Part 3/15:
A neural network's "size" refers primarily to its parameters—the weights and biases that dictate how input data is processed and decisions are made. Increasing the model size by a factor of 10 implies a corresponding growth in the number of parameters—think of it as having a more detailed, nuanced map of the driving environment inside the network.
Why Larger Models Matter
A bigger neural network can capture more complex patterns and subtle nuances in the data, leading to better decision-making. For driving, this means richer interpretation of sensor inputs, more refined control commands, and more human-like reactions. Essentially, a larger model can make the vehicle smarter, more adaptable, and more reliable.