Table of Contents
Whats the point of AlphaGo?
AlphaGo is an artificial intelligence (AI) agent that is specialized to play Go, a Chinese strategy board game, against human competitors. AlphaGo is a Google DeepMind project. The ability to create a learning algorithm that can beat a human player at strategic games is a measure of AI development.
What can we learn from AlphaGo?
What AlphaGo Can Teach Us About How People Learn
- Application. Prediction. Human-computer interaction.
- Company. Alphabet.
- End User. Big company. Research.
- Sector. Research. IT.
- Technology. Machine learning.
How was AlphaGo made?
Algorithm. As of 2016, AlphaGo’s algorithm uses a combination of machine learning and tree search techniques, combined with extensive training, both from human and computer play. It uses Monte Carlo tree search, guided by a “value network” and a “policy network,” both implemented using deep neural network technology.
How long did it take to train AlphaGo?
AlphaGo uses 50 GPUs to train the network and it takes 3 weeks. The SL policy network achieves a 57\% accuracy. It sounds not too accurate but this policy network can beat an advanced amateur already. During game simulation (discussed later), we need something faster to narrow our search for moves.
Who won AlphaGo?
Lee Se-dol is the only human to ever beat the AlphaGo software developed by Google’s sister company Deepmind. In 2016, he took part in a five-match showdown against AlphaGo, losing four times but beating the computer once.
Why does AlphaGo play so well?
It used a revolutionary new algorithm — one that relied not on previous brute-force algorithms like Minimax but one that sought to replicate the intuition of the masters with powerful reinforcement learning methods. In the end, AlphaGo Zero’s only worthy match was itself… so it learned by playing against itself.
Who made AlphaGo?
DeepMind
The system was invented by DeepMind, co-founded by scientist Demis Hassabis. Five months earlier, AlphaGo had beaten European champion Fan Hui, becoming the first program to defeat a professional player.
How did AlphaGo lose?
In 2016, he took part in a five-match showdown against AlphaGo, losing four times but beating the computer once. The South Korean said he had decided to retire after realising: “I’m not at the top even if I become the number one.” AlphaGo was developed by Deepmind, which is owned by Google’s parent company Alphabet.
Who is the best Go player in the world?
International
| # | Player | Total |
|---|---|---|
| 1 | Lee Changho | 21 |
| 2 | Lee Sedol | 18 |
| 3 | Cho Hunhyun | 11 |
| 4 | Ke Jie | 10 |
Who can beat AlphaGo?
Lee Se-dol
Lee Se-dol is the only human to ever beat the AlphaGo software developed by Google’s sister company Deepmind. In 2016, he took part in a five-match showdown against AlphaGo, losing four times but beating the computer once.
How did AlphaGo get so good at go?
With AlphaGo, however, the computer scientists simply used lots and lots of games from a myriad of players, who were all at different levels of Go knowledge and experience. And unlike when DeepBlue was unveiled, when AlphaGo was first shown to the world, Go players paid attention. They saw that AlphaGo was playing in innovative ways.
What was AlphaGo’s 37th move in Game 2?
With the 37th move in the match’s second game, AlphaGo landed a surprise on the right-hand side of the 19-by-19 board that flummoxed even the world’s best Go players, including Lee Sedol. “That’s a very strange move,” said one commentator, himself a nine dan Go player, the highest rank there is.
How did AlphaGo Zero compare to previous versions?
AlphaGo Zero quickly surpassed the performance of all previous versions and also discovered new knowledge, developing unconventional strategies and creative new moves, including those which beat the World Go Champions Lee Sedol and Ke Jie. These creative moments give us confidence that AI can be used as a positive multiplier for human ingenuity.
Did Lee Sedol’s move take AlphaGo by surprise?
As we found out after the game, AlphaGo made a disastrous play with its very next move, and just minutes later, after analyzing the board position, the machine determined that its chances of winning had suddenly fallen off a cliff. Commentator and nine dan Go player Michael Redmond called Lee Sedol’s move brilliant: “It took me by surprise.