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The latest wave of generative AI, like large language models, has paved the way for significant advancements in the utilization of vector embeddings and vector similarity search. Large language models, such as OpenAI's GPT, are capable of learning complex patterns and representations from vast amounts of text, enabling them to generate rich semantic embeddings for words, sentences, and documents. By leveraging these learned embeddings, developers can now harness the power of vector similarity search, revolutionizing the way information is organized, retrieved, and analyzed in various domains, including fraud detection, recommendation systems, and information retrieval.Study guide: GitHub Actions certification
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