Architecture AWS Knowledge Base Machine Learning 
AWS Machine Learning - AI
FEBRUARY 29, 2024
Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. RAG is a popular technique that combines the use of private data with large language models (LLMs).
AWS Machine Learning - AI
APRIL 8, 2024
RAG allows models to tap into vast knowledge bases and deliver human-like dialogue for applications like chatbots and enterprise search assistants. Solution overview In this post, we demonstrate how to create a RAG-based application using LlamaIndex and an LLM. Download press releases to use as our external knowledge base.
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AWS Machine Learning - AI
FEBRUARY 19, 2024
One way to enable more contextual conversations is by linking the chatbot to internal knowledge bases and information systems. Integrating proprietary enterprise data from internal knowledge bases enables chatbots to contextualize their responses to each user’s individual needs and interests.
AWS Machine Learning - AI
FEBRUARY 8, 2024
You can now use Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock to configure specialized agents that seamlessly run actions based on natural language input and your organization’s data. The following diagram illustrates the solution architecture. The following are some example prompts: Create a new claim.
AWS Machine Learning - AI
NOVEMBER 27, 2023
Consider the following machine learning (ML) problem: user asks a large language model (LLM) question: “How to filter and search models in Amazon Bedrock?”. The choice of vector database is an important architectural decision. Further, we show how to preprocess a dataset for RAG. Access to Amazon OpenSearch as a vector database.
AWS Machine Learning - AI
APRIL 23, 2024
However, to unlock the long-term success and viability of these AI-powered solutions, it is crucial to align them with well-established architectural principles. The AWS Well-Architected Framework provides best practices and guidelines for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud.
AWS Machine Learning - AI
MAY 14, 2024
An important aspect of developing effective generative AI application is Reinforcement Learning from Human Feedback (RLHF). RLHF is a technique that combines rewards and comparisons, with human feedback to pre-train or fine-tune a machine learning (ML) model. You can build such chatbots following the same process.
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