You have an Azure subscription. You need to build an app that will compare documents for semantic similarity. The solution must meet the following requirements: - Return numeric vectors that…

GPT-3.5 is a generative language model designed for tasks like text generation and summarization, not primarily for creating numerical vector representations for semantic similarity.

GPT-4 is a highly advanced generative language model, but like GPT-3.5, its primary purpose is not generating embeddings for semantic similarity, and using it for this task would be inefficient or require additional processing.

Azure OpenAI embeddings models (like `text-embedding-ada-002`) are specifically designed to convert text into numerical vector representations (embeddings) that capture semantic meaning, making them ideal for tasks like semantic similarity comparison and minimizing development effort by providing a ready-to-use solution for this task.

DALL-E is an image generation model and is completely unrelated to processing text for semantic similarity or returning numeric vectors for documents.