Part 5/6:
One of the more profound outcomes of this research is the ability to train AI systems in simulated environments rather than in the complexities of the real world. As discussed, using these virtual scenarios allows for an expansive and inexpensive means of data collection, sidestepping the difficulties and costs inherent in real-world datasets.
The conversation then shifted towards leveraging Google’s extensive geographical data repositories—such as Google Maps, Street View, and Google Earth—to enhance AI understanding of the real world. The goal is to extract knowledge from static images and create interactive experiences that can bring these environments to life.