Semantic similarity and lexical similarity are two distinct ways of comparing text, with the key difference being meaning versus surface-level features.
Word embeddings are a fundamental concept in Natural Language Processing (NLP), enabling machines to understand and process human language effectively.
Due to superposition and entanglement, a quantum computer can, for certain problems, explore a vast number of possibilities in parallel, potentially solving some problems much faster than classical computers.