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AlfaGo and the Future

What does it mean for Deep Learning to recently beat Go champion Lee Sedol? Or what did it mean back in 1997 for Deep Blue to beat chess champion Garry Kasparov? Is the purpose of AI to only demonstrate that it can win against humans, or is it much more than winning?

Such wins demonstrate the capabilities of AI, and open up new avenues for the tools and techniques used. In the case of Deep Blue developed by IBM, it was better search and evaluation algorithms, combined with a supercomputer to defeat a world champion. Similar AI algorithms were then applied to other applications including search engines.

AI community continued its fascination of winning in games involving intelligence, with IBM Watson turning out to be a winner of quiz show Jeopardy. Watson even received the first place prize of $1 million. The AI techniques such as Natural Language Processing and Machine Learning that Watson used to win the competition are today driving the Watson Cloud Platform to understand unstructured documents and create question answering systems.

AI has come a long way since Deep Blue’s win. Recently Google took up the challenge of creating a Deep Learning based AI called AlfaGo to beat the world champion of Go, and it was successful in doing so. The same algorithms that won the game of Go, also power Google’s softwares that recognize spoken words, understand natural language, classify images.

Deep Learning has now evolved enough that it was able to beat a Go champion, and it looks like it can win in any kind of competitive game involving human mind. It seems, the AI community might have to invent new games to further show capabilities of AI.

P.S: Looking forward to see a match between robots and the world champions of football, with no red cards, of course.

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