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ariel79 commited on Jul 30, 2024

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-Topic: Artificial Intelligence (AI)
 Description: AI allows computers to think and act like humans, finding patterns in data to make decisions.
-Topic: Machine Learning (ML)
-Description: ML is a subset of AI, where a program trains on previous data to make predictions and exhibit "human" behavior.
-Topic: Model
-Description: A model is a function that maps from an input to a prediction, and finds patterns based on this input data.
-Topic: Castling
-Description: Castling is a move that involves the king moving two squares towards a rook on the player's first rank, then the rook moving to the square over which the king crossed.
-Topic: Check
-Description: A check is a situation where a king is under threat of being captured on the next move.
-Topic: Checkmate
-Description: A game of chess is won by checkmating your opponent's king, which means the king is in a position to be captured and cannot escape.
-Topic: Stalemate
-Description: A stalemate occurs when the player whose turn it is to move has no legal move and their king is not in check. It results in a draw.
-Topic: En Passant
-Description: En passant is a special pawn capture that can occur if a pawn moves two squares forward from its starting position and lands beside an opponent's pawn.
-Topic: Chess Clock
-Description: A chess clock is used to track the total time each player takes for their moves. If a player's time runs out, they lose the game.
-Topic: Fork
-Description: A fork is a tactic where a single piece attacks two or more of the opponent's pieces at the same time.
-Topic: Bishop Movement
-Description: A bishop moves diagonally any number of squares, but cannot jump over other pieces.
-Topic: Pin
-Description: A pin occurs when a piece cannot move without exposing a more valuable piece, like the king or queen, to attack.
-Topic: Discovered Check
-Description: A discovered check happens when a piece moves, revealing an attack on the opponent's king by another piece.
-Topic: Rook Movement
-Description: A rook moves any number of squares along a row or column.
-Topic: Gambit
-Description: A gambit is a chess opening in which a player sacrifices material, usually a pawn, with the hope of achieving a subsequent advantageous position.
-Topic: Fifty-Move Rule
-Description: The fifty-move rule allows a player to claim a draw if no pawn has been moved and no capture has been made in the last fifty moves by each player.
-Topic: Difference Between Check and Checkmate
-Description: Check is when the king is in danger but can still escape, whereas checkmate is when the king is in danger and cannot escape.
-Topic: Queen Movement
-Description: The queen can move any number of squares along a row, column, or diagonal.
-Topic: Perpetual Check
-Description: Perpetual check is a situation in which one player can check the opponent's king continuously, resulting in a draw if it occurs three times.
-Topic: Phases of a Chess Game
-Description: The three phases of a chess game are the opening, the middlegame, and the endgame.
-Topic: Chess
-Description: A selection of white and black chess pieces on a checkered surface. Chess is a board game for two players. It is sometimes called international chess or Western chess to distinguish it from related games such as xiangqi (Chinese chess) and shogi (Japanese chess). Chess is an abstract strategy game that involves no hidden information and no elements of chance. It is played on a chessboard with 64 squares arranged in an 8×8 grid. The players, referred to as "White" and "Black", each control sixteen pieces: one king, one queen, two rooks, two bishops, two knights, and eight pawns. White moves first, followed by Black. The game is won by checkmating the opponent's king, i.e. threatening it with inescapable capture. There are several ways a game can end in a draw.
-Topic: Setup
-Description: The game is played on a square board of eight rows (called ranks) and eight columns (called files). By convention, the 64 squares alternate in color and are referred to as light and dark squares; common colors for chessboards are white and brown, or white and green. The pieces are set out as shown in the diagram and photo. Thus, on White's first rank, from left to right, the pieces are placed as follows: rook, knight, bishop, queen, king, bishop, knight, rook. Eight pawns are placed on the second rank. Black's position mirrors White's, with an equivalent piece on the same file. The board is placed with a light square at the right-hand corner nearest to each player. The correct position of the light square may be remembered by the phrase "light on right", while the correct positions of the king and queen may be remembered by the phrase "queen on her own color" (i.e. the white queen begins on a light square, and the black queen on a dark square). In competitive games, the piece colors are allocated to players by the organizers; in informal games, the colors are usually decided randomly, for example by a coin toss, or by one player concealing a white pawn in one hand and a black pawn in the other, and having the opponent choose.
-Topic: Objective
-Description: The object of the game is to checkmate the opponent; this occurs when the opponent's king is in check, and there is no legal way to get it out of check. It is never legal for a player to make a move that puts or leaves the player's own king in check. In casual games, it is common to announce "check" when putting the opponent's king in check, but this is not required by the rules of chess and is usually not done in tournaments.
-Topic: Promotion
-Description: When a pawn advances to its eighth rank, as part of the move, it is promoted and must be exchanged for the player's choice of queen, rook, bishop, or knight of the same color. Usually, the pawn is chosen to be promoted to a queen, but in some cases, another piece is chosen; this is called underpromotion. In the animated diagram, the pawn on c7 can be advanced to the eighth rank and be promoted. There is no restriction on the piece promoted to, so it is possible to have more pieces of the same type than at the start of the game (e.g., two or more queens). If the required piece is not available (e.g. a second queen) an inverted rook is sometimes used as a substitute, but this is not recognized in FIDE-sanctioned games.
-Topic: Checkmate
-Description: Checkmate: The opposing king is in check and the opponent has no legal move.
-Topic: Resignation
-Description: Resignation: A player may resign, conceding the game to the opponent. If, however, the opponent has no way of checkmating the resigned player, this is a draw under FIDE Laws. Most tournament players consider it good etiquette to resign in a hopeless position.
-Topic: Forfeit
-Description: Forfeit: A player who cheats, violates the rules, or violates the rules of conduct specified for the particular tournament can be forfeited. Occasionally, both players are forfeited.
-Topic: Draw
-Description: Stalemate: If the player to move has no legal move, but is not in check, the position is a stalemate, and the game is drawn.
-Topic: Dead position
-Description: Dead position: If neither player is able to checkmate the other by any legal sequence of moves, the game is drawn. For example, if only the kings are on the board, all other pieces having been captured, checkmate is impossible, and the game is drawn by this rule. On the other hand, if both players still have a knight, there is a highly unlikely yet theoretical possibility of checkmate, so this rule does not apply. The dead position rule supersedes the previous rule which referred to "insufficient material", extending it to include other positions where checkmate is impossible, such as blocked pawn endings where the pawns cannot be attacked.
-Topic: Draw by agreement
-Description: Draw by agreement: In tournament chess, draws are most commonly reached by mutual agreement between the players. The correct procedure is to verbally offer the draw, make a move, then start the opponent's clock. Traditionally, players have been allowed to agree to a draw at any point in the game, occasionally even without playing a move. More recently efforts have been made to discourage short draws, for example by forbidding draw offers before move thirty.
-Topic: Middlegame
-Description: The middlegame is the part of the game that starts after the opening. There is no clear line between the opening and the middlegame, but typically the middlegame will start when most pieces have been developed. (Similarly, there is no clear transition from the middlegame to the endgame; see start of the endgame.) Because the opening theory has ended, players have to form plans based on the features of the position, and at the same time take into account the tactical possibilities of the position. The middlegame is the phase in which most combinations occur. Combinations are a series of tactical moves executed to achieve some gain. Middlegame combinations are often connected with an attack against the opponent's king. Some typical patterns have their own names; for example, the Boden's Mate or the Lasker–Bauer combination. Specific plans or strategic themes will often arise from particular groups of openings that result in a specific type of pawn structure. An example is the minority attack, which is the attack of queenside pawns against an opponent who has more pawns on the queenside. The study of openings is therefore connected to the preparation of plans that are typical of the resulting middlegames. Another important strategic question in the middlegame is whether and how to reduce material and transition into an endgame (i.e. simplify). Minor material advantages can generally be transformed into victory only in an endgame, and therefore the stronger side must choose an appropriate way to achieve an ending. Not every reduction of material is good for this purpose; for example, if one side keeps a light-squared bishop and the opponent has a dark-squared one, the transformation into a bishops and pawns ending is usually advantageous for the weaker side only, because an endgame with bishops on opposite colors is likely to be a draw, even with an advantage of a pawn, or sometimes even with a two-pawn advantage.
-Topic: Chess tactics
-Description: In chess, tactics in general concentrate on short-term actions – so short-term that they can be calculated in advance by a human player or a computer. The possible depth of calculation depends on the player's ability. In quiet positions with many possibilities on both sides, a deep calculation is more difficult and may not be practical, while in positions with a limited number of forced variations, strong players can calculate long sequences of moves.
-Topic: Chess strategy
-Description: Chess strategy is concerned with the evaluation of chess positions and with setting up goals and long-term plans for future play. During the evaluation, players must take into account numerous factors such as the value of the pieces on the board, control of the center and centralization, the pawn structure, king safety, and the control of key squares or groups of squares (for example, diagonals, open files, and dark or light squares). The most basic step in evaluating a position is to count the total value of pieces of both sides. The point values used for this purpose are based on experience; usually, pawns are considered worth one point, knights and bishops about three points each, rooks about five points (the value difference between a rook and a bishop or knight being known as the exchange), and queens about nine points. The king is more valuable than all of the other pieces combined, since its checkmate loses the game. But in practical terms, in the endgame, the king as a fighting piece is generally more powerful than a bishop or knight but less powerful than a rook. These basic values are then modified by other factors like position of the piece (e.g. advanced pawns are usually more valuable than those on their initial squares), coordination between pieces (e.g. a pair of bishops usually coordinate better than a bishop and a knight), or the type of position (e.g. knights are generally better in closed positions with many pawns while bishops are more powerful in open positions). Another important factor in the evaluation of chess positions is pawn structure (sometimes known as the pawn skeleton): the configuration of pawns on the chessboard. Since pawns are the least mobile of the pieces, pawn structure is relatively static and largely determines the strategic nature of the position. Weaknesses in pawn structure include isolated, doubled, or backward pawns and holes; once created, they are often permanent. Care must therefore be taken to avoid these weaknesses unless they are compensated by another valuable asset (for example, by the possibility of developing an attack).
-Topic: Endgame
-Decsription: The endgame (also end game or ending) is the stage of the game when there are few pieces left on the board. There are three main strategic differences between earlier stages of the game and the endgame: Pawns become more important. Endgames often revolve around endeavors to promote a pawn by advancing it to the furthest rank. The king, which requires safeguarding from attack during the middlegame, emerges as a strong piece in the endgame. It is often brought to the center where it can protect its own pawns, attack enemy pawns, and hinder moves of the opponent's king. Endgames can be classified according to the type of pieces remaining on the board. Basic checkmates are positions in which one side has only a king and the other side has one or two pieces and can checkmate the opposing king, with the pieces working together with their king. For example, king and pawn endgames involve only kings and pawns on one or both sides, and the task of the stronger side is to promote one of the pawns. Other more complicated endings are classified according to pieces on the board other than kings, such as "rook and pawn versus rook" endgames.
-Topic: History of chess
-Description: Texts referring to the origins of chess date from the beginning of the seventh century. Three are written in Pahlavi (Middle Persian) and one, the Harshacharita, is in Sanskrit. One of these texts, the Chatrang-namak, represents one of the earliest written accounts of chess. The narrator Bozorgmehr explains that Chatrang, "Chess" in Pahlavi, was introduced to Persia by 'Dewasarm, a great ruler of India' during the reign of Khosrow I. The oldest known chess manual was in Arabic and dates to about 840, written by al-Adli ar-Rumi (800–870), a renowned Arab chess player, titled Kitab ash-shatranj (The Book of Chess). This is a lost manuscript, but is referenced in later works. Here also, al-Adli attributes the origins of Persian chess to India, along with the eighth-century collection of fables Kalīla wa-Dimna. By the 20th century, a substantial consensus developed regarding chess's origins in northwest India in the early seventh century. More recently, this consensus has been the subject of further scrutiny.
-Topic: History of chess
-Description: The early forms of chess in India were known as chaturaṅga (Sanskrit: चतुरङ्ग), literally "four divisions" [of the military] – infantry, cavalry, elephants, and chariotry – represented by pieces that would later evolve into the modern pawn, knight, bishop, and rook, respectively. Chaturanga was played on an 8×8 uncheckered board, called ashtāpada. Thence it spread eastward and westward along the Silk Road. The earliest evidence of chess is found in nearby Sasanian Persia around 600 A.D., where the game came to be known by the name chatrang (Persian: چترنگ). Chatrang was taken up by the Muslim world after the Islamic conquest of Persia (633–51), where it was then named shatranj (Arabic: شطرنج; Persian: شترنج), with the pieces largely retaining their Persian names. In Spanish, "shatranj" was rendered as ajedrez ("al-shatranj"), in Portuguese as xadrez, and in Greek as ζατρίκιον (zatrikion, which comes directly from the Persian chatrang), but in the rest of Europe it was replaced by versions of the Persian shāh ("king"), from which the English words "check" and "chess" descend. The word "checkmate" is derived from the Persian shāh māt ("the king is dead").
-Topic: History of chess
-Description: Xiangqi is the form of chess best known in China. The eastern migration of chess, into China and Southeast Asia, has even less documentation than its migration west, making it largely conjectured. The word xiàngqí (象棋) was used in China to refer to a game from 569 A.D. at the latest, but it has not been proven if this game was or was not directly related to chess. The first reference to Chinese chess appears in a book entitled Xuánguaì Lù (玄怪錄; "Record of the Mysterious and Strange"), dating to about 800. A minority view holds that Western chess arose from xiàngqí or one of its predecessors. Chess historians Jean-Louis Cazaux and Rick Knowlton contend that xiangqi's intrinsic characteristics make it easier to construct an evolutionary path from China to India/Persia than the opposite direction.
-Topic: 1200–1700: Origins of the modern game
-Description: The game of chess was then played and known in all European countries. A famous 13th-century Spanish manuscript covering chess, backgammon, and dice is known as the Libro de los juegos, which is the earliest European treatise on chess as well as being the oldest document on European tables games. The rules were fundamentally similar to those of the Arabic shatranj. The differences were mostly in the use of a checkered board instead of a plain monochrome board used by Arabs and the habit of allowing some or all pawns to make an initial double step. In some regions, the queen, which had replaced the wazir, or the king could also make an initial two-square leap under some conditions.
-Topic: 1200–1700: Origins of the modern game
-Description: Around 1200, the rules of shatranj started to be modified in Europe, culminating, several major changes later, in the emergence of modern chess practically as it is known today. A major change was the modern piece movement rules, which began to appear in intellectual circles in Valencia, Spain, around 1475, which established the foundations and brought it very close to current chess. These new rules then were quickly adopted in Italy and Southern France before diffusing into the rest of Europe. Pawns gained the ability to advance two squares on their first move, while bishops and queens acquired their modern movement powers. The queen replaced the earlier vizier chess piece toward the end of the 10th century and by the 15th century had become the most powerful piece; in light of that, modern chess was often referred to at the time as "Queen's Chess" or "Mad Queen Chess". Castling, derived from the "king's leap", usually in combination with a pawn or rook move to bring the king to safety, was introduced. These new rules quickly spread throughout Western Europe.
-Topic: 1200–1700: Origins of the modern game
-Description: Writings about chess theory began to appear in the late 15th century. An anonymous treatise on chess of 1490 with the first part containing some openings and the second 30 endgames is deposited in the library of the University of Göttingen. The book El Libro dels jochs partitis dels schachs en nombre de 100 was written by Francesc Vicent in Segorbe in 1495, but no copy of this work has survived. The Repetición de Amores y Arte de Ajedrez (Repetition of Love and the Art of Playing Chess) by Spanish churchman Luis Ramírez de Lucena was published in Salamanca in 1497. Lucena and later masters like Portuguese Pedro Damiano, Italians Giovanni Leonardo Di Bona, Giulio Cesare Polerio and Gioachino Greco, and Spanish bishop Ruy López de Segura developed elements of opening theory and started to analyze simple endgames.
-Topic: 1700–1873: Romantic era
-Description: In the 18th century, the center of European chess life moved from Southern Europe to mainland France. The two most important French masters were François-André Danican Philidor, a musician by profession, who discovered the importance of pawns for chess strategy, and later Louis-Charles Mahé de La Bourdonnais, who won a famous series of matches against Irish master Alexander McDonnell in 1834. Centers of chess activity in this period were coffee houses in major European cities like Café de la Régence in Paris and Simpson's Divan in London.
-Topic: 1700–1873: Romantic era
-Description: At the same time, the intellectual movement of romanticism had had a far-reaching impact on chess, with aesthetics and tactical beauty being held in higher regard than objective soundness and strategic planning. As a result, virtually all games began with the Open Game, and it was considered unsportsmanlike to decline gambits that invited tactical play such as the King's Gambit and the Evans Gambit. This chess philosophy is known as Romantic chess, and a sharp, tactical style consistent with the principles of chess romanticism was predominant until the late 19th century.
-Topic: 1700–1873: Romantic era
-Description: The rules concerning stalemate were finalized in the early 19th century. Also in the 19th century, the convention that White moves first was established (formerly either White or Black could move first). Finally, the rules around castling and en passant captures were standardized – variations in these rules persisted in Italy until the late 19th century. The resulting standard game is sometimes referred to as Western chess or international chess, particularly in Asia where other games of the chess family such as xiangqi are prevalent. Since the 19th century, the only rule changes, such as the establishment of the correct procedure for claiming a draw by repetition, have been technical in nature.
-Topic: 1700–1873: Romantic era
-Description: As the 19th century progressed, chess organization developed quickly. Many chess clubs, chess books, and chess journals appeared. There were correspondence matches between cities; for example, the London Chess Club played against the Edinburgh Chess Club in 1824. Chess problems became a regular part of 19th-century newspapers; Bernhard Horwitz, Josef Kling, and Samuel Loyd composed some of the most influential problems. In 1843, von der Lasa published his and Bilguer's Handbuch des Schachspiels (Handbook of Chess), the first comprehensive manual of chess theory.
-Topic: 1700–1873: Romantic era
-Description: The first modern chess tournament was organized by Howard Staunton, a leading English chess player, and was held in London in 1851. It was won by the German Adolf Anderssen, who was hailed as the leading chess master. His brilliant, energetic attacking style was typical for the time. Sparkling games like Anderssen's Immortal Game and Evergreen Game or Morphy's "Opera Game" were regarded as the highest possible summit of the art of chess.
-Topic: 1700–1873: Romantic era
-Description: Deeper insight into the nature of chess came with the American Paul Morphy, an extraordinary chess prodigy. Morphy won against all important competitors (except Staunton, who refused to play), including Anderssen, during his short chess career between 1857 and 1863. Morphy's success stemmed from a combination of brilliant attacks and sound strategy; he intuitively knew how to prepare attacks.
-Topic: 1873–1945: Birth of a sport
-Description: Prague-born Wilhelm Steinitz laid the foundations for a scientific approach to the game, the art of breaking a position down into components and preparing correct plans. In addition to his theoretical achievements, Steinitz founded an important tradition: his triumph over the leading German master Johannes Zukertort in 1886 is regarded as the first official World Chess Championship. This win marked a stylistic transition at the highest levels of chess from an attacking, tactical style predominant in the Romantic era to a more positional, strategic style introduced to the chess world by Steinitz. Steinitz lost his crown in 1894 to a much younger player, the German mathematician Emanuel Lasker, who maintained this title for 27 years, the longest tenure of any world champion.
-Topic: 1873–1945: Birth of a sport
-Description: After the end of the 19th century, the number of master tournaments and matches held annually quickly grew. The first Olympiad was held in Paris in 1924, and FIDE was founded initially for the purpose of organizing that event. In 1927, the Women's World Chess Championship was established; the first to hold the title was Czech-English master Vera Menchik.
-Topic: 1873–1945: Birth of a sport
-Description: A prodigy from Cuba, José Raúl Capablanca, known for his skill in endgames, won the World Championship from Lasker in 1921. Capablanca was undefeated in tournament play for eight years, from 1916 to 1924. His successor (1927) was the Russian-French Alexander Alekhine, a strong attacking player who died as the world champion in 1946. Alekhine briefly lost the title to Dutch player Max Euwe in 1935 and regained it two years later.
-Topic: 1873–1945: Birth of a sport
-Description: In the interwar period, chess was revolutionized by the new theoretical school of so-called hypermodernists like Aron Nimzowitsch and Richard Réti. They advocated controlling the center of the board with distant pieces rather than with pawns, thus inviting opponents to occupy the center with pawns, which become objects of attack.
-Topic: 1945–1990: Post-World War II era
-Description: After the death of Alekhine, a new World Champion was sought. FIDE, which has controlled the title since then, ran a tournament of elite players. The winner of the 1948 tournament was Russian Mikhail Botvinnik. In 1950, FIDE established a system of titles, conferring the title of Grandmaster on 27 players. (Some sources state that, in 1914, the title of chess Grandmaster was first formally conferred by Tsar Nicholas II of Russia to Lasker, Capablanca, Alekhine, Tarrasch, and Marshall, but this is a disputed claim.)
-Topic: 1945–1990: Post-World War II era
-Description: Botvinnik started an era of Soviet dominance in the chess world, which mainly through the Soviet government's politically inspired efforts to demonstrate intellectual superiority over the West stood almost uninterrupted for more than a half-century. Until the dissolution of the Soviet Union, there was only one non-Soviet champion, American Bobby Fischer (champion 1972–1975). Botvinnik also revolutionized opening theory. Previously, Black strove for equality, attempting to neutralize White's first-move advantage. As Black, Botvinnik strove for the initiative from the beginning. In the previous informal system of World Championships, the current champion decided which challenger he would play for the title and the challenger was forced to seek sponsors for the match. FIDE set up a new system of qualifying tournaments and matches. The world's strongest players were seeded into Interzonal tournaments, where they were joined by players who had qualified from Zonal tournaments. The leading finishers in these Interzonals would go through the "Candidates" stage, which was initially a tournament, and later a series of knockout matches. The winner of the Candidates would then play the reigning champion for the title. A champion defeated in a match had a right to play a rematch a year later. This system operated on a three-year cycle. Botvinnik participated in championship matches over a period of fifteen years. He won the world championship tournament in 1948 and retained the title in tied matches in 1951 and 1954. In 1957, he lost to Vasily Smyslov, but regained the title in a rematch in 1958. In 1960, he lost the title to the 23-year-old Latvian prodigy Mikhail Tal, an accomplished tactician and attacking player who is widely regarded as one of the most creative players ever, hence his nickname "the magician from Riga". Botvinnik again regained the title in a rematch in 1961.
-Topic: 1945–1990: Post-World War II era
-Description: Following the 1961 event, FIDE abolished the automatic right of a deposed champion to a rematch, and the next champion, Armenian Tigran Petrosian, a player renowned for his defensive and positional skills, held the title for two cycles, 1963–1969. His successor, Boris Spassky from Russia (champion 1969–1972), won games in both positional and sharp tactical style. The next championship, the so-called Match of the Century, saw the first non-Soviet challenger since World War II, American Bobby Fischer. Fischer defeated his opponents in the Candidates matches by unheard-of margins, and convincingly defeated Spassky for the world championship. The match was followed closely by news media of the day, leading to a surge in popularity for chess; it also held significant political importance at the height of the Cold War, with the match being seen by both sides as a microcosm of the conflict between East and West. In 1975, however, Fischer refused to defend his title against Soviet Anatoly Karpov when he was unable to reach agreement on conditions with FIDE, and Karpov obtained the title by default. Fischer modernized many aspects of chess, especially by extensively preparing openings.
-Topic: 1945–1990: Post-World War II era
-Description: Karpov defended his title twice against Viktor Korchnoi and dominated the 1970s and early 1980s with a string of tournament successes. In the 1984 World Chess Championship, Karpov faced his toughest challenge to date, the young Garry Kasparov from Baku, Soviet Azerbaijan. The match was aborted in controversial circumstances after 5 months and 48 games with Karpov leading by 5 wins to 3, but evidently exhausted; many commentators believed Kasparov, who had won the last two games, would have won the match had it continued. Kasparov won the 1985 rematch. Kasparov and Karpov contested three further closely fought matches in 1986, 1987 and 1990, Kasparov winning them all. Kasparov became the dominant figure of world chess from the mid-1980s until his retirement from competition in 2005.
-Topic: Beginnings of chess technology
-Description: Chess-playing computer programs (later known as chess engines) began to appear in the 1960s. In 1970, the first major computer chess tournament, the North American Computer Chess Championship, was held, followed in 1974 by the first World Computer Chess Championship. In the late 1970s, dedicated home chess computers such as Fidelity Electronics' Chess Challenger became commercially available, as well as software to run on home computers. The overall standard of computer chess was low, however, until the 1990s.
-Topic: Beginnings of chess technology
-Description: The first endgame tablebases, which provided perfect play for relatively simple endgames such as king and rook versus king and bishop, appeared in the late 1970s. This set a precedent to the complete six- and seven-piece tablebases that became available in the 2000s and 2010s respectively.
-Topic: Beginnings of chess technology
-Description: The first commercial chess database, a collection of chess games searchable by move and position, was introduced by the German company ChessBase in 1987. Databases containing millions of chess games have since had a profound effect on opening theory and other areas of chess research.
-Topic: Beginnings of chess technology
-Description: Digital chess clocks were invented in 1973, though they did not become commonplace until the 1990s. Digital clocks allow for time controls involving increments and delays.
-Topic: Technology
-Description: The Internet enabled online chess as a new medium of playing, with chess servers allowing users to play other people from different parts of the world in real time. The first such server, known as Internet Chess Server or ICS, was developed at the University of Utah in 1992. ICS formed the basis for the first commercial chess server, the Internet Chess Club, which was launched in 1995, and for other early chess servers such as FICS (Free Internet Chess Server). Since then, many other platforms have appeared, and online chess began to rival over-the-board chess in popularity. During the 2020 COVID-19 pandemic, the isolation ensuing from quarantines imposed in many places around the world, combined with the success of the popular Netflix show The Queen's Gambit and other factors such as the popularity of online tournaments (notably PogChamps) and chess Twitch streamers, resulted in a surge of popularity not only for online chess, but for the game of chess in general; this phenomenon has been referred to in the media as the 2020 online chess boom.
-Topic: Technology
-Description: Computer chess has also seen major advances. By the 1990s, chess engines could consistently defeat most amateurs, and in 1997 Deep Blue defeated World Champion Garry Kasparov in a six-game match, starting an era of computer dominance at the highest level of chess. In the 2010s, engines significantly stronger than even the best human players became accessible for free on a number of PC and mobile platforms, and free engine analysis became a commonplace feature on internet chess servers. An adverse effect of the easy availability of engine analysis on hand-held devices and personal computers has been the rise of computer cheating, which has grown to be a major concern in both over-the-board and online chess. In 2017, AlphaZero – a neural network also capable of playing shogi and Go – was introduced. Since then, many chess engines based on neural network evaluation have been written, the best of which have surpassed the traditional "brute-force" engines. AlphaZero also introduced many novel ideas and ways of playing the game, which affected the style of play at the top level.
-Topic: Technology
-Description: Since the late 1990s, it has been possible to follow major international chess events online, the players' moves being relayed in real time. Sensory boards have been developed to enable automatic transmission of moves. Chess players will frequently run engines while watching these games, allowing them to quickly identify mistakes by the players and spot tactical opportunities. While in the past the moves have been relayed live, today chess organizers will often impose a half-hour delay as an anti-cheating measure. In the mid-to-late 2010s – and especially following the 2020 online boom – it became commonplace for supergrandmasters, such as Hikaru Nakamura and Magnus Carlsen, to livestream chess content on platforms such as Twitch. Also following the boom, online chess started being viewed as an esport, with esport teams signing chess players for the first time in 2020.
-Topic: Online chess
-Description: Online chess is chess that is played over the internet, allowing players to play against each other in real time. This is done through the use of Internet chess servers, which pair up individual players based on their rating using an Elo or similar rating system. Online chess saw a spike in growth during the quarantines of the COVID-19 pandemic. This can be attributed to both isolation and the popularity of Netflix miniseries The Queen's Gambit, which was released in October 2020. Chess app downloads on the App Store and Google Play Store rose by 63% after the show debuted. Chess.com saw more than twice as many account registrations in November as it had in previous months, and the number of games played monthly on Lichess doubled as well. There was also a demographic shift in players, with female registration on Chess.com shifting from 22% to 27% of new players. GM Maurice Ashley said "A boom is taking place in chess like we have never seen maybe since the Bobby Fischer days", attributing the growth to an increased desire to do something constructive during the pandemic. USCF Women's Program Director Jennifer Shahade stated that chess works well on the internet, since pieces do not need to be reset and matchmaking is virtually instant.
-Topic: Computer chess
-Description: The idea of creating a chess-playing machine dates to the 18th century; around 1769, the chess-playing automaton called The Turk became famous before being exposed as a hoax. Serious trials based on automata, such as El Ajedrecista, were too complex and limited to be useful. Since the advent of the digital computer in the 1950s, chess enthusiasts, computer engineers, and computer scientists have built, with increasing degrees of seriousness and success, chess-playing machines and computer programs. The groundbreaking paper on computer chess, "Programming a Computer for Playing Chess", was published in 1950 by Claude Shannon.
-Topic: Computer chess
-Description: With huge databases of past games and high analytical ability, computers can help players to learn chess and prepare for matches. Internet Chess Servers allow people to find and play opponents worldwide. The presence of computers and modern communication tools have raised concerns regarding cheating during games.

+Topic: Artificial Intelligence
 Description: AI allows computers to think and act like humans, finding patterns in data to make decisions.
+Topic: AI
+Description: AI allows computers to think and act like humans, finding patterns in data to make decisions.
+Topic: Machine Learning
+Description: ML is a subset of AI, where a program trains on previous data to make predictions and exhibit "human" behavior.
+Topic:ML
+Description: ML is a subset of AI, where a program trains on previous data to make predictions and exhibit "human" behavior.
+Topic: Model
+Description: A model is a function that maps from an input to a prediction, and finds patterns based on this input data.
+Topic: abstraction
+Description: In software engineering and computer science, abstraction is the process of generalizing concrete details, such as attributes, away from the study of objects and systems to focus attention on details of greater importance. Abstraction is a fundamental concept in computer science and software engineering, especially within the object-oriented programming paradigm. Examples of this include:the usage of abstract data types to separate usage from working representations of data within programs;the concept of functions or subroutines which represent a specific way of implementing control flow;the process of reorganizing common behavior from groups of non-abstract classes into abstract classes using inheritance and sub-classes, as seen in object-oriented programming languages.
+Topic: abstract data type
+Description: Mathematical model for data typesNot to be confused with Abstract type or Algebraic data type.In computer science, an abstract data type ADT is a mathematical model for data types, defined by its behavior semantics from the point of view of a user of the data, specifically in terms of possible values, possible operations on data of this type, and the behavior of these operations. This mathematical model contrasts with data structures, which are concrete representations of data, and are the point of view of an implementer, not a user.Formally, an ADT may be defined as a "class of objects whose logical behavior is defined by a set of values and a set of operations"; this is analogous to an algebraic structure in mathematics. What is meant by "behaviour" varies by author, with the two main types of formal specifications for behavior being axiomatic algebraic specification and an abstract model; these correspond to axiomatic semantics and operational semantics of an abstract machine, respectively. Some authors also include the computational complexity "cost", both in terms of time for computing operations and space for representing values. In practice, many common data types are not ADTs, as the abstraction is not perfect, and users must be aware of issues like arithmetic overflow that are due to the representation. For example, integers are often stored as fixed-width values 32-bit or 64-bit binary numbers, and thus experience integer overflow if the maximum value is exceeded.ADTs are a theoretical concept, in computer science, used in the design and analysis of algorithms, data structures, and software systems, and do not correspond to specific features of computer languages—mainstream computer languages do not directly support formally specified ADTs. However, various language features correspond to certain aspects of ADTs, and are easily confused with ADTs proper; these include abstract types, opaque data types, protocols, and design by contract. ADTs were first proposed by Barbara Liskov and Stephen N. Zilles in 1974, as part of the development of the CLU language.
+Topic: Adaptive Neuro Fuzzy Inference System
+Description:An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system ANFIS is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system. The technique was developed in the early 1990s. Since it integrates both neural networks and fuzzy logic principles, it has potential to capture the benefits of both in a single framework.Its inference system corresponds to a set of fuzzy IF–THEN rules that have learning capability to approximate nonlinear functions. Hence, ANFIS is considered to be a universal estimator. For using the ANFIS in a more efficient and optimal way, one can use the best parameters obtained by genetic algorithm. It has uses in intelligent situational aware energy management system.
+Topic: Affective Computing
+Description: Area of research in computer science aiming to understand the emotional state of usersAffective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. While some core ideas in the field may be traced as far back as to early philosophical inquiries into emotion, the more modern branch of computer science originated with Rosalind Picard's 1995 paper on affective computing and her book Affective Computing published by MIT Press. One of the motivations for the research is the ability to give machines emotional intelligence, including to simulate empathy. The machine should interpret the emotional state of humans and adapt its behavior to them, giving an appropriate response to those emotions.
+Topic: AI-Complete
+Description: Term describing difficult problems in AIIn the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems, assuming intelligence is computational, is equivalent to that of solving the central artificial intelligence problem—making computers as intelligent as people, or strong AI.  To call a problem AI-complete reflects an attitude that it would not be solved by a simple specific algorithm.  AI-complete problems are hypothesised to include computer vision, natural language understanding, and dealing with unexpected circumstances while solving any real-world problem.Currently, AI-complete problems cannot be solved with modern computer technology alone, but would also require human computation.  This property could be useful, for example, to test for the presence of humans as CAPTCHAs aim to do, and for computer security to circumvent brute-force attacks.
+Topic: Algorithmic Probability
+Description:In algorithmic information theory, algorithmic probability, also known as Solomonoff probability, is a mathematical method of assigning a prior probability to a given observation. It was invented by Ray Solomonoff in the 1960s. It is used in inductive inference theory and analyses of algorithms. In his  general theory of inductive inference, Solomonoff uses the method together with Bayes' rule to obtain probabilities of prediction for an algorithm's future outputs.In the mathematical formalism used, the observations have the form of finite binary strings viewed as outputs of Turing machines, and the universal prior is a probability distribution over the set of finite binary strings calculated from a probability distribution over programs that is, inputs to a universal Turing machine.  The prior is universal in theTuring-computability sense, i.e. no string has zero probability. It is not computable, but it can be approximated.
+Topic: AlphaGo
+Description: AlphaGo is a computer program that plays the board game Go. It was developed by the London-based DeepMind Technologies, an acquired subsidiary of Google now Alphabet Inc.. Subsequent versions of AlphaGo became increasingly powerful, including a version that competed under the name Master. After retiring from competitive play, AlphaGo Master was succeeded by an even more powerful version known as AlphaGo Zero, which was completely self-taught without learning from human games. AlphaGo Zero was then generalized into a program known as AlphaZero, which played additional games, including chess and shogi.  AlphaZero has in turn been succeeded by a program known as MuZero which learns without being taught the rules.AlphaGo and its successors use a Monte Carlo tree search algorithm to find its moves based on knowledge previously acquired by machine learning, specifically by an artificial neural network a deep learning method by extensive training, both from human and computer play. A neural network is trained to identify the best moves and the winning percentages of these moves. This neural network improves the strength of the tree search, resulting in stronger move selection in the next iteration.In October 2015, in a match against Fan Hui, the original AlphaGo became the first computer Go program to beat a human professional Go player without handicap on a full-sized 19×19 board. In March 2016, it beat Lee Sedol in a five-game match, the first time a computer Go program has beaten a 9-dan professional without handicap. Although it lost to Lee Sedol in the fourth game, Lee resigned in the final game, giving a final score of 4 games to 1 in favour of AlphaGo. In recognition of the victory, AlphaGo was awarded an honorary 9-dan by the Korea Baduk Association. The lead up and the challenge match with Lee Sedol were documented in a documentary film also titled AlphaGo, directed by Greg Kohs. The win by AlphaGo was chosen by Science as one of the Breakthrough of the Year runners-up on 22 December 2016.At the 2017 Future of Go Summit, the Master version of AlphaGo beat Ke Jie, the number one ranked player in the world at the time, in a three-game match, after which AlphaGo was awarded professional 9-dan by the Chinese Weiqi Association.After the match between AlphaGo and Ke Jie, DeepMind retired AlphaGo, while continuing AI research in other areas. The self-taught AlphaGo Zero achieved a 100–0 victory against the early competitive version of AlphaGo, and its successor AlphaZero was perceived as the world's top player in Go by the end of the 2010s.
+Topic: Ambient Intelligence
+Description: Ambient intelligence AmI is a term used in computing to refer to electronic environments that are sensitive and responsive to the presence of people. The term is generally applied to consumer electronics, telecommunications, and computing. Ambient intelligence is intended to enable devices to work in concert with people in carrying out their everyday life activities in an intuitive way by using information and intelligence hidden in the network connecting these devices. An example of ambient intelligence is the Internet of Things. A typical context of the ambient intelligence environment is the home, but it may also be used in workspaces offices, co-working, public spaces based on technologies such as smart streetlights, and hospital environments.The concept of ambient intelligence was originally developed in the late 1990s by Eli Zelkha and his team at Palo Alto Ventures for the time frame 2010–2020. Developers theorize that as devices grow smaller, more connected, and more integrated into human environments, the technological framework behind them will disappear into the surroundings until only the user interface remains perceivable by people.
+Topic: Natural Language Processing
+Description: Field of linguistics and computer scienceFor other uses, see NLP.This article is about natural language processing done by computers. For the natural language processing done by the human brain, see Language processing in the brain.Natural language processing NLP is an interdisciplinary subfield of computer science and linguistics. It is primarily concerned with giving computers the ability to support and manipulate human language. It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic i.e. statistical and, most recently, neural network-based machine learning approaches. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.Challenges in natural language processing frequently involve speech recognition, natural-language understanding, and natural-language generation.
+Topic: Recurrent Neural Network
+Description: Computational model used in machine learningNot to be confused with recursive neural network.A recurrent neural network RNN is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to the uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state memory to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition. The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response. Both classes of networks exhibit temporal dynamic behavior. A finite impulse recurrent network is a directed acyclic graph that can be unrolled and replaced with a strictly feedforward neural network, while an infinite impulse recurrent network is a directed cyclic graph that can not be unrolled.Additional stored states and the storage under direct control by the network can be added to both infinite-impulse and finite-impulse networks. The storage can also be replaced by another network or graph if that incorporates time delays or has feedback loops. Such controlled states are referred to as gated state or gated memory, and are part of long short-term memory networks LSTMs and gated recurrent units. This is also called Feedforward Neural Network FNN. Recurrent neural networks are theoretically Turing complete and can run arbitrary programs to process arbitrary sequences of inputs.
+Topic: Python
+Description: Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation.Python is dynamically typed and garbage-collected. It supports multiple programming paradigms, including structured particularly procedural, object-oriented and functional programming. It is often described as a "batteries included" language due to its comprehensive standard library.Guido van Rossum began working on Python in the late 1980s as a successor to the ABC programming language and first released it in 1991 as Python 0.9.0. Python 2.0 was released in 2000. Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2.Python consistently ranks as one of the most popular programming languages.
+Topic: Convolutional Neural Network
+Description: Artificial neural networkFor other uses, see CNN disambiguation.Convolutional neural network CNN is a regularized type of feed-forward neural network that learns feature engineering by itself via filters or kernel optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels. However, applying cascaded convolution or cross-correlation kernels,  only 25 neurons are required to process 5x5-sized tiles. Higher-layer features are extracted  from wider context windows, compared to lower-layer features.They have applications in: image and video recognition,recommender systems,image classification,image segmentation,medical image analysis,natural language processing,brain–computer interfaces, andfinancial time series.CNNs are also known as Shift Invariant or Space Invariant Artificial Neural Networks SIANN, based on the shared-weight architecture of the convolution kernels or filters that slide along input features and provide translation-equivariant responses known as feature maps. Counter-intuitively, most convolutional neural networks are not invariant to translation, due to the downsampling operation they apply to the input.Feed-forward neural networks are usually fully connected networks, that is, each neuron in one layer is connected to all neurons in the next layer. The "full connectivity" of these networks make them prone to overfitting data. Typical ways of regularization, or preventing overfitting, include: penalizing parameters during training such as weight decay or trimming connectivity skipped connections, dropout, etc. Robust datasets also increases the probability that CNNs will learn the generalized principles that characterize a given dataset rather than the biases of a poorly-populated set.Convolutional networks were inspired by biological processes in that the connectivity pattern between neurons resembles the organization of the animal visual cortex. Individual cortical neurons respond to stimuli only in a restricted region of the visual field known as the receptive field. The receptive fields of different neurons partially overlap such that they cover the entire visual field.CNNs use relatively little pre-processing compared to other image classification algorithms. This means that the network learns to optimize the filters or kernels through automated learning, whereas in traditional algorithms these filters are hand-engineered. This independence from prior knowledge and human intervention in feature extraction is a major advantage.
+Topic: Computer Science
+Description: Fundamental areas of computer scienceProgramming language theoryComputational complexity theoryArtificial intelligenceComputer architectureComputer science is the study of computation, information, and automation. Computer science spans theoretical disciplines such as algorithms, theory of computation, and information theory to applied disciplines including the design and implementation of hardware and software. Though more often considered an academic discipline, computer science is closely related to computer programming.Algorithms and data structures are central to computer science.The theory of computation concerns abstract models of computation and general classes of problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and for preventing security vulnerabilities. Computer graphics and computational geometry address the generation of images. Programming language theory considers different ways to describe computational processes, and database theory concerns the management of repositories of data. Human–computer interaction investigates the interfaces through which humans and computers interact, and software engineering focuses on the design and principles behind developing software. Areas such as operating systems, networks and embedded systems investigate the principles and design behind complex systems. Computer architecture describes the construction of computer components and computer-operated equipment. Artificial intelligence and machine learning aim to synthesize goal-orientated processes such as problem-solving, decision-making, environmental adaptation, planning and learning found in humans and animals. Within artificial intelligence, computer vision aims to understand and process image and video data, while natural language processing aims to understand and process textual and linguistic data.The fundamental concern of computer science is determining what can and cannot be automated. The Turing Award is generally recognized as the highest distinction in computer science.
+Topic: Chatbot
+Description: A chatbot originally chatterbot is a software application or web interface that aims to mimic human conversation through text or voice interactions. Modern chatbots are typically online and use artificial intelligence AI systems that are capable of maintaining a conversation with a user in natural language and simulating the way a human would behave as a conversational partner. Such technologies often utilize aspects of deep learning and natural language processing, but more simplistic chatbots have been around for decades prior.Recently, this field has gained widespread attention due to the popularity of OpenAI's ChatGPT using GPT-3 or GPT-4, released in 2022, followed by alternatives such as Microsoft's Bing Chat which uses OpenAI's GPT-4 and Google's Bard. Such examples reflect the recent practice of such products being built based upon broad foundational large language models that get fine-tuned so as to target specific tasks or applications i.e. simulating human conversation, in the case of chatbots. Chatbots can also be designed or customized to further target even more specific situations and/or particular subject-matter domains.A major area where chatbots have long been used is in customer service and support, such as with various sorts of virtual assistants. Companies spanning various industries have begun using the latest generative artificial intelligence technologies to power more advanced developments in such areas.
+Topic: Tensor Flow
+Description: TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.TensorFlow was developed by the Google Brain team for internal Google use in research and production. The initial version was released under the Apache License 2.0 in 2015. Google released the updated version of TensorFlow, named TensorFlow 2.0, in September 2019.TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java. This flexibility lends itself to a range of applications in many different sectors.
+Topic: Turing Test
+Description: The Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal robotic.The test was introduced by Turing in his 1950 paper "Computing Machinery and Intelligence" while working at the University of Manchester. It opens with the words: "I propose to consider the question, 'Can machines think?'" Because "thinking" is difficult to define, Turing chooses to "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." Turing describes the new form of the problem in terms of a three-person game called the "imitation game", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: "Are there imaginable digital computers which would do well in the imitation game?" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that "machines can think".Since Turing introduced his test, it has been both highly influential and widely criticised, and has become an important concept in the philosophy of artificial intelligence. Some of its criticisms, such as John Searle's Chinese room, are themselves controversial.
+Topic: Alan Turing
+Description: The creator of the Turing Test.
+Topic: OpenAI
+Description: OpenAI is an American artificial intelligence AI organization consisting of the non-profit OpenAI, Inc. registered in Delaware and its for-profit subsidiary corporation OpenAI Global, LLC. OpenAI researches artificial intelligence with the declared intention of developing "safe and beneficial" artificial general intelligence, which it defines as "highly autonomous systems that outperform humans at most economically valuable work".OpenAI was founded in 2015 by Ilya Sutskever, Greg Brockman, Trevor Blackwell, Vicki Cheung, Andrej Karpathy, Durk Kingma, Jessica Livingston, John Schulman, Pamela Vagata, and Wojciech Zaremba, with Sam Altman and Elon Musk serving as the initial board members. Microsoft provided OpenAI Global LLC with a $1 billion investment in 2019 and a $10 billion investment in 2023.
+Topic: Software
+Description: Software is a set of computer programs and associated documentation and data. This is in contrast to hardware, from which the system is built and which actually performs the work.At the lowest programming level, executable code consists of machine language instructions supported by an individual processor—typically a central processing unit CPU or a graphics processing unit GPU. Machine language consists of groups of binary values signifying processor instructions that change the state of the computer from its preceding state. For example, an instruction may change the value stored in a particular storage location in the computer—an effect that is not directly observable to the user. An instruction may also invoke one of many input or output operations, for example, displaying some text on a computer screen, causing state changes that should be visible to the user. The processor executes the instructions in the order they are provided, unless it is instructed to "jump" to a different instruction or is interrupted by the operating system. As of 2023, most personal computers, smartphone devices, and servers have processors with multiple execution units, or multiple processors performing computation together, so computing has become a much more concurrent activity than in the past.The majority of software is written in high-level programming languages. They are easier and more efficient for programmers because they are closer to natural languages than machine languages. High-level languages are translated into machine language using a compiler, an interpreter, or a combination of the two. Software may also be written in a low-level assembly language that has a strong correspondence to the computer's machine language instructions and is translated into machine language using an assembler.