Question: In 2015, Google created a machine learning system that could beat a human in the game of Go. This extremely complex game is thought to have more gameplay possibilities than there are atoms of the universe. The first version of the system won by observing hundreds of thousands of hours of human gameplay; the second version learned how to play by getting rewards while playing against itself. How would you describe this transition to different machine learning approaches?

1. The system went from supervised learning to reinforcement learning.
2. The system evolved from supervised learning to unsupervised learning.
3. The system evolved from unsupervised learnin9 to supervised learning.
4. The system evolved from reinforcement learning to unsupervised learning.

Answer: The correct answer of the above question is Option A:The system went from supervised learning to reinforcement learning.