1. Semantic Memory – Facts and Knowledge
Semantic memory stores general world knowledge and facts that are not tied to personal experience. It includes information like "Paris is the capital of France" or "LangChain is a framework for developing language model applications." In AI, this can be represented by structured databases, knowledge graphs, or embeddings of factual data.
2. Episodic Memory – Experiences and Events
Episodic memory refers to the recall of specific events or personal experiences in time and space — like remembering the first time you deployed a LangChain agent. In AI systems, episodic memory can be modeled by logging interactions or maintaining user-specific conversational history that helps the model contextualize its responses.
3. Procedural Memory – Skills and Habits
Procedural memory enables the performance of tasks without conscious thought, such as riding a bike or writing code fluently. In AI, this is similar to learned behaviors encoded in model weights or routines — like fine-tuned model workflows that "instinctively" handle certain tasks like parsing inputs or generating summaries.