What Writers Can Learn from Chess Enthusiasts

<a href="https://aibusiness.com/ml/25-years-ago-today-how-deep-blue-vs-kasparov-changed-ai-forever" rel="noopener ugc nofollow" target="_blank">When IBM chess computer Deep Blue beat grandmaster Garry Kasparov in 1997</a>, it would be understandable to predict the end of chess as we know it. Why would we care about human chess if humans are no longer the best at chess? Yet while computers have gotten stronger and stronger over the last 25 years, chess is more popular than ever. How is this possible? <a href="https://www.nytimes.com/2022/06/17/crosswords/chess/chess-is-booming.html" rel="noopener ugc nofollow" target="_blank">One factor in the rise of chess is certainly the COVID-19 pandemic</a>. With people spending lots of time at home, many inevitably turned to chess. They wanted a distraction from fear and the horrors of the outside world. But I believe there is another major factor at play as well. Chess computers have created exciting new possibilities for chess enthusiasts that have never been seen before. While I do not advocate for playing only moves computers think are best, many computer ideas are novel and exciting. For example, some chess computers have <a href="https://www.chess.com/article/view/10-positions-chess-engines-just-dont-understand" rel="noopener ugc nofollow" target="_blank">traditionally cared a lot about material</a> (winning/losing pieces) and not as much about other important factors like piece activity (potential to attack) and king safety (potential to defend). Stronger computers, however, have been more willing to sacrifice material for exciting while justified attacks. <a href="https://www.youtube.com/watch?v=8dT6CR9_6l4" rel="noopener ugc nofollow" target="_blank">One game in this video shows a supercomputer giving up four pawns to another supercomputer only to build up pressure and decisively win later</a>! <a href="https://medium.com/getting-into-chess/what-writers-can-learn-from-chess-enthusiasts-af25058caa2c">Click Here</a>