Part 4/12:
Human memory is inherently associative and temporal, meaning similar memories often link based on meaning or timing. Embeddings facilitate this, enabling the system to efficiently retrieve related memories based on content and proximity in time.
Microservice Implementation
The Embedding Service harnesses Google's Universal Sentence Encoder (version five), producing 512-dimensional vectors suitable for short text snippets—up to 500 characters. Its small, efficient design runs on Flask for rapid prototyping, ready for scaling into larger networks. This service's role is pivotal in making memories searchable, ensuring the system can handle vast databases of stored experiences.