Parameters are what we update during training. One parameter is one scalar among the learned variables of the model. Audio-visual inputs do sometimes end up ha

Parameters are what we update during training. One parameter is one scalar among the learned variables of the model. Audio-visual inputs do sometimes end up having 1B+ individual values, but there isn't necessarily a 1:1 relationship between input size and parameter count. In many deep neural nets, most of the weights are internal. They're used to process the outputs of earlier layers of the network. This is where the term "deep" comes from.