Vector Databases Tutorial: Advanced AI App Data Access
These databases are revolutionising data storage and access and advancing AI and machine learning applications
Specialised database systems called vector databases are made with the purpose of effectively storing, managing, and retrieving high-dimensional vectors
These are particularly good at handling high-dimensional data, which frequently has hundreds or thousands of dimensions
They easily interface with pipelines and models for machine learning, making it easier to train, implement, and infer AI models
The capacity of vector databases to conduct quick and precise similarity searches is one of their best qualities
Vector databases are remarkably accurate in providing personalised suggestions based on analysis of user behaviour and preferences
By using vector databases to track transactions in real-time, financial institutions can accurately detect and stop fraudulent activity