Text, images, and videos are all examples of unstructured data. Vector databases capture and store the essence of a particular piece of data that a machine-learning program or LLM can then pull from.

For example, while a relational database can ... These embeddings form the foundation of vector databases, allowing them to perform similarity searches and contextual data retrieval.

In today’s data-driven world, the exponential growth of unstructured data is a phenomenon that demands our attention. The rise of generative AI and large language models (LLMs) has added even ...

With vector databases, the question is converted into an embedding and used to perform the search. For example, I might say, “Find me a midpriced SLR camera that’s new to the market ...

a lot easier to operate [with a vector database],” he says. He points to GDPR compliance as an example. If you have to delete a record, it’s fairly trivial to do in a database, but it’s much ...

adding that the example illustrates the impact at the application level. “The database has to be able to provide those capabilities,” he says. The introduction of vector search is the latest step in ...

For example, you can capture the meaning of a ... on embeddings to determine whether certain content is held by a vector database. Sometimes, an attacker won’t even have to use fancy attacks ...

Liberty is the founder and CEO of vector database pioneer Pinecone, which has raised over $138 million including a $100 million round in 2023. As it turns out, random projections, which was his ...