Dec. 22, 2023, 2:47 p.m. | Vince Lwt

DEV Community dev.to

In the era of AI-driven applications, the ability to efficiently handle and search through vector data is crucial.


Vector databases are designed specifically for this purpose, providing a robust infrastructure for applications such as retrieval-augmented generation (RAG) apps, recommendation systems, and advanced search engines.


Whether you're creating an app to "Chat with a PDF" or need to power a complex recommendation system, vector databases are the engines under the hood that make it all possible.


Today we're diving into 6 …

advanced ai ai app app applications apps data database databases github infrastructure opensource power rag recommendation recommendation systems retrieval retrieval-augmented search systems through vector vector databases

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

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Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Risk Management - Machine Learning and Model Delivery Services, Product Associate - Senior Associate-

@ JPMorgan Chase & Co. | Wilmington, DE, United States

Senior ML Engineer (Speech/ASR)

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