Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships between words. Word embeddings are useful for tasks such as language translation, sentiment analysis, and document clustering.
A Large Language Model refers to a type of advanced Artificial Intelligence model designed to exhibit human-like language understanding and generation abilities. LLMs are…