"There are clear cases in which "understanding" literally applies and clear cases in which it does not apply; and these two sorts of cases are all I need for this argument"

The quote by John Searle discuss the nuanced and frequently discussed idea of "understanding", particularly in the context of artificial intelligence and cognitive science. Searle is most likely referencing his famous thought experiment, the Chinese Space Argument, which questions the nature of understanding in devices versus people.

In this context, "clear cases in which 'comprehending' actually uses" refers to scenarios where comprehension is real and intrinsic, usually related to human cognition. For instance, when a person reads a story in their native language, they don't simply procedure signs; they get in touch with meanings, feelings, and context. This kind of understanding is mindful, includes a depth of contextual and cultural understanding, and includes a gratitude of subtleties, feelings, and objectives behind the communication.

Alternatively, the "clear cases in which it does not apply" typically connect to procedures carried out by devices. A computer or a program may imitate understanding by processing data and reacting appropriately-- such as translating a language or playing chess-- however such actions are typically based upon algorithmic treatments instead of understanding. Devices don't "comprehend" in the exact same method a human does since they do not have awareness, subjective experience, and intentionality, all of which are important elements of real understanding.

By highlighting "these 2 sorts of cases", Searle establishes a dichotomy that underpins his argument versus the notion that syntactical manipulation by computer systems corresponds to semantic understanding. He presumes that while devices may successfully mimic tasks that require understanding, they do not possess intrinsic understanding. This difference is essential in disputes over expert system's capabilities and restrictions, specifically worrying whether AI can ever really duplicate the human mind's nuanced understanding. Searle's argument challenges us to reassess what it implies to "understand" and whether this distinctively human trait can ever be really replicated by makers.