quot;; in the middle stage, features such as &quot;my knight can capture their queen&quot;; and later, features such as &quot;my position is solid&quot;. Because of this, each layer has its own set of 256 convolution filters trained for different jobs, and each of these filters is not just 3&nbsp;×&nbsp;3 in two dimensions, but 256&nbsp;×&nbsp;3&nbsp;×&nbsp;3 in three dimensions, sliding over the output of each of the previous layer's different filters (see Figure 6). So, at each layer there is a set of 