AlphaGo

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AlphaGo - The Movie | Full award-winning documentary

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13.03.2020

With more board configurations than there are atoms in the universe, the ancient Chinese game of Go has long been considered a grand challenge for artificial intelligence. On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history. Directed by Greg Kohs and with an original score by Academy Award nominee Hauschka, AlphaGo had its premiere at the Tribeca Film Festival. It has since gone on to win countless awards and near universal praise for a story that chronicles a journey from the halls of Oxford, through the backstreets of Bordeaux, past the coding terminals of DeepMind in London, and ultimately, to the seven-day tournament in Seoul. As the drama unfolds, more questions emerge: What can artificial intelligence reveal about a 3000-year-old game? What can it teach us about humanity? Best documentary winner: Denver International Film Festival (2017), Warsaw International Film Festival (2017), and Traverse City Film Festival (2017). Official selection at Tribeca Film Festival (2017), BFI London Film Festival (2017), and Critics' Choice Documentary Awards (2017). Find out more: 🤍 "I want my style of Go to be something different, something new, my own thing, something that no one has thought of before." Lee Sedol, Go Champion (18 World Titles). "We think of DeepMind as kind of an Apollo program effort for AI. Our mission is to fundamentally understand intelligence and recreate it artificially." Demis Hassabis, Co-Founder & CEO, DeepMind. "The Game of Go is the holy grail of artificial intelligence. Everything we've ever tried in AI, it just falls over when you try the game of Go." Dave Silver, Lead Researcher for AlphaGo.

AlphaGo Official Trailer

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🤍 Watch on Google Play Movies → 🤍 AlphaGo chronicles a journey from the halls of Cambridge, through the backstreets of Bordeaux, past the coding terminals of DeepMind, to Seoul, where a legendary Go master faces an unproven AI challenger. As the drama unfolds, questions emerge: What can artificial intelligence reveal about a 3000-year-old game? What will it teach us about humanity?

AlphaGo & Deep Learning - Computerphile

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18.03.2016

AlphaGo beat the Go World Champion 4-1. Why do the creators not know how? Brais Martinez is a Research Fellow & Deep Learning expert at the University of Nottingham. 🤍 🤍 This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: 🤍 Computerphile is a sister project to Brady Haran's Numberphile. More at 🤍

Lee Sedol vs AlphaGo Move 37 reactions and analysis

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05.01.2018

Lee Sedol vs AlphaGo Move 37 reactions and analysis . Reactions from Lee Sedol, reactions from AlphaGo team, reactions from commentators, analysis on move 37 . Google DeepMind Challenge. With more board configurations than there are atoms in the universe, the ancient Chinese game of 'Go' has long been considered a grand challenge for artificial intelligence. On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The Google DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history. Directed by Greg Kohs with an original score by Academy Award nominee, Hauschka, AlphaGo chronicles a journey from the halls of Cambridge, through the backstreets of Bordeaux, past the coding terminals of DeepMind in London, and, ultimately, to the seven-day tournament in Seoul. As the drama unfolds, more questions emerge: What can artificial intelligence reveal about a 3000-year-old game? What can it teach us about humanity? —AlphaGo Credit: AlphaGo Movie 🤍

New DeepMind AI Beats AlphaGo 100-0 | Two Minute Papers #201

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The AlphaGo Zero paper "Mastering the Game of Go without Human Knowledge" is available here: 🤍 🤍 Our Patreon page with the details: 🤍 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Andrew Melnychuk, Brian Gilman, Christoph Jadanowski, Dave Rushton-Smith, Dennis Abts, Eric Haddad, Esa Turkulainen, Evan Breznyik, Kaben Gabriel Nanlohy, Malek Cellier, Michael Albrecht, Michael Jensen, Michael Orenstein, Steef, Steve Messina, Sunil Kim, Torsten Reil. 🤍 Two Minute Papers Merch: US: 🤍 EU/Worldwide: 🤍 Photo credits: Watson - AP Photo/Jeopardy Productions, Inc. Fan Hui match photo - Google DeepMind - 🤍 Go board image credits (all CC BY 2.0): Renato Ganoza - 🤍 Jaro Larnos (changes were applied, mostly recoloring) - 🤍 Luis de Bethencourt - 🤍 Go ratings: 🤍 Music: Antarctica by Audionautix is licensed under a Creative Commons Attribution license (🤍 Artist: 🤍 Thumbnail background image credit: 🤍 Splash screen/thumbnail design: Felícia Fehér - 🤍 Károly Zsolnai-Fehér's links: Facebook: 🤍 Twitter: 🤍 Web: 🤍

Why did Lee Sedol, one of the world’s best ‘Go’ players, retire from the game?

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16.01.2020

One of the greatest ‘Go’ players of all time just retired from the game, saying that artificial intelligence programmes can play at a level humans aren’t able to. His decision has reignited discussions about AI and how we define human achievement. #AI #Go #LeeSedol #SouthKorea Beyond The Game 👉 🤍 Panama Papers 👉 🤍 Subscribe: 🤍

Google's AI AlphaGo Is Beating Humanity At Its Own Games (HBO)

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10.09.2017

Go is an ancient, aristocratic Chinese board game that’s reputed to have as many possible moves as there are atoms in the universe. And Google recently trained an artificial intelligence computer to play against one of the best human players in the world. The computer won. At Google’s Future of Go Summit, 19-year-old Chinese Go prodigy Ke Jie was defeated by the AI AlphaGo in a three-match series. AI evangelists are happy with the win, but AI doomsayers are worried it’s coming for our jobs next. And China is just mad that an American company beat the world at a Chinese game. VICE News reports on what the competition really means for AI development. Subscribe to VICE News here: 🤍 Check out VICE News for more: 🤍 Follow VICE News here: Facebook: 🤍 Twitter: 🤍 Tumblr: 🤍 Instagram: 🤍 More videos from the VICE network: 🤍

David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning | Lex Fridman Podcast #86

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David Silver leads the reinforcement learning research group at DeepMind and was lead researcher on AlphaGo, AlphaZero and co-lead on AlphaStar, and MuZero and lot of important work in reinforcement learning. Support this podcast by signing up with these sponsors: - MasterClass: 🤍 - Cash App - use code "LexPodcast" and download: - Cash App (App Store): 🤍 - Cash App (Google Play): 🤍 EPISODE LINKS: Reinforcement learning (book): 🤍 PODCAST INFO: Podcast website: 🤍 Apple Podcasts: 🤍 Spotify: 🤍 RSS: 🤍 Full episodes playlist: 🤍 Clips playlist: 🤍 OUTLINE: 0:00 - Introduction 4:09 - First program 11:11 - AlphaGo 21:42 - Rule of the game of Go 25:37 - Reinforcement learning: personal journey 30:15 - What is reinforcement learning? 43:51 - AlphaGo (continued) 53:40 - Supervised learning and self play in AlphaGo 1:06:12 - Lee Sedol retirement from Go play 1:08:57 - Garry Kasparov 1:14:10 - Alpha Zero and self play 1:31:29 - Creativity in AlphaZero 1:35:21 - AlphaZero applications 1:37:59 - Reward functions 1:40:51 - Meaning of life CONNECT: - Subscribe to this YouTube channel - Twitter: 🤍 - LinkedIn: 🤍 - Facebook: 🤍 - Instagram: 🤍 - Medium: 🤍 - Support on Patreon: 🤍

Lee Sedol Hand of God Move 78 Reaction and Analysis

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05.01.2018

The hand of God move from Lee Sedol in match 4 against AlphaGo. This move 78 changed the dynamics of the match and Lee Sedol wins against AlphaGo. With more board configurations than there are atoms in the universe, the ancient Chinese game of 'Go' has long been considered a grand challenge for artificial intelligence. On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The Google DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history. Directed by Greg Kohs with an original score by Academy Award nominee, Hauschka, AlphaGo chronicles a journey from the halls of Cambridge, through the backstreets of Bordeaux, past the coding terminals of DeepMind in London, and, ultimately, to the seven-day tournament in Seoul. As the drama unfolds, more questions emerge: What can artificial intelligence reveal about a 3000-year-old game? What can it teach us about humanity? —AlphaGo Credit: AlphaGo Movie 🤍

AlphaGo Zero: Starting from scratch

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18.10.2017

DeepMind's Professor David Silver describes AlphaGo Zero, the latest evolution of AlphaGo, the first computer program to defeat a world champion at the ancient Chinese game of Go. Zero is even more powerful and is arguably the strongest Go player in history. Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play. In doing so, it quickly surpassed human level of play and defeated the previously published champion-defeating version of AlphaGo by 100 games to 0. Find out more here: 🤍

L'imposture AlphaGo: débunkage ScienceEtonnante, Scilabus ... intelligence artificielle IA

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11.03.2020

#AlphaGo #IA #IntelligenceArtificielle Débunkage et arguments scientifiques contre l'idée qu'AlphaGo serait une intelligence artificielle. Je vais vous expliquer pourquoi AlphaGo n'est pas une IA. Je vais prendre 2 arguments qui me sautent le plus aux yeux en tant que spécialiste. Mais il en existe d'autres. [1] Jeu de go et intelligence artificielle — À chaud ! #2 🤍 [2] AlphaGo et l'intelligence artificielle | Actu 1 🤍 [3] Lee Sedol vs AlphaGo Move 37 reactions and analysis 🤍 [4] Ce robot peut-il se faire du mal ? 🤍 50s à 2m30s: Ce qui me gêne particulièrement, c'est que l'apprentissage machine est présenté de la manière suivant: 1-Apprentissage sur un jeu de données Manquent: 2-la création aléatoire de 3-dizaines voires centaines de milliers de parcours 4-répartis en 3 jeux de données: Train 1, Train 2 et Test. 5-l'explication que le jeu de données d'apprentissage est partagé en 2 (pour la sélection et l'optimisation des paramètres d'apprentissage de tout classifieur). 6-que Train 1, Train 2 et Test ne doivent idéalement contenir aucun exemple identique. 7-la difficulté du calcul des performances: courbe ROC, subjectivité du seuil pour le calcul de la sensibilité, du rappel. L'impossibilité de pondérer les performances par classe en fonction des désiquilibre du nombre d'exemples d'apprentissage pour chaque classe. Et surtout, comment faire la "moyenne" (et quelle moyenne? artithmétique, pondérée, harmonique ...) de N rappels, sensibilités et Fscores? [5] Olivier Dufour, Benoît Gineste, Yves Bas, Matthieu Le Corre, Thierry Artières, First automatic passive acoustic tool for monitoring two species of procellarides (Pterodroma baraui and Puffinus bailloni) on Reunion Island, Indian Ocean, Ecological Informatics, Volume 35, 2016, Pages 55-60, ISSN 1574-9541, Keywords: Seabirds; Automatic detector; Acoustic monitoring; Procellarides; Autonomous recording unit; Barau's petrel 🤍 👨‍💻 Comment devenir chercheur en Intelligence Artificielle: 5 conseils 🤍 Pour vous former à l'intelligence artificielle et à l'apprentissage machine: Playlist de tous les épisodes de la chaîne dans l'ordre chronologique (écoutez-en 1 par jour par exemple!): 🤍 Références personnelles et mon profil: Références de mon sujet de thèse: 🤍 Un peu de biblio perso: 🤍 🤍 🤍 🤍 🤍 Les articles que j'ai reviewé pour la revue scientifique à comité de lecture "Ecological informatics": 🤍 🤍 🤍 🤍 F A C E B O O K 🤍 T W I T T E R 🤍 Je suis le Docteur Olivier Dufour. (Montpellier) Crédits photos miniature: 🤍 http://159.203.44.189/wp-content/uploads/2013/07/photoMoi.png 🤍 🤍

AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained

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07.03.2021

❤️ Become The AI Epiphany Patreon ❤️ ► 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ In this video, I cover the seminal AlphaGo paper - the first system to beat a professional Go player in the game of Go. A task previously considered beyond the reach of current AI systems and at least 10 years off into the future, but neural networks proved them wrong! You'll learn about: ✔️All of the nitty-gritty details around AlphaGo ✔️How MTCS and other subcomponents work ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ✅ AlphaGo movie: 🤍 ✅ Karpathy on AlphaGo: 🤍 ✅ Silver on UCB algo: 🤍 ✅ MTCS explained: 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ⌚️ Timetable: 00:00 Intro 00:37 Context behind the game of Go 04:10 High-level overview of components - SL policies 07:25 RL policy network 09:30 The value network 11:15 Going deeper 16:30 Details around value network 19:05 Understanding the search (MTCS) 27:10 Evaluation of AlphaGo 33:30 Older techniques 34:40 Even more detailed explanation of APV-MTCS 37:40 Virtual loss 41:00 Engineering 45:30 Neural networks and symmetries ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💰 BECOME A PATREON OF THE AI EPIPHANY ❤️ If these videos, GitHub projects, and blogs help you, consider helping me out by supporting me on Patreon! The AI Epiphany ► 🤍 One-time donation: 🤍 Much love! ❤️ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition". ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 👋 CONNECT WITH ME ON SOCIAL LinkedIn ► 🤍 Twitter ► 🤍 Instagram ► 🤍 Facebook ► 🤍 👨‍👩‍👧‍👦 JOIN OUR DISCORD COMMUNITY: Discord ► 🤍 📢 SUBSCRIBE TO MY MONTHLY AI NEWSLETTER: Substack ► 🤍 💻 FOLLOW ME ON GITHUB FOR COOL PROJECTS: GitHub ► 🤍 📚 FOLLOW ME ON MEDIUM: Medium ► 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #alphago #deepmind #reinforcementlearning

Lee Sedol beats AlphaGo!

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On Google DeepMind Challenge Match 4, Lee Sedol (9-dan pro, the top Go player of the past decade) defeated DeepMind's program AlphaGo. The match took place in Seoul on 13 March 2016. Match commentary by Michael Redmond (9-dan pro) and Chris Garlock. Lee Sedol vs AlphaGo, Match 4 Credit: Google DeepMind

Lee Sedol VS AlphaGo - The Divine Move

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03.08.2020

In 2016, Lee Sedol faced off against Google's AlphaGo for one final clash between man and machine. Though Lee Sedol lost the match 4-1, the one win he received was full of such insight and beauty, that many have called the turning point of the game Lee's Divine Move. In this video, I endeavored to bring the game to life - one last time in honor of one of the greatest Go players of our time! Support my work on Patreon! 🤍 Watch me play LIVE on Twitch here! 🤍 Follow me on Twitch 🤍in_sente Thanks to Annie, a good friend who helped give me the Influencie software which made this board visualization possible! Download the program here! 🤍 Thanks to Jota-R for the royalty free music! 🤍

Google's Deep Mind Explained! - Self Learning A.I.

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02.05.2016

Subscribe here: 🤍 Become a Patreon!: 🤍 Visual animal AI: 🤍 Hi, welcome to ColdFusion (formally known as ColdfusTion). Experience the cutting edge of the world around us in a fun relaxed atmosphere. Sources: Why AlphaGo is NOT an "Expert System": 🤍 “Inside DeepMind” Nature video: 🤍 “AlphaGo and the future of Artificial Intelligence” BBC Newsnight: 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍forbes.com/sites/privacynotice/2014/02/03/inside-googles-mysterious-ethics-board/#5dc388ee4674 🤍 🤍 🤍 🤍 //Soundtrack// Disclosure - You & Me (Ft. Eliza Doolittle) (Bicep Remix) Stumbleine - Glacier Sundra - Drifting in the Sea of Dreams (Chapter 2) Dakent - Noon (Mindthings Rework) Hnrk - fjarlæg Dr Meaker - Don't Think It's Love (Real Connoisseur Remix) Sweetheart of Kairi - Last Summer Song (ft. CoMa) Hiatus - Nimbus KOAN Sound & Asa - This Time Around (feat. Koo) Burn Water - Hide » Google + | 🤍 » Facebook | 🤍 » My music | t.guarva.com.au/BurnWater 🤍 or » 🤍 » 🤍 » Collection of music used in videos: 🤍 Producer: Dagogo Altraide Editing website: 🤍cfnstudios.com Coldfusion Android Launcher: 🤍 » Twitter | 🤍ColdFusion_TV

The Future of Go Summit, Match One: Ke Jie & AlphaGo

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23.05.2017

Watch AlphaGo and the world's number one Go player, Ke Jie, explore the mysteries of the game together in the first of three classic 1:1 matches. This is the livestream for match one to be played on Tuesday 23 May 10:30 CST (local), 03:30 BST

AlphaGo and the future of Artificial Intelligence - BBC Newsnight

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09.03.2016

Remember the excitement in 1997 when Deep Blue, the IBM computer, defeated chess grandmaster Gary Kasparov? That moment was considered a great leap forward for artificial intelligence. Now software designed to beat the best players in the world at “Go” is about to take thinking machines to a whole new level. Here’s why. Featuring former government tech adviser Rohan Silva. Newsnight is the BBC's flagship news and current affairs TV programme - with analysis, debate, exclusives, and robust interviews. Subscribe to our YouTube channel for highlights and bonus videos 🤍 Follow us on Twitter 🤍BBCNewsnight for the latest updates on #newsnight Add us on Snapchat - our username is 'BBCNewsnight' And follow on Facebook for our best material, an early heads up on what's coming up, and to join in our debates 🤍

AlphaGo vs. AlphaGo with Michael Redmond 9p: Game 53

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13.05.2022

Originally aired on February 6, 2022 Produced by Eva-Dee Beech, Chris Garlock and Stephen Hu Thumbnail image of Rock 'em Sock 'em Robots by Lorie Shaull - Own work, CC BY-SA 4.0, 🤍

阿尔法狗用什么算法击败李世石?《阿尔法围棋》 | 看电影了没

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31.01.2018

好的电影 改变你的认知 欢迎大家回到【看电影了没】我是K猫。 我今天要跟大家讲人机大战《阿尔法围棋》 这是关于阿尔法狗背后不为人知的故事。 片名: 阿尔法围棋 AlphaGo (2017) 喜欢我们的频道内容,请记得点赞分享+订阅! ►🤍 下载K星球知道更多好看的电影►🤍 可以搜寻bilibili网站►🤍 #看电影了没 #講說者 #阿尔法围棋 #AlphaGo #解说 #讲评

2022 AlphaGo S6 V1 AIR Dual Fold Off-Road Camper Trailer Walkthrough Video

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Take a tour of our newly launched AlphaGo S6 V1 AIR - a full off-road capable dual fold trailer that inflates into a villa on wheels at the push of a button! Overview No more poles. The world’s most spacious camper with serious off-road capabilities that self-inflates in under 3 minutes. Highlights Sleeps 6 Full Off-Road Capable Low Towing Profile Wrap Around Lounge Suite with Day Bed Premium Slide Out Kitchen External Shower Features Memory Foam Double Size Bed x 2 Wrap Around Lounge Suite (Converts to Double Bed) Dining Table Led Lighting 12v / 220v Inlets 🤍alphago.co.za External Premium Slide Out Kitchen + Hot & Cold Tap 4 Burner Stove Up to 75L Fridge Space External Shower Led Lighting 12v / 220v Inlets Multiple Storage Areas Built in Roof Cargo Cage Tent Ripstop 330g Poly Cotton Premium Self-Inflating Tent with Dacron Support Beams Individual Beams Shut Off Valves Tropical Roof Ground Skirting Front Awning* Plumbing 90L Water Tank 6L Geyser Hot Water System Portable Toilet* Electrical Full 12v + 220v Power System Battery Charging System 100ah Deep Cycle battery 2000w Inverter* *Sold Separately

Match 1 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo

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09.03.2016

Watch DeepMind's program AlphaGo take on the legendary Lee Sedol (9-dan pro), the top Go player of the past decade, in a $1M 5-game challenge match in Seoul. This is the livestream for Match 1 to be played on: 9th March 13:00 KST (local), 04:00 GMT; note for US viewers this is the day before on: 8th March 20:00 PT, 23:00 ET. In October 2015, AlphaGo became the first computer program ever to beat a professional Go player by winning 5-0 against the reigning 3-times European Champion Fan Hui (2-dan pro). That work was featured in a front cover article in the science journal Nature in January 2016. Match commentary by Michael Redmond (9-dan pro) and Chris Garlock.

李世石 神之一手 擊敗 AlphaGo 第四局78手

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18.04.2016

古力驚嘆, 佐為附身了!

AlphaGo

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07.01.2020

This video explains the details behind AlphaGo! AlphaGo uses policy and value networks to reduce the search space in MCTS! Thanks for watching! Please Subscribe! Paper Link: 🤍

AlphaGo - How AI mastered the hardest boardgame in history

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13.11.2017

In this episode I dive into the technical details of the AlphaGo Zero paper by Google DeepMind. This AI system uses Reinforcement Learning to beat the world's Go champion using only self-play, a remarkable display of clever engineering on the path to stronger AI systems. DeepMind Blogpost: 🤍 AlphaGo Zero paper: 🤍 If you want to support this channel, here is my patreon link: 🤍 - You are amazing!! ;) If you have questions you would like to discuss with me personally, you can book a 1-on-1 video call through Pensight: 🤍

Un AlphaGo invencible

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18.10.2017

AlphaGo Zero es la nueva versión de la inteligencia artificial que aprende sola a partir de las reglas básicas del juego del go hasta convertirse en un jugador invencible.

The Future of Go Summit: AlphaGo & Ke Jie match 1 moves analysis

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24.05.2017

Catch up on most exciting moves from the first AlphaGo & Ke Jie match at The Future of Go Summit. With commentary from DeepMind research scientist, Thore Graepel, and 9-dan professional, Michael Redmond.

TRİBE GİREN YAPAY ZEKA AlphaGo: 37. Hamle 78. Hamleye Karşı

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19.08.2018

Yapay zeka AlphaGo'nun, 18 kez dünya şampiyonu olmuş 9 dan sahibi Lee Sedol ile karşılaşmasının ve 5 serilik turnuvanın ikisinde tarihe nasıl tanıklık ettiğimizin hikayesi bu videoda. Go: Antik Çin’de 2.500 yıldan fazla tarihi ile dünyaca ünlü bir strateji oyunu. Amaç rakipten daha fazla alan sağlayarak onu alt etmek. Bu öyle bir oyun ki; board üzerindeki hamle olasılığı evrendeki atomların toplamından daha fazla. Bu oyunu son yıllarda bu kadar popüler yapan şey ise bir makine. AlphaGo'nun sıradışı hikayesini anlatmaya çalıştım. Abone Ol: 🤍 Blog: 🤍 Twitter: 🤍 Instagram: 🤍 Disclaimer for Fair Use: Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.

nachgehakt: Wie Googles KI AlphaGo auf Profi-Niveau Go spielt

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12.03.2016

🤍 – Bisher taten sich Computer schwer, auf Profi-Niveau Go zu spielen. Warum das so war und worin der Durchbruch besteht, weshalb AlphaGo durchaus Chancen gegen einen der weltstärksten Go-Spieler haben könnte, erklärt Harald Bögeholz. Mehr zu AlphaGo und KI im Artikel in c't 6/16: 🤍

AlphaGo Zero: Discovering new knowledge

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18.10.2017

DeepMind's Professor David Silver describes AlphaGo Zero, the latest evolution of AlphaGo, the first computer program to defeat a world champion at the ancient Chinese game of Go. Zero is even more powerful and is arguably the strongest Go player in history. Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play. In doing so, it quickly surpassed human level of play and defeated the previously published champion-defeating version of AlphaGo by 100 games to 0. If similar techniques can be applied to other structured problems, such as protein folding, reducing energy consumption or searching for revolutionary new materials, the resulting breakthroughs have the potential to positively impact society. Find out more here: 🤍

The Future of Go Summit, Match Three: Ke Jie & AlphaGo

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27.05.2017

Watch AlphaGo and the world's number one Go player, Ke Jie, explore the mysteries of the game together in the third of three classic 1:1 matches. This is the livestream for match three to be played on Saturday 27 May 10:30 CST (local), 03:30 BST.

Exploring the mysteries of Go with AlphaGo and China's top players

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10.04.2017

DeepMind is excited to share the news that AlphaGo, China’s top Go players, and leading A.I. experts from Google and China will come together in Wuzhen, in May 2017 for the “Future of Go Summit".

Artefarita Inteligenteco, de la komenco ĝis AlphaGo

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00:08:06
22.03.2019

Nuntempe Artefarita Inteligenteco (AI) kutimas en niaj ĉiutagaj vivoj sed sia komenco ne estas nova. La vojo ekde la una revo pri maŝinoj kiuj povos pensi ĝis AlphaGo estis longe kaj en tiu ĉi video ni rakontos la unuan parton de tiu historio. Ekspektu kiel maŝinoj lernis venki nin! - Verkinto: Frank van Hertrooij Produktinto: Carlos Pesquera Alonso Prezentinto: Adam Brooking Muntinto: Carlos Pesquera Alonso Sonplibonigo: Carlos Pesquera Alonso - Legu la originalan artikolojn je 🤍 - Aŭdiovidaĵaj fontoj: 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 Niaj videoj ankaŭ estas aŭdeblaj per podkasto: 🤍 Ankaŭ estas samnoma scienca blogo de nia teamano Frank: 🤍

AlphaGo Official Trailer

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00:01:31
26.10.2017

🤍

AlphaGo是什麼?人工智慧真的戰勝人腦了嗎!?|科學大爆炸EP.59

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00:04:35
19.05.2016

#科學大爆炸 3月 AlphaGo V.S. 李世乭的世紀圍棋大賽,人工智慧以4:1下贏了天才棋士李世乭,開啟了人工智慧的新里程碑。 究竟AlphaGo厲害在哪裡?第四場為什麼AlphaGo會輸呢?人工智慧比人腦厲害在哪裡?我們真的就從此贏不了電腦了嗎?一起來聽聽台灣紅面棋王周俊勳,和又懂人工智慧又下棋的于天立老師怎麼說! 延伸必讀: AlphaGo 爆冷從李世乭手中拿下首勝。台灣棋王怎麼看?電腦為何辦得到? 🤍 AlphaGo成為「棋靈王」是有多厲害?人工智慧未來又要怎麼走? 🤍 AlphaGo既不是起點也不會是終點,從頭述說人工智慧走過的這70年 🤍 人工智慧贏了圍棋,然後呢 🤍 ________________ 周俊勳 棋士: 臺灣棋院九段、中國圍棋協會三段、職業圍棋棋士,是臺灣1979年成立職業圍棋制度以來第一位職業九段棋手。因右臉有大片紅色胎記,號紅面棋王。 他是世界圍棋棋壇上唯一擁有三個職業圍棋組織(中國圍棋會,中國圍棋協會(中國棋院),臺灣棋院)棋籍的棋手。 🤍 于天立 副教授: 任教於台大電機系,研究領域為基因遺傳演算法、 演化計算、機器學習、人工智慧。 俞俐均 棋士: 職業一段,為目前台灣職業圍棋最年輕的女棋士。 🤍

Ke Jie and DeepMind's Go Ambassador Fan Hui review the 1st AlphaGo vs Ke Jie game

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01:15:26
15.09.2017

Watch world champion Go player Ke Jie and DeepMind's Go Ambassador Fan Hui review the three AlphaGo vs Ke Jie games played in the Future of Go summit in Wuzhen in May 2017. Their review is aided by real-time analysis from the same version of AlphaGo that played in Wuzhen (1 of 3).

Google DeepMind: Ground-breaking AlphaGo masters the game of Go

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00:02:48
27.01.2016

In a paper published in Nature on 28th January 2016, we describe a new approach to computer Go. This is the first time ever that a computer program “AlphaGo” has defeated a human professional player. The game of Go is widely viewed as an unsolved “grand challenge” for artificial intelligence. Games are a great testing ground for inventing smarter, more flexible algorithms that have the ability to tackle problems in ways similar to humans. The first classic game mastered by a computer was noughts and crosses (also known as tic-tac-toe) in 1952. But until now, one game has thwarted A.I. researchers: the ancient game of Go. Despite decades of work, the strongest computer Go programs only played at the level of human amateurs. AlphaGo has won over 99% of games against the strongest other computer Go programs. It also defeated the human European champion by 5-0 in tournament games, a feat previously believed to be at least a decade away. In March 2016, AlphaGo will face its ultimate challenge: a 5-game challenge match in Seoul against the legendary Lee Sedol—the top Go player in the world over the past decade This video tells the story so far... With Demis Hassabis, Google DeepMind Deep Blue photo credit courtesy of International Business Machines Corporation, © International Business Machines Corporation.

รีวิวสารคดีนักเล่นโกะปัญญาประดิษฐ์ Alpha Go | MONDAY Talk EP5

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06.06.2022

รีวิวสารคดีเรื่อง Alpha Go ซึ่งเป็น AI ที่สร้างขึ้นมาเพื่อต่อกรกับนักเล่นโกะระดับโลกทั้งหลาย ไม่ว่าจะเป็น Fan Hui หรือ Lee Sedol และทำให้เห็นว่าเทคโนโลยี AI นั้นก้าวไหนไปถึงไหนแล้ว ขอบคุณภาพและคลิปจาก DeepMind คลิกลิงค์ 🤍 #ยอดบารมี #TheMONDAY #AlphaGo #Documentary #Netflix #FanHui #LeeSedol #DeepMind #AI #Go #ArtificialIntelligence #MovieReview #MondayTalk

The Future of Go Summit, Match Two: Ke Jie & AlphaGo

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05:27:45
25.05.2017

Watch AlphaGo and the world's number one Go player, Ke Jie, explore the mysteries of the game together in the second of three classic 1:1 matches. This is the livestream for match two to be played on Thursday 25 May 10:30 CST (local), 03:30 BST

DeepMind AlphaGo Zero Explained

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00:12:07
14.08.2018

DeepMind's AlphaGo Zero algorithm beat the best Go player in the world by training entirely by self-play. It played against itself repeatedly, getting better over time with no human gameplay input. AlphaGo Zero was a remarkable moment in AI history, a moment that will always be remembered. Move 37 in particular is worthy of many philosophical debates. You'll see what I mean and get a technical overview of its neural components (code + animations) in this video. Enjoy! Code for this video: 🤍 Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: 🤍 instagram: 🤍 Facebook: 🤍 There are 2 errors in this video: 1. At the top of the residual network, it says value layer twice. One should say 'policy' layer. 2 The residual network is 40 layers, i say 20. This video is apart of my Machine Learning Journey course: 🤍 More Learning Resources: 🤍 🤍 🤍 🤍 🤍 🤍 Join us in the Wizards Slack channel: 🤍 Sign up for the next course at The School of AI: 🤍 And please support me on Patreon: 🤍 #AlphaGoZero #Deepmind #SirajRaval Signup for my newsletter for exciting updates in the field of AI: 🤍 Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

How Google Deepmind AlphaGo works

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00:01:31
07.01.2018

How Google Deepmind AlphaGo works. Extract from Movie Alphago. Thore Graepel is research scientist at Deepmind explains the AplhaGo logic. Three main components - Policy network, Value Network and tree search. Credit: AlphaGo movie

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