Which of the following describes 'Knowledge Representation' in AI?

Knowledge Representation in AI refers to the methods and structures used to represent information about the world in a way that a computer system can utilize to solve complex tasks such as diagnosing a problem, understanding natural language, or reasoning. This includes storing facts about objects, concepts, and the relationships between them, enabling AI systems to perform tasks that require understanding and manipulation of knowledge.

The focus on how AI stores facts and relationships emphasizes the importance of organizing information in a structured format. For instance, techniques such as ontologies, semantic networks, and frames are employed in this context, allowing AI to reason about the data it holds and make inferences based on that data.

In contrast, interpretations of visual data, generating human-like responses, and processing spoken language pertain to different aspects of AI functionality, such as computer vision, natural language processing, and conversational agents, rather than the underlying organization and representation of knowledge.