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Summary: This is a summary of an article originally published by The New Stack. Read the full original article here →
It seems like nearly every day brings a new AI application that pushes the boundaries of what is possible. Despite all the attention https://thenewstack.io/is-generative-ai-augmenting-our-jobs-or-about-to-take-them/ is garnering, some high-profile missteps have reminded the world once again of “garbage in, garbage out.”
There are many considerations when deciding on how to evaluate a new or existing database to handle your generative AI workloads. The essential capabilities needed to deliver AI workloads are shown and explained in further detail in the following diagram: Ingestion/Vectorization
While it’s too early to say whether a multi-model database is equally adept at storing vector embeddings as a native vector database, we expect these data structures to converge.
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