Explaining AI Fundamentals: Vector Embeddings and Memory Mechanisms
_jaydeepkarale · x · 2026-07-30
An infographic explaining the foundational mechanisms behind modern AI applications:
- Vector Embeddings: AI doesn't understand text like humans do; it converts sentences into numerical vectors. Similar meanings produce similar vectors, enabling semantic search, RAG, and AI Agents to retrieve information by meaning rather than exact keywords.
- Memory: LLMs don't inherently remember past conversations. Memory modules provide the necessary context from previous interactions, enabling long-term personalized experiences while managing token costs through windowing.
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