QuestionQ2

Introduction to Generative AI for Software Testing

Which of the following statements BEST characterizes the purpose of embeddings in Large Language Models (LLMs) when processing and generating content?

  • A They define the maximum length of text an LLM can process at one time to maintain coherence.
  • B They break down input text into smaller units, such as words or sub-words, for individual processing.
  • C They are numerical representations of tokens that capture their semantic, syntactic, and contextual relationships.
  • D They control the randomness or creativity of an LLM's outputs during text generation.
Explanation

Embeddings are numerical vector representations of tokens or text that encode learned semantic and linguistic relationships, allowing the model to operate on language mathematically. OpenAI describes an embedding as a vector of floating-point numbers whose distances represent text relatedness.

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