research two important game playing programmes: IBM Deep Blue and Alpha Go and how they are different.

Sure, here is a comparison of IBM's Deep Blue and Google's AlphaGo, two significant game-playing programs:

1. IBM Deep Blue: Deep Blue was a chess-playing computer developed by IBM. It is known for being the first piece of artificial intelligence to win both a chess game and a chess match against a reigning world champion under regular time controls. Deep Blue won its first game against a world champion on February 10, 1996, when it defeated Garry Kasparov in game one of a six-game match. However, Kasparov won three and drew two of the following five games, defeating Deep Blue by a score of 4–2. Deep Blue was then heavily upgraded, and played Kasparov again in May 1997, winning the six-game rematch 3½–2½, ending on May 11. Deep Blue's programming code was written in C and ran under the AIX operating system. It was a brute force approach, evaluating 200 million positions per second.

2. AlphaGo: AlphaGo is a computer program that plays the board game Go. It was developed by DeepMind Technologies which was later acquired by Google. AlphaGo became famous for being the first computer Go program to defeat a human professional Go player, the world champion, and several top-ranked players. Unlike Deep Blue which used brute force to calculate all possible moves, AlphaGo uses a combination of machine learning and tree search techniques, along with extensive training, both from human and computer play to make its moves. It uses a Monte Carlo tree search algorithm, where it selects its moves based on the analysis of more possible outcomes.

Differences: The main difference between the two is their approach to game playing. Deep Blue was based on brute force, calculating as many moves as possible, while AlphaGo uses machine learning and tree search techniques to predict and analyze its moves. This makes AlphaGo more adaptable and capable of learning from its mistakes, while Deep Blue's performance is more static.