Goto

Collaborating Authors

Results


An imprisoned bishop Highly Evolved Leela vs Mighty Stockfish TCEC Season 17 Rd 34

#artificialintelligence

FIDE CM Kingscrusher goes over a game featuring An imprisoned bishop Highly Evolved Leela vs Mighty Stockfish TCEC Season 17 Rd 34 Play turn style chess at http://bit.ly/chessworld FIDE CM Kingscrusher goes over amazing games of Chess every day, with a focus recently on chess champions such as Magnus Carlsen or even games of Neural Networks which are opening up new concepts for how chess could be played more effectively. The Game qualities that kingscrusher looks for are generally amazing games with some awesome or astonishing features to them. Many brilliant games are being played every year in Chess and this channel helps to find and explain them in a clear way. There are classic games, crushing and dynamic games. There are exceptionally elegant games.


Why The Retirement Of Lee Se-Dol, Former 'Go' Champion, Is A Sign Of Things To Come

#artificialintelligence

South Korean professional Go player Lee Se-Dol after the match against Google's artificial ... [ ] intelligence program, AlphaGo on March 10, 2016 in Seoul, South Korea. In May 1997, IBM's Deep Blue supercomputer defeated the reigning world chess champion, Garry Kasparov, in an official match under tournament conditions. Fast forward to 2011, IBM extended development in machine learning, natural language processing, and information retrieval to build Watson, a system capable of defeating two highly decorated Jeopardy champions: Brad Rutter and Ken Jennings. The progress of gaming innovation in the field of artificial intelligence was swift, but it wasn't until the introduction of Google DeepMind's AlphaGo in 2016 that things started to change dramatically. The AlphaGo supercomputer tackled the notion that Go, an ancient Chinese board game invented thousands of years ago, was unsolvable due to a near limitless combination of moves that a player can execute.


Leela Chess outrageous Thorn Pawn Strategy KomodoMCTS vs Leela TCEC Season 16

#artificialintelligence

FIDE CM Kingscrusher goes over Leela Chess outrageous Thorn Pawn Strategy KomodoMCTS vs Leela TCEC Season 16 Play turn style chess at http://bit.ly/chessworld FIDE CM Kingscrusher goes over amazing games of Chess every day, with a focus recently on chess champions such as Magnus Carlsen or even games of Neural Networks which are opening up new concepts for how chess could be played more effectively. The Game qualities that kingscrusher looks for are generally amazing games with some awesome or astonishing features to them. Many brilliant games are being played every year in Chess and this channel helps to find and explain them in a clear way. There are classic games, crushing and dynamic games. There are exceptionally elegant games.


The Democratisation of Technology

#artificialintelligence

In 1997 the IBM computer Deep Blue beat Gary Kasparov, the reigning world chess champion. Nineteen years later Google's AlphaGo beat Go master Lee Se-dol. Both are landmark moments for computing and artificial intelligence. Both were the product of some of the world's smartest people writing cutting edge software. In parallel, AI has become a game-changer in business, for example transforming the way we interact with technology and information through Alexa and Siri.


Leela reacts beautifully to the Budapest Gambit vs Stockfish emphasising squishing strategy

#artificialintelligence

FIDE CM Kingscrusher goes over amazing games of Chess every day, with a focus recently on games of Neural Networks which are opening up new concepts for how chess could be played more effectively. It is developed by Belgian programmer Gian-Carlo Pascutto,[1][2][3] the author of chess engine Sjeng and Go engine Leela.[4][5] Unlike the original Leela, which has a lot of human knowledge and heuristics programmed into it, Leela Zero only knows the basic rules and nothing more.[7] Leela Zero is trained by a distributed effort, which is coordinated at the Leela Zero website. Members of the community provide computing resources by running the client, which generates self-play games and submits them to the server.


ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero

arXiv.org Machine Learning

The AlphaGo, AlphaGo Zero, and AlphaZero series of algorithms are a remarkable demonstration of deep reinforcement learning's capabilities, achieving superhuman performance in the complex game of Go with progressively increasing autonomy. However, many obstacles remain in the understanding of and usability of these promising approaches by the research community. Toward elucidating unresolved mysteries and facilitating future research, we propose ELF OpenGo, an open-source reimplementation of the AlphaZero algorithm. ELF OpenGo is the first open-source Go AI to convincingly demonstrate superhuman performance with a perfect (20:0) record against global top professionals. We apply ELF OpenGo to conduct extensive ablation studies, and to identify and analyze numerous interesting phenomena in both the model training and in the gameplay inference procedures. Our code, models, selfplay datasets, and auxiliary data are publicly available.


Google's New AI Is a Master of Games, but How Does It Compare to the Human Mind?

#artificialintelligence

For humans, chess may take a lifetime to master. But Google DeepMind's new artificial intelligence program, AlphaZero, can teach itself to conquer the board in a matter of hours. Building on its past success with the AlphaGo suite--a series of computer programs designed to play the Chinese board game Go--Google boasts that its new AlphaZero achieves a level of "superhuman performance" at not just one board game, but three: Go, chess, and shogi (essentially, Japanese chess). The team of computer scientists and engineers, led by Google's David Silver, reported its findings recently in the journal Science. "Before this, with machine learning, you could get a machine to do exactly what you want--but only that thing," says Ayanna Howard, an expert in interactive computing and artificial intelligence at the Georgia Institute of Technology who did not participate in the research.


AI takes on video games in quest for common sense

Science

Next week, scientists working on artificial intelligence (AI) and games will be watching the latest human-machine matchup. But instead of a single pensive player squaring off against a computer, a team of five top video game players will be furiously casting magic spells and lobbing (virtual) fireballs at a team of five AIs called OpenAI Five. They'll be playing the real-time strategy game Dota 2 at The International in Vancouver, Canada, an annual e-sports tournament that draws professional gamers who compete for millions of dollars. In 1997, IBM's Deep Blue AI bested chess champion Garry Kasparov. In 2016, DeepMind's AlphaGo AI beat Lee Sedol, a world master, at the traditional Chinese board game Go.


AlphaGo, Google's Artificial Intelligence – OpenDeepTech

#artificialintelligence

AlphaGo, Google's AI becomes the best Go player in the world by winning three games against world number one, Ke jie. AlphaGo once battled other champions like Fan Hui and Lee Sedol, which allowed him to improve, in addition to millions of games played against himself. Twenty years ago, Deep Blue, IBM's supercomputer, defeated world champion Garry Kasparov with his algorithms and great computing power, sweeping all the gameplay on many shots. But faced with the game of Go, which has an immense number of possible combinations, the computing power is not enough, it is necessary to improve the algorithms. Two methods are used in AlphaGo: the Monte Carlo method and Deep Learning.


Garry Kasparov Talks Artificial Intelligence, Deep Blue, And AlphaGo Zero

#artificialintelligence

Despite losing at chess to the IBM Deep Blue computer more than 20 years ago, Garry Kasparov is a big believer in artificial intelligence. The former world chess champion is now an author and speaker who is trying to counter some of the more alarmist beliefs over the rise of AI technologies, typically exemplified in Hollywood movies in which robots rise against their human creators. Speaking at the Train AI conference on Thursday in San Francisco, Kasparov explained how humanity has long considered people's performance in playing a game of chess as a metric of intelligence. "People looked at it as an opportunity to go deep in the human mind," he said of chess. That's why when Kasparov lost to Deep Blue in 1997 in a rematch from a prior match he won in 1996 -- which, he likes to note, "nobody remembers" -- people considered it a "watershed moment" for computer science.