These tools are easy to use, even for people with no background in programming or video editing. Such is the case with a certain AI-based technique called 'deepfake' (combination of 'deep learning' and 'fake'), which uses deep neural networks to easily create fake videos in which the face of one person is superimposed on that of another. Unfortunately, just like any technology in the world, AI can be used by those with less noble intentions. From reducing pollution to making roads safer with self-driving cars to enabling better healthcare through medical big-data analysis, AI still has plenty of untapped potential. Designed to help unearth even more strategic moves, the summit included various game formats such as pair Go, team Go, and a match with the world’s number one player Ke Jie.Artificial intelligence (AI) contributes significantly to good in the world. The five-day festival created an opportunity to explore the mysteries of Go in a spirit of mutual collaboration with the country’s top players. ‍Four months later, AlphaGo took part in the Future of Go Summit in China, the birthplace of Go. This online player achieved 60 straight wins in time-control games against top international players. ‍In January 2017, we revealed an improved, online version of AlphaGo called Master. Players of all levels have extensively examined these moves ever since. During the games, AlphaGo played several inventive winning moves, several of which - including move 37 in game two - were so surprising that they upended hundreds of years of wisdom. This was the first time a computer Go player had ever received the accolade. ‍The game earned AlphaGo a 9 dan professional ranking, the highest certification. This landmark achievement was a decade ahead of its time. AlphaGo's 4-1 victory in Seoul, South Korea, on March 2016 was watched by over 200 million people worldwide. AlphaGo won the first ever game against a Go professional with a score of 5-0.ĪlphaGo then competed against legendary Go player Mr Lee Sedol, the winner of 18 world titles, who is widely considered the greatest player of the past decade. In October 2015, AlphaGo played its first match against the reigning three-time European Champion, Mr Fan Hui.

AlphaGo went on to defeat Go world champions in different global arenas and arguably became the greatest Go player of all time. This process is known as reinforcement learning. Over time, AlphaGo improved and became increasingly stronger and better at learning and decision-making. Then we had it play against different versions of itself thousands of times, each time learning from its mistakes. We introduced AlphaGo to numerous amateur games to help it develop an understanding of reasonable human play. The other neural network, the “value network”, predicts the winner of the game. One neural network, the “policy network”, selects the next move to play. These neural networks take a description of the Go board as an input and process it through a number of different network layers containing millions of neuron-like connections. We created AlphaGo, a computer program that combines advanced search tree with deep neural networks. To capture the intuitive aspect of the game, we needed a new approach.

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