According to Gartner, by 2026, more than 70% of generative artificial intelligence (AI) use cases will leverage vector databases to “ground” the AI foundation models.
Artificial intelligence (AI) applications, especially those using large language models (LLMs), are considered some of the most strategic and important in business today. As a result, there is tremendous pressure to make the right choices in terms of the technology stack that supports these applications. This pressure is made more complicated by the fact that the technology is evolving and changing rapidly. AI applications, and LLMs in particular, require storage structures that are different from traditional applications. These requirements have given rise to vector-based storage, which can be in the form of vector capability added to existing data stores or AI-native vector databases.
Read this eBook to learn how LLMs and similar algorithms work, what the different capabilities of vector storage technologies are, and how to choose the best technology for your application.
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