Part 3/10:
The significance of scaling laws lies in their ability to predict a neural network's performance as it scales in size, data, and compute resources. Essentially, these laws establish stable relationships among the network's size, the training data volume, and the total computational power needed. For Tesla, this means they can forecast how effective FSD V12 will become before investing heavily in development and hardware, saving time and money.