Explore the path towards Artificial General Intelligence in this 36-minute conference talk from GOTO Chicago 2019. Discover why game engines serve as ideal virtual biodomes for AI evolution, and learn about groundbreaking developments in reinforcement learning. Delve into topics such as ML training environments, nature's learning methods, and the concept of tabula rasa through practical examples like a chicken crossing the road. Examine the role of Long Short-Term Memory (LSTM), cooperative and competitive rewards, and the limitations of standard reinforcement learning. Gain insights into innovative approaches like the "Good Puppy, Bad Puppy" method and ML-Agents training environments. Finally, trace the journey from biological to cultural evolution in the context of AI development.