The meaning behind ‘artificial’ and ‘intelligence’

17

September

2016

5/5 (1)

 


Artificial intelligence was officially born in 1956 when John McCarthy organized a workshop at the Dartmouth Summer Research Project[1]. The goal was to create an artificial intelligence being. Decades of unsuccessful trials in the attempt to create an artificial being that had an independent intuition have passed. After waiting for 60 years, this March of 2016, the artificial intelligence program AlphaGo beat Lee Sedol, the grand master in Go (the ancient Chinese board game).

But is Go such a difficult game?

Although the concept is simple, the number of moves are almost endless. Go is a game of two and the goal is to surround a total area that is larger than that of your opponent in a 19 by 19 grid. To give you a comparison, in chess 35 is the number of possible moves a player can choose from in a given turn. In Go, a player can choose from 200 different possibilities in one turn. Now, if one were to account to the total number of possible moves of a Go player in a given game, it could amount to 10 to the power of 170. So how much is 10^170? A lot, given that the number of atoms in the universe is estimated to be around 10^81. Therefore, AlphaGo has achieved a big milestone for beating the best Go human master in such a complex game with almost endless possibilities.

How did AlphaGo manage to beat Lee Sedol? Let’s start from the general idea. AlphaGo uses a deep learning technique that is programed to mimic a human neuron. Deep learning belongs to a branch of algorithms and techniques called machine learning. And Artificial intelligence can be defined as a set of algorithms and techniques that mimic the human intelligence. In short, AlphaGo is specific deep learning system of machine learning that built upon algorithms and techniques.

My guess is that deep learning is going to help us understand the human brain better and consequently develop improved techniques for learning. Why? Because deep learning operates and processes information like a human neuron. By feeding the machine a lot of data, the computer can learn to recognize and classify objects by itself[2]. This leads to the creation of the so-called artificial intuition. As a result, I can imagine a world where artificial intuition will provide out-of-the-box perspectives and guide human beings to solve grand challenges.

AlphaGo vs. Lee Sedol enlightened our species once again. Let me explain. After watching the match between AlphaGo and Lee Sedol, Go players grasp an understanding of the possibilities of deep learning. Go players were fascinated with how AlphaGo was playing because it played unlike any human has played the game before. It made moves that did not seem to make sense at first sight but were very fruitful at last. By playing with or watching AlphaGo play, players are influenced by the way the machine plays the game. In turn players are able to learn from AlphaGo by observing these new strategies, which creates a feedback loop. The master himself, Lee Sedol expressed his positive thoughts after the match “I have improved already. It has given me new ideas” referring to AlphaGo[3].

This has been the first glimpse of what AI can bring in the field of learning. Artificial intuition challenges us to think differently, which will reinforce and disrupt the way the human brain thinks time and time again.  Because of this constant thinking enhancements, I believe that Al will challenge the “Homo Sapiens Sapiens” status that modern humans currently hold.


Sources:

[1] http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html

[2] http://www0.cs.ucl.ac.uk/staff/d.silver/web/Publications.html

[3] https://www.wired.com/2016/05/google-alpha-go-ai/

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