This is in contrast to traditional computer vision models which disregard the context of their labels (in other words, a "normal" image classifier works just as well if your labels are "cat" and "dog" or "foo" and "bar"; behind the scenes it just converts them into a numeric identifier with no particular meaning).

In real world tasks, the "glyphs" are actually patterns of pixels (features) representing abstractions like colors, shapes, textures, and patterns (and even concepts like people and locations ).