AlphaGo and What it Means for Artificial Intelligence

  • April 27, 2016
  • Nolan

dreamstime_s_59228080In the artificial intelligence and machine learning community the big story a few weeks ago was the “Go” competition between the Lee Sodol and the computer program AlphaGo build by Google DeepMind. As of today March 15, 2016 AlphaGo is winning the match against Sodol with a score of 3 games to 1. AlphaGo is the next progression in game playing artificial intelligence following in the footsteps of its ancestors IBM Deep Blue(Chess playing computer) and IBM Watson(Jeopardy playing computer). The difference between AlphaGo and its predecessors is the complexity of the game Go. Go is played on a very large board and allows for extremely large number of moves for each turn which quickly makes the feasibility of many other game playing algorithms impossible.

The achievement of AlphaGo and the DeepMind team is incredible and needs to be applauded. The solution they arrived at for an extremely complicated problem has achieved exceptional results and has done wonderful things for artificial intelligence research. However many people are considering this the last great game for machines to conquer but I think this cant be farther from the truth.

Every time we write a program to solve a problem we increase our own understanding of that problem and the outcome of that program helps us better understand and make discoveries we hadn’t previously realized. In the case of Deep Blue and chess, the game has never been the same but the players today are better than they have ever been before because the theoretical and practical understanding of the game has increased significantly due to artificial intelligence. This is the same with Go and all areas where artificial intelligence has or can be applied.

Programs written by people only reflect what we already know in a way that our minds have trouble operating. Artificial intelligence and machine learning gives us just another tool to research a topic and grow our understanding. In the case of BPM, introduction of new analytical technology in the space will only help us better understand business problems and help us make better decisions. These new technologies aren’t competitors as many people suggest but tools to be used to help us grow.

There is no doubt still room to grow and learn within most games computers have been used to optimize and there are still an uncountable number of problems in the real world that artificial intelligence can be used to help better understand. The word of game theory and artificial intelligence goes far beyond the bounds of board games and I wouldn’t consider any of the great board games to be completely solved yet.

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