Understanding context is crucial for enhancing the quality of interactions and decision-making processes between humans and AI systems. Context encompasses situational, social, and interpersonal elements that influence how messages are perceived and understood, and it plays a vital role in shaping meaning and comprehension. The ability to interpret information within its environment, background, and intent is essential for accurate interpretations and communication. This can be achieved through various elements such as linguistic context, cultural context, situational context, and historical context. Contextual understanding allows for more accurate interpretations and enhances communication by capturing nuance and intent. Large language models (LLMs) with retrieval augmented generation (RAG) capabilities are being developed to incorporate detailed context into queries, producing relevant and customized responses. These systems can offer personalized experiences through the accumulation of vectors or embeddings, which encode diverse aspects of data and provide a rich, contextual backdrop for LLMs. By understanding and applying context, AI systems can offer unparalleled personalization and relevance, promising a future where interactions with AI are as nuanced and comprehensible as those between humans.