DataHour: Significance of Vector Databases in Gen AI
DataHour: Significance of Vector Databases in Gen AI
30 Jan 202412:01pm - 30 Jan 202413:01pm
DataHour: Significance of Vector Databases in Gen AI
About the Event
Vector databases are designed to efficiently handle high-dimensional data, which is common in AI applications dealing with complex and diverse data types. Vector databases excel in similarity search, allowing for the retrieval of data points that are most similar to a given query vector. This is crucial in various AI tasks, including recommendation systems and image recognition.
Vector databases support the storage and retrieval of vector embeddings generated by machine learning models. This is essential for applications like natural language processing, where words and sentences are often represented as vectors. With the ability to efficiently index and search high-dimensional vectors, vector databases contribute to real-time analytics, enabling quick insights and decision-making in AI-driven applications.
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
About the Speaker
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