The AlphaGo artificial intelligence program has been in the news lately for beating Ke Jie, champion of the Chinese board game Go at The Future of Go Summit in Wuzhen, China. The world applauded Google for building an incredibly smart AI program after it beat the world champion thrice, apart from gaining victory over other champions of the board game. Now, Google wants its AI program to help scientists in their important research as it thinks AlphaGo has become smart enough.
AlphaGo will develop "advanced general algorithms" that can help scientists with research on diseases like cancer or discover new materials for building stuff. DeepMind, the Google-owned firm responsible for AlphaGo, thinks that software has got smart enough to face complex situations and figure out solutions for them.
In a recent blog post, DeepMind mentioned, “We have always believed in the potential for AI to help society discover new knowledge and benefit from it, and AlphaGo has given us an early glimpse that this may indeed be possible.” They also say that AlphaGo has been instrumental in training several budding Go players online, teaching them new moves and strategies.
While AlphaGo will be pulled out of the Go gaming community, DeepMind will still publish a final academic journal that will explain the algorithm’s improvements in its efficiency and potential generalised across a broader set of problems. They also believe that other developers will use the findings of AlphaGo and incorporate the learnings into their own AI programs.
DeepMind will also build a teaching tool based on popular demand. The tool will show AlphaGo’s analysis of Go positions, providing an insight into how the program thinks, and hopefully giving all players and fans the opportunity to see the game through the lens of AlphaGo.
With AlphaGo, DeepMind has shown that a set of codes has become smart enough to do what they were meant to in the first place – assist humans in their complex work. It also shows that the geniuses responsible for those smart codes are ready for the next set of challenges that humanity throws at machines.
(Source)
