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From prototype to production: Vector databases in generative AI applications - Stack Overflow

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Since the rise of ChatGPT, the general public has realized that generative artificial intelligence (GenAI) could potentially transform our lives. The availability of large language models (LLMs) has also changed how developers build AI-powered applications and has led to the emergence of various new developer tools. Although vector databases have been around long before ChatGPT, they have become an integral part of the GenAI technology stack, as vector databases can address some of LLMs’ key limitations, such as hallucinations and lack of long-term memory This article first introduces vector databases and their use cases. Next, you will learn more about how vector databases are designed to help developers get started with building GenAI applications quickly. As a developer advocate at Weaviate, an open-source vector database, I will use Weaviate to demonstrate relevant concepts as we go along. In the final discussion, you will learn how they can address the challenges enterprises face

Since the rise of ChatGPT, the general public has realized that generative artificial intelligence (GenAI) could potentially transform our lives. The availability of large language models (LLMs) has also changed how developers build AI-powered applications and has led to the emergence of various new developer tools. Although vector databases have been around long before ChatGPT, they have become an integral part of the GenAI technology stack, as vector databases can address some of LLMs’ key limitations, such as hallucinations and lack of long-term memory This article first introduces vector d

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