Chess is one of the world's most popular games. Its popularity and complexity make it an interesting research domain for artificial intelligence. The number of board positions we can get to from the initial board state is larger than the number of atoms in the universe! Chess playing machines have been the subject of human interest for hundreds of years, but only on the last few decades have they been able to compete with (and beat) the world champions. Chess programs now have their own tournaments.
On the other side was a new program called AlphaZero (the "zero" meaning no human knowledge in the loop), a chess engine in some ways very much weaker than Stockfish--powering through just 1/100th as many moves per second as its opponent. The AI engine won the match (winning 28 games and drawing the rest) with dazzling sacrifices, risky moves, and a beautiful style that was completely new to the world of computer chess. British chess grandmaster Matthew Sadler and mathematician and chessmaster Natasha Regan are still piecing together how AlphaZero's strategy works in their new book, Game Changer. We're breaking open two moves in just one of the games to show the aggressive style, what it does, and what humans can learn from our new chess champion. By move 42, AlphaZero has sacrificed even more pawns, and is marching another poor, disposable sucker toward oblivion.
I have come to the personal conclusion that while all artists are not chess players, all chess players are artists. Originally called Chaturanga, the game was set on an 8x8 Ashtāpada board and shared two key fundamental features that still distinguish the game today. Different pieces subject to different rules of movement and the presence of a single king piece whose fate determines the outcome. But it was not until the 15th century, with the introduction of the queen piece and the popularization of various other rules, that we saw the game develop into the form we know today. The emergence of international chess competition in the late 19th century meant that the game took on a new geopolitical importance.
The term Artificial Intelligence was coined 70 years ago as the stuff of fantasy fiction and about 50 years post that nothing much moved. Then, in 1997 like a bolt from the blue, IBM's Deep Blue defeated world chess champion Garry Kasparov 4-2 in a six game series. Since then, machines have beaten humans at far more complex games – Go, Poker, Dota 2. Computing power grew over a trillion times in the last 50 years. Can you name any industry/trend that has evolved by this order of magnitude? The computer that helped navigate Apollo 11's moon landing had the power of two Nintendo consoles. You have a lot more power in your smartphone today.
If you're planning on teaching a computer to play chess, it is often helpful to start off with the building block of the AI, also known as chess board representation. This is a program which is able to keep track of the state of the game as well as to provide the basis for further position evaluation. There are a number of different programming languages, libraries and software applications which are thought to be good for building computer chess programs. Python is usually the most loved language among data scientists, but I decided to write my own chess board representation with PHP from scratch since I spotted an opportunity to do something new in the PHP community. It'd be nice if a chess library like python-chess could be available in PHP too, I thought.
Since IBM's Deep Blue defeated World Chess Champion Garry Kasparov in their 1997 match, chess engines have only increased dramatically in strength and understanding. Today, the best chess engines are an almost incomprehensible 1,000 Elo points stronger than Deep Blue was at that time. A quick Google search for terms such as "Magnus Carlsen versus Stockfish" turns up numerous threads asking if humans can compete against today's top chess engines. The broad consensus seems to be that the very best humans might secure a few draws with the white pieces, but in general, they would lose the vast majority of games and would have no hope of winning any games. I see no reason to disagree with this consensus. Despite the clear superiority of engines, there ARE positions which chess engines don't (and possibly can't) understand that are quite comprehensible for human players.
In this article, we will discuss what I believe is one of the most significant issues facing the future of project management. Let me start by asking 3 questions. If you're a project manager and don't know the answers to those three questions, I suggest you read further because your career might depend on knowing them. So why is the 5th of December 2017 a significant date for those of us who take even a cursory interest in the development of AI and machine learning or what we call ML? The 5th of December 2017 was a pretty special day; on that day, one computer beat another computer at the Top Chess Engine Championship.
"Just to rub it in, a version of AlphaGO, called AlphaZero recently learned to trounce AlphaGo at Go, and also to trounce Stockfish (the world's best chess program, far better than any human) and Elmo (the world's best shongi program, also better than any human). AlphaZero did all this in one day." I was reading "Human Compatible" this week and the above anecdote got me thinking. A computer crushing Chess and Go Grandmasters is impressive and feels ominous, but what does it mean for our everyday jobs? Every year computer chips get smaller and faster (Moore's Law) and experts predict Machine Learning, AI and automation will eviscerate our jobs.
Dating back to the Industrial Revolution, people have speculated that machines would render human ... [ ] work obsolete. Unlike in earlier eras, artificial intelligence will prove this prophecy true. "When looms weave by themselves, man's slavery will end." Stanford is hosting an event next month named "Intelligence Augmentation: AI Empowering People to Solve Global Challenges." This title is telling and typical.
Chess has captured the imagination of humans for centuries due to its strategic beauty--an objective, board-based testament to the power of mortal intuition. Twenty-five years ago Wednesday, though, human superiority on a chessboard was seriously threatened for the first time. At a nondescript convention center in Philadelphia, a meticulously constructed supercomputer called Deep Blue faced off against Garry Kasparov for the first in a series of six games. Kasparov was world chess champion at the time and widely considered to be one of the greatest players in the history of chess. He did not expect to lose.
We mere mortals haven't truly been competitive against artificial intelligence in chess in a long time. It's been 15 years since a human has conquered a computer in a chess tournament. However, a team of researchers have developed an AI chess engine that doesn't set out to crush us puny humans -- it tries to play like us. The Maia engine doesn't necessarily play the best available move. Instead, it tries to replicate what a human would do.