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Answer: By connecting Bedrock Knowledge Bases to internal data sources like S3
Amazon Bedrock supports organizations in augmenting foundation models with proprietary internal knowledge through its **Knowledge Bases** feature. This allows organizations to connect to internal data sources like Amazon S3 buckets, where proprietary data can be stored. The Knowledge Bases feature creates vector embeddings of the data and enables the foundation model to retrieve and use this proprietary information during inference, without requiring full retraining of the model. **Why other options are incorrect:** - **B**: Retraining foundation models with raw PDFs is not the primary method; this would be expensive and time-consuming compared to using Knowledge Bases. - **C**: Customers cannot upload data directly into the model's neural layers; this is not how foundation models are augmented. - **D**: While vector databases are involved, Bedrock provides integrated Knowledge Bases that handle the vectorization and retrieval, not requiring external-only solutions.
Author: Ritesh Yadav
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How does Amazon Bedrock support organizations that want to augment a foundation model with proprietary internal knowledge?
A
By connecting Bedrock Knowledge Bases to internal data sources like S3
B
By retraining the foundation model with raw PDFs
C
By allowing customers to upload data directly into the model's neural layers
D
By requiring external vector databases only
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