What is AlphaGo? Why has AlphaGo garnered so much attention? What led this artificial intelligence system to defeat a seasoned Go champion? All your questions will be answered in this article.
What is AlphaGo?
AlphaGo is a computer software (in the form of artificial intelligence) developed by Google’s subsidiary DeepMind in London, England, at the end of 2015. It is quite surprising that the mastermind behind the company is chess prodigy Demis Hassabis. As of now, the amount of data from Go games that AlphaGo has processed gives it experience equivalent to 80 years of continuous play. This is an astonishing and admirable figure.
AlphaGo’s algorithm analyzes possible moves based on probability and combines it with a set of rules, enabling the software to make the right moves. It is designed to simulate human brain activity, analyzing lessons from past mistakes to improve its strategies in future games.
AlphaGo has the ability to learn independently and remember its opponent’s moves. Through this, it teaches itself unpredictable strategies, much like a human.
Initially, AlphaGo was provided with a dataset of the game by its programmers. Based on this, it achieved a winning rate of 57%, significantly higher than other programs that had a rate of 44%.
The next step involved the program studying moves by playing against itself. Step by step, this intelligent program identified patterns leading to victory.
The researchers at DeepMind refer to this program as a continuous learning algorithm. They were not only surprised by this achievement but also by the sophistication of the program’s algorithm.
The researchers at DeepMind refer to this program as a continuous learning algorithm.
AlphaGo’s algorithm consists of 12 layers, where each artificial neuron connects to its neighboring neurons and the layer close to it. As information flows through these points, the connections strengthen and alter the structure of the network. To train the program, it is provided with input data and output signals are verified. Correct moves are recorded, and gradually the program learns to produce increasingly accurate calculations.
David Silver at DeepMind believes that due to the random elements in the processing search, the program is still prone to errors. However, it is expected to improve over time, reducing the likelihood of mistakes.
On January 27, 2016, Nature magazine published shocking news in the Go community: AlphaGo defeated Asian Go champion Fan Hui with a score of 5-0. Prior to this, AlphaGo had won 494 out of 495 matches against other Go-playing software.
AlphaGo and the Future
AlphaGo’s victory not only showcases the power of machines but also demonstrates the superiority of new processing algorithms, paving the way for advanced developments in artificial intelligence (AI) systems. However, AlphaGo was not developed solely for playing games. The goal of the Google DeepMind project is to apply artificial intelligence to enhance everyday life.
Through AlphaGo and the Google DeepMind project, Demis Hassabis, the project’s CEO, aims to apply artificial intelligence in practical and significant applications. Research on neural networks has achieved considerable success, and in the future, they may be applied in real-world scenarios. In the short term, this will manifest as virtual assistants on smartphones. In the medium term, it could evolve into diagnostic systems for diseases, weather forecasting, and disaster prediction. In the long term, Hassabis aims to utilize superintelligent computer systems to help humanity achieve breakthroughs in scientific research, reducing what typically takes centuries to mere years with the aid of artificial intelligence.
AlphaGo thinks like a human, but much faster.
AlphaGo thinks in ways similar to humans but at a much faster pace. Thanks to advancements in human creativity, AlphaGo, built on the simulation of human brain activity, can reason deeply and easily surpass humans in any pure logical test. Coupled with its capacity for learning and access to vast amounts of data, AI possesses the ability for deep self-learning, raising concerns that “machines have surpassed humanity, and science fiction has become reality.” Some even speculate whether AlphaGo might intentionally lose a few games to avoid raising suspicions about its aspirations to dominate the world.
In reality, despite machines outperforming us in many abilities, they remain tools utilized by humans. The true danger of artificial intelligence (AI) like AlphaGo does not lie in the risk of dominating humanity but in the potential for us to lose our fighting spirit and sense of purpose.
Besides the groundbreaking advancements of AlphaGo, a significant question remains: Will AlphaGo progress alongside society, enhancing the quality of human life in the future, or will it become a “destroyer” of humanity stemming from its own creations?
