WaterForge on Instagram: "As neural networks become very wide, their activations and outputs tend to follow a Gaussian distribution due to the central limit effect: each neuron computes a weighted sum of many inputs, and the sum of many independent contributions approaches a normal distribution. This leads to a view where an infinitely wide neural network with random weights can be represented as a Gaussian process, meaning its outputs over inputs follow a joint multivariate normal distribution