|Alpha Go - Documentary Now Freely Available|
|Written by Lucy Black|
|Sunday, 15 March 2020|
DeepMind's acclaimed AlphaGo - The Movie, about how AI took on and defeated South Korean Go Master Lee Seedol, has proved a big hit with AI researchers and Go aficionados. It is now on YouTube making it more accessible than ever.
The 90-minute movie was made in 2017, the year after AlphaGo beat Lee Seedol, and was shown that year at film festivals and special screenings. At the beginning of 2018 it was hosted on Netflix and has also been available to Amazon Prime Customers in the US. Now those platforms no longer have it and instead it is on You Tube - which means you can also see it here:
Who would have thought that a documentary about a program that beats a human at a game would win quite so many awards? Its unprecedented level of achievement reflects the fact that it is a well-crafted film that tells a fascinating story. In case you don't already know the background, here's a quick recap condensed from our news item, AlphaGo The Movie - Who Is The Hero
Plucky newcomer to the AI field DeepMind thought that it could do what no one else had - create a program that would play the very difficult and subtle game of Go better than any human. Go is very hard to even start to attack because it is a game of spatial reasoning and strategy. By comparison chess is easy, for AI to tackle.
After five games, and against every expert's expectations, the score was AlphaGo 4 : Lee Sedol 1. It didn't really matter that the machine lost one game, the point was proved.
Only this isn't the story that the film tells. Instead it focuses on the defeat of humanity, or more exactly a single man, but we all know that one small defeat for man is a giant defeat for mankind. The film synopsis reads:
"With more board configurations than there are atoms in the universe, the ancient Chinese game of ‘Go’ has long been considered a grand challenge for artificial intelligence. On March 9 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The Google DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history.
Directed by Greg Kohs with an original score by Academy Award nominee, Hauschka, AlphaGo chronicles a journey from the halls of Oxford, through the backstreets of Bordeaux, past the coding terminals of DeepMind in London, and, ultimately, to the seven-day tournament in Seoul. As the drama unfolds, more questions emerge: What can artificial intelligence reveal about a 3000-year-old game? What can it teach us about humanity?"
Here's the 90-second official trailer:
The film ends with the question of what's next for AlphaGo?
The answer is that as a mystery player in online contests with the assumed names Master and Magister, it took on the top professional Go players, one by one and emerged victorious on each occasion. It then beat the world’s number one player, Ke Jie, at the Future of Go Summit in China in match which it won 3:0. It also proved an unassailable match for humans on other Go formats, such as Pair Go. However, all the human players involved concluded that the game of Go benefited from AlphaGo's involvement with this comment from Gu Li summing up the reaction of professionals who had encountered the machine:
“AlphaGo’s self play games are incredible - we can learn many things from them.”
In December 2019, Lee Sedol announced his resignation from Go at the age of 36, after almost 25 years as a Go professional and 30 years of playing the game. He stated that he would no longer play professionally, because AI is impossible to overcome saying:.
"Even if I become the number one, there is an entity that cannot be defeated,"
The Future of Go summit in China had already marked the end of AlphaGo's career. As it concluded a post on the DeepMind blog announced that:
The research team behind AlphaGo will now throw their energy into the next set of grand challenges, developing advanced general algorithms that could one day help scientists as they tackle some of our most complex problems, such as finding new cures for diseases, dramatically reducing energy consumption, or inventing revolutionary new materials.
We have subsequently reported on DeepMind's progress in the realm of chemistry and it is just one of several ongoing areas of research. Game playing must not be dismissed as trivial, however, as is demonstrated by the AlphaZero algorithm, a successor to the AlphaGo program which mastered chess. This is fully generic algorithm which:
replaces the handcrafted knowledge and domain-specific augmentations used in traditional game-playing programs with deep neural networks and a tabula rasa reinforcement learning algorithm.
Having proved itself with three challenging games, chess, shogi (a Japanese version of chess played on a bigger board) and Go, AlphaZero can now go on to tackle the list of complex problems on DeepMind's bucket list.
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|Last Updated ( Sunday, 15 March 2020 )|