As an illustration, the greatest handicap normally given to a weaker opponent is 9 stones. It was not until August 2008 that a computer won a game against a professional level player at this handicap. It was the Mogo program, which scored this first victory in an exhibition game played during the US Go Congress. By 2013, a win at the professional level of play was accomplished with a four-stone advantage. In October 2015, Google DeepMind's program AlphaGo beat Fan Hui, the European Go champion and a 2 dan (out of 9 dan possible) professional, five times out of five with no handicap on a full size 19×19 board. AlphaGo used a fundamentally different paradigm than earlier Go programs; it included very little direct instruction, and mostly used deep learning where AlphaGo played itself in hundreds of millions of games such that it could measure positions more intuitively. In March 2016, Google next challenged Lee Sedol, a 9 dan considered the top player in the world in the early 21st century, to a five-game match. Leading up to the game, Lee Sedol and other top professionals were confident that he would win; however, AlphaGo defeated Lee in four of the five games. After having already lost the series by the third game, Lee won the fourth game, describing his win as "invaluable". In May 2017, AlphaGo beat Ke Jie, who at the time continuously held the world No. 1 ranking for two years, winning each game in a three-game match during the Future of Go Summit.