We used the OpenAI embeddings API to generate embeddings, saved those embeddings in a local vector store , then asked the OpenAI chat model two questions about a single retrieved document ...

Vector databases offer a mind-numbing new level of capability to search unstructured data in particular, but can tackle semi-structured and even structured data as well. Diving into vectors and search ...

Zilliz is looking to become the preferred vector database choice for LLM-powered applications through strategic enhancements and a cost-effective new pricing model that now includes a free tier. The ...

AI inference then compares vector-embedded data using the model and newly supplied queries. This is carried out by very high performance processors, most notably by graphical processing units ...

Using vector databases and search brings with it a few common generative AI risks such as data quality, modeling issues, and more. New issues include hallucinations and confabulations .

Now, let the show begin: Dump all the data into the vector DB, add a bit of RAG architecture, sprinkle in a bit of prompt engineering, and voila! The gen AI wave has officially arrived in your ...

Frank Liu, ML architect at Zilliz, joined DBTA's webinar, 'Vector Databases Have Entered the Chat-How ChatGPT Is Fueling the Need for Specialized Vector Storage,' to explore how purpose-built vector ...

A Vector DB stores and manages unstructured data — text, images, audio, etc. — as vector embeddings (numerical format). These embeddings capture the semantic relationships between the data points.

And like the other Firefly models, the vector model, too, was trained on data from Adobe Stock. In its beta, Illustrator will now let you create entire scenes through a text prompt.