on. Convolutional networks take small, trainable filters and slide them across images, just like applying a blur in Photoshop. However, the output is interpreted as gathered data rather than as a visual medium. This is an efficient way to recognize interesting features and applies well to 2D grid-based board games like Go and chess.</p>
        <p>In an approach inspired by our own visual cortex, stacking these filters in sequence creates a hierarchy of complexity, with earlier layers recognizing lines, cor