of the United States Constitution which gives the following enumerated power to the United States Congress: In 1641, the first patent in North America was issued to Samuel Winslow by the General Court of Massachusetts for a new method of making salt. On April 10, 1790, President George Washington signed the Patent Act of 1790 (1 Stat. 109) into law which proclaimed that patents were to be authorized for "any useful art, manufacture, engine, machine, or device, or any improvement therein not before known or used." On July 31, 1790, Samuel Hopkins of Pittsford, Vermont became the first person in the United States to file and to be granted a patent for an improved method of "Making Pot and Pearl Ashes." The Patent Act of 1836 (Ch. 357, 5 Stat. 117) further clarified United States patent law to the extent of establishing a patent office where patent applications are filed, processed, and granted, contingent upon the language and scope of the claimant's invention, for a patent term of 14 years with an extension of up to an additional 7 years. However, the Uruguay Round Agreements Act of 1994 (URAA) changed the patent term in the United States to a total of 20 years, effective for patent applications filed on or after June 8, 1995, thus bringing United States patent law further into conformity with international patent law. The modern-day provisions of the law applied to inventions are laid out in Title 35 of the United States Code (Ch. 950, sec. 1, 66 Stat. 792). From 1836 to 2011, the United States Patent and Trademark Office (USPTO) has granted a total of 7,861,317 patents relating to several well-known inventions appearing throughout the timeline below. Some examples of patented inventions between the years 1946 and 1991 include William Shockley's transistor (1947), John Blankenbaker's personal computer (1971), Vinton Cerf's and Robert Kahn's Internet protocol/TCP (1973), and Martin Cooper's mobile phone (1973).
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Timeline of United States inventions (1946–1991) | Wikipedia audio article
 
02:41:20
This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Timeline_of_United_States_inventions_(1946%E2%80%931991) 00:03:20 1 Cold War (1946–1991) 00:03:33 1.1 Post-war and the late 1940s (1946–1949) 00:24:12 1.2 1950s 01:07:39 1.3 1960s 01:49:11 1.4 1970s 02:20:18 1.5 1980s and the early 1990s (1980–1991) 02:39:13 2 See also 02:39:22 3 Footnotes 02:39:31 4 Further reading 02:40:38 5 External links Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.7346002310281773 Voice name: en-AU-Wavenet-B "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= A timeline of United States inventions (1946–1991) encompasses the ingenuity and innovative advancements of the United States within a historical context, dating from the era of the Cold War, which have been achieved by inventors who are either native-born or naturalized citizens of the United States. Copyright protection secures a person's right to his or her first-to-invent claim of the original invention in question, highlighted in Article I, Section 8, Clause 8 of the United States Constitution which gives the following enumerated power to the United States Congress: In 1641, the first patent in North America was issued to Samuel Winslow by the General Court of Massachusetts for a new method of making salt. On April 10, 1790, President George Washington signed the Patent Act of 1790 (1 Stat. 109) into law which proclaimed that patents were to be authorized for "any useful art, manufacture, engine, machine, or device, or any improvement therein not before known or used." On July 31, 1790, Samuel Hopkins of Pittsford, Vermont became the first person in the United States to file and to be granted a patent for an improved method of "Making Pot and Pearl Ashes." The Patent Act of 1836 (Ch. 357, 5 Stat. 117) further clarified United States patent law to the extent of establishing a patent office where patent applications are filed, processed, and granted, contingent upon the language and scope of the claimant's invention, for a patent term of 14 years with an extension of up to an additional 7 years. However, the Uruguay Round Agreements Act of 1994 (URAA) changed the patent term in the United States to a total of 20 years, effective for patent applications filed on or after June 8, 1995, thus bringing United States patent law further into conformity with international patent law. The modern-day provisions of the law applied to inventions are laid out in Title 35 of the United States Code (Ch. 950, sec. 1, 66 Stat. 792). From 1836 to 2011, the United States Patent and Trademark Office (USPTO) has granted a total of 7,861,317 patents relating to several well-known inventions appearing throughout the timeline below. Some examples of patented inventions between the years 1946 and 1991 include William Shockley's transistor (1947), John Blankenbaker's personal computer (1971), Vinton Cerf's and Robert Kahn's Internet protocol/TCP (1973), and Martin Cooper's mobile phone (1973).
Views: 188 wikipedia tts
Brain-computer interface | Wikipedia audio article
 
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This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface 00:01:35 1 History 00:06:23 2 Versus neuroprosthetics 00:08:02 3 Animal BCI research 00:08:51 3.1 Early work 00:10:40 3.2 Prominent research successes 00:10:50 3.2.1 Kennedy and Yang Dan 00:12:07 3.2.2 Nicolelis 00:14:30 3.2.3 Donoghue, Schwartz and Andersen 00:15:57 3.2.4 Other research 00:19:49 3.2.5 The BCI Award 00:23:38 4 Human BCI research 00:23:49 4.1 Invasive BCIs 00:24:33 4.1.1 Vision 00:27:33 4.1.2 Movement 00:29:43 4.2 Partially invasive BCIs 00:33:04 4.3 Non-invasive BCIs 00:34:16 4.3.1 Non-EEG-based human–computer interface 00:34:27 4.3.1.1 Pupil-size oscillation 00:35:25 4.3.1.2 Functional near-infrared spectroscopy 00:35:54 4.3.2 Electroencephalography (EEG)-based brain-computer interfaces 00:36:07 4.3.2.1 Overview 00:40:19 4.3.3 Dry active electrode arrays 00:42:56 4.3.4 SSVEP mobile EEG BCIs 00:46:46 4.3.4.1 Limitations 00:48:34 4.3.5 Prosthesis and environment control 00:50:20 4.3.6 DIY and open source BCI 00:52:02 4.3.7 MEG and MRI 00:53:58 4.3.8 BCI control strategies in neurogaming 00:54:09 4.3.8.1 Motor imagery 00:55:27 4.3.8.2 Bio/neurofeedback for passive BCI designs 00:57:09 4.3.8.3 Visual evoked potential (VEP) 01:00:47 4.4 Synthetic telepathy/silent communication 01:04:10 5 Cell-culture BCIs 01:06:26 6 Ethical considerations 01:09:47 7 Low-cost BCI-based interfaces 01:13:00 8 Future directions 01:14:34 8.1 Disorders of consciousness (DOC) 01:19:06 8.2 Motor recovery 01:21:30 8.3 Functional brain mapping 01:23:16 8.4 Flexible devices 01:24:03 8.5 Neural dust Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.8310201752345111 Voice name: en-GB-Wavenet-A "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= A brain–computer interface (BCI), sometimes called a neural-control interface (NCI), mind-machine interface (MMI), direct neural interface (DNI), or brain–machine interface (BMI), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.Research on BCIs began in the 1970s at the University of California, Los Angeles (UCLA) under a grant from the National Science Foundation, followed by a contract from DARPA. The papers published after this research also mark the first appearance of the expression brain–computer interface in scientific literature. The field of BCI research and development has since focused primarily on neuroprosthetics applications that aim at restoring damaged hearing, sight and movement. Thanks to the remarkable cortical plasticity of the brain, signals from implanted prostheses can, after adaptation, be handled by the brain like natural sensor or effector channels. Following years of animal experimentation, the first neuroprosthetic devices implanted in humans appeared in the mid-1990s.
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