Part 9/14:
The Software and AI Complexity
On the software side, neural networks, reinforcement learning, and simulation environments must mature significantly. Tesla’s extensive world simulator, employed for self-driving, illustrates how complex generating and maintaining realistic, comprehensive virtual environments is—imagine extending that to indoor spaces, gardens, or outdoor terrains with unpredictable species and objects.
Simulating every potential scenario humans encounter daily—pets, children, varying furniture, and outdoor conditions—is a gargantuan task, requiring immense computational resources and advanced algorithms. The difficulty is compounded by the need to recognize and understand the physics of countless tools, objects, and environmental factors dynamically.