A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources. Which solution will meet this requirement?
C. Create an Amazon Bedrock knowledge base.
This would allow the company use the knowledge base for Retrieval Augmented Generation (RAG) to enhance the model's knowledge with company's private data sources.
Explicação:
O Amazon Bedrock permite que você complemente um modelo de fundação (Foundation Model – FM), como o Amazon Titan, com dados proprietários da sua empresa sem precisar treinar ou ajustar o modelo.
Isso é feito por meio da criação de uma base de conhecimento, que permite que o modelo:
Busque e consulte dados relevantes em fontes privadas (como documentos, bancos de dados ou repositórios internos).
Ofereça respostas mais precisas e contextualizadas com base nas informações da empresa.Use a técnica conhecida como RAG (Retrieval-Augmented Generation).
Create an Amazon Bedrock knowledge base: This solution allows the company to supplement the Amazon Titan foundation model with their own relevant, private data sources. The knowledge base enables the foundation model to access specific, proprietary data during inference, enhancing the model's responses and making it more tailored to the company’s needs. This is especially useful when the model needs to be supplemented with data that is not part of the model’s initial training data.
Create an Amazon Bedrock knowledge base.
An Amazon Bedrock knowledge base allows you to incorporate your company's proprietary data into the foundation model. By feeding the model with relevant information, you can enhance its ability to generate more accurate and informative responses.
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