AWS Certified AI Practitioner AIF-C01 Practice Question

Embeddings map text (or other data) into high-dimensional numeric vectors in such a way that semantically similar items are located near one another in vector space. This representation enables semantic or "meaning-based" search because similarity can be computed with simple distance metrics. Tokenization merely splits text into tokens, chunking breaks long text into manageable pieces, and diffusion models are used for iterative data generation (e.g., images), none of which alone provide semantic vector representations for search.