A "thought vector" is a concept mainly associated with natural language processing (NLP) and machine learning, particularly in the context of deep learning models. It represents a way of encoding complex ideas, sentiments, or pieces of information as dense, fixed-length numerical vectors in a high-dimensional space. These vectors capture the semantic meaning of the input data (e.g., words, sentences, or entire documents) in a way that allows for easier manipulation and comparison.
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