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This feature was designed to allow users to integrate custom deep learning models directly into OpenSearch . It addresses several core functionalities:

: A new REST API to upload proprietary models by splitting them into smaller chunks for storage.

: APIs to load and unload models into memory on demand, preventing the need for cluster restarts.

: They are critical for tasks such as anomaly detection in surveillance, medical image analysis, and forgery detection.

: Extract basic concepts like edges, contours, and simple textures.

Broadly, a is a data representation automatically extracted by a Deep Neural Network (DNN).

: Unlike traditional "handcrafted" features (like color or shape) that require expert design, deep features are learned directly from raw data. Hierarchical Abstraction :

: Once loaded, these models can be used for real-time inference tasks like text embedding or image classification.