AWS Machine Learning - AI

AUGUST 5, 2024

An end-to-end RAG solution involves several components, including a knowledge base, a retrieval system, and a generation system. Solution overview The solution provides an automated end-to-end deployment of a RAG workflow using Knowledge Bases for Amazon Bedrock. Choose Sync to initiate the data ingestion job.

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AWS Machine Learning - AI

APRIL 26, 2024

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With Knowledge Bases for Amazon Bedrock, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data for fully managed Retrieval Augmented Generation (RAG).

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AWS Machine Learning - AI

OCTOBER 29, 2024

We have built a custom observability solution that Amazon Bedrock users can quickly implement using just a few key building blocks and existing logs using FMs, Amazon Bedrock Knowledge Bases , Amazon Bedrock Guardrails , and Amazon Bedrock Agents. Additionally, you can choose what gets logged.

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AWS Machine Learning - AI

MAY 31, 2024

However, if you want to use an FM to answer questions about your private data that you have stored in your Amazon Simple Storage Service (Amazon S3) bucket, you need to use a technique known as Retrieval Augmented Generation (RAG) to provide relevant answers for your customers. The following diagram depicts a high-level RAG architecture.

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AWS Machine Learning - AI

MARCH 20, 2025

It often requires managing multiple machine learning (ML) models, designing complex workflows, and integrating diverse data sources into production-ready formats. Traditionally, documents from portals, email, or scans are stored in Amazon Simple Storage Service (Amazon S3) , requiring custom logic to split multi-document packages.

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AWS Machine Learning - AI

JULY 1, 2024

Generative artificial intelligence (AI)-powered chatbots play a crucial role in delivering human-like interactions by providing responses from a knowledge base without the involvement of live agents. Create new generative AI-powered intent in Amazon Lex using the built-in QnAIntent and point the knowledge base.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

Amazon Bedrock Agents coordinates interactions between foundation models (FMs), knowledge bases, and user conversations. The agents also automatically call APIs to perform actions and access knowledge bases to provide additional information. The following diagram illustrates the workflow of the agent.

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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. Knowledge Bases for Amazon Bedrock provides fully managed RAG to supply the agent with access to your data.

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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.

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AWS Machine Learning - AI

SEPTEMBER 25, 2024

Amazon Bedrock Knowledge Bases is a fully managed capability that helps you implement the entire RAG workflow—from ingestion to retrieval and prompt augmentation—without having to build custom integrations to data sources and manage data flows. Latest innovations in Amazon Bedrock Knowledge Base provide a resolution to this issue.

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AWS Machine Learning - AI

OCTOBER 31, 2024

The Lambda function interacts with Amazon Bedrock through its runtime APIs, using either the RetrieveAndGenerate API that connects to a knowledge base, or the Converse API to chat directly with an LLM available on Amazon Bedrock. If you don’t have an existing knowledge base, refer to Create an Amazon Bedrock knowledge base.

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AWS Machine Learning - AI

JULY 10, 2024

Knowledge Bases for Amazon Bedrock is a fully managed service that helps you implement the entire Retrieval Augmented Generation (RAG) workflow from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows, pushing the boundaries for what you can do in your RAG workflows.

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AWS Machine Learning - AI

JULY 2, 2024

In November 2023, we announced Knowledge Bases for Amazon Bedrock as generally available. Knowledge bases allow Amazon Bedrock users to unlock the full potential of Retrieval Augmented Generation (RAG) by seamlessly integrating their company data into the language model’s generation process.

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AWS Machine Learning - AI

APRIL 10, 2025

They offer fast inference, support agentic workflows with Amazon Bedrock Knowledge Bases and RAG, and allow fine-tuning for text and multi-modal data. To do so, we create a knowledge base. Complete the following steps: On the Amazon Bedrock console, choose Knowledge Bases in the navigation pane. Choose Next.

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Cloudera

NOVEMBER 1, 2023

This AMP is built on the foundation of one of our previous AMP s, with the additional enhancement of enabling customers to create a knowledge base from data on their own website using Cloudera DataFlow (CDF) and then augment questions to the chatbot from that same knowledge base in Pinecone.

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AWS Machine Learning - AI

NOVEMBER 15, 2024

As Principal grew, its internal support knowledge base considerably expanded. With QnABot, companies have the flexibility to tier questions and answers based on need, from static FAQs to generating answers on the fly based on documents, webpages, indexed data, operational manuals, and more.

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AWS Machine Learning - AI

DECEMBER 4, 2024

When users pose questions through the natural language interface, the chat agent determines whether to query the structured data in Amazon Athena through the Amazon Bedrock IDE function, search the Amazon Bedrock knowledge base, or combine both sources for comprehensive insights.

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AWS Machine Learning - AI

AUGUST 5, 2024

In this solution, audio files stored in mp3 format are first uploaded to Amazon Simple Storage Service (Amazon S3) storage. Included with Amazon Bedrock is Knowledge Bases for Amazon Bedrock. With Knowledge Bases for Amazon Bedrock, we first set up a vector database on AWS.

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AWS Machine Learning - AI

AUGUST 28, 2024

The complexity of developing and deploying an end-to-end RAG solution involves several components, including a knowledge base, retrieval system, and generative language model. Solution overview The solution provides an automated end-to-end deployment of a RAG workflow using Knowledge Bases for Amazon Bedrock.

Knowledge Base 82

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AWS Machine Learning - AI

MARCH 18, 2025

This transcription then serves as the input for a powerful LLM, which draws upon its vast knowledge base to provide personalized, context-aware responses tailored to your specific situation. These data sources provide contextual information and serve as a knowledge base for the LLM.

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AWS Machine Learning - AI

SEPTEMBER 19, 2024

Amazon Bedrock Knowledge Bases provides foundation models (FMs) and agents in Amazon Bedrock contextual information from your company’s private data sources for Retrieval Augmented Generation (RAG) to deliver more relevant, accurate, and customized responses. Amazon Bedrock Knowledge Bases offers a fully managed RAG experience.

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AWS Machine Learning - AI

JANUARY 29, 2025

Accelerate your generative AI application development by integrating your supported custom models with native Bedrock tools and features like Knowledge Bases, Guardrails, and Agents. Sufficient local storage space, at least 17 GB for the 8B model or 135 GB for the 70B model. The following diagram illustrates the end-to-end flow.

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AWS Machine Learning - AI

JANUARY 13, 2025

Enterprises provide their developers, engineers, and architects with a range of knowledge bases and documents, such as usage guides, wikis, and tools. But these resources tend to become siloed over time and inaccessible across teams, resulting in reduced knowledge, duplication of work, and reduced productivity.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

Depending on the use case and data isolation requirements, tenants can have a pooled knowledge base or a siloed one and implement item-level isolation or resource level isolation for the data respectively. Hasan helps design, deploy and scale Generative AI and Machine learning applications on AWS.

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AWS Machine Learning - AI

NOVEMBER 20, 2024

In this post, we explore how you can use Amazon Q Business , the AWS generative AI-powered assistant, to build a centralized knowledge base for your organization, unifying structured and unstructured datasets from different sources to accelerate decision-making and drive productivity.

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AWS Machine Learning - AI

MARCH 4, 2025

Knowledge base integration Incorporates up-to-date WAFR documentation and cloud best practices using Amazon Bedrock Knowledge Bases , providing accurate and context-aware evaluations. Amazon Textract extracts the content from the uploaded documents, making it machine-readable for further processing.

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AWS Machine Learning - AI

MARCH 20, 2025

Amazon Bedrock offers fine-tuning capabilities that allow you to customize these pre-trained models using proprietary call transcript data, facilitating high accuracy and relevance without the need for extensive machine learning (ML) expertise.

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AWS Machine Learning - AI

NOVEMBER 14, 2024

Solution overview This solution uses the Amazon Bedrock Knowledge Bases chat with document feature to analyze and extract key details from your invoices, without needing a knowledge base. The storage layer uses Amazon Simple Storage Service (Amazon S3) to hold the invoices that business users upload.

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AWS Machine Learning - AI

SEPTEMBER 24, 2024

We will walk you through deploying and testing these major components of the solution: An AWS CloudFormation stack to set up an Amazon Bedrock knowledge base, where you store the content used by the solution to answer questions. This solution uses Amazon Bedrock LLMs to find answers to questions from your knowledge base.

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AWS Machine Learning - AI

NOVEMBER 15, 2024

To help with fairness in AI applications that are built on top of Amazon Bedrock, application developers should explore model evaluation and human-in-the-loop validation for model outputs at different stages of the machine learning (ML) lifecycle. Amazon Bedrock Knowledge Bases manages the end-to-end RAG workflow for you.

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AWS Machine Learning - AI

DECEMBER 11, 2024

When Amazon Q Business became generally available in April 2024, we quickly saw an opportunity to simplify our architecture, because the service was designed to meet the needs of our use caseto provide a conversational assistant that could tap into our vast (sales) domain-specific knowledge bases.

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AWS Machine Learning - AI

NOVEMBER 22, 2024

Instead of handling all items within a single execution, Step Functions launches a separate execution for each item in the array, letting you concurrently process large-scale data sources stored in Amazon Simple Storage Service (Amazon S3), such as a single JSON or CSV file containing large amounts of data, or even a large set of Amazon S3 objects.

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AWS Machine Learning - AI

AUGUST 15, 2024

QnABot on AWS (an AWS Solution) now provides access to Amazon Bedrock foundational models (FMs) and Knowledge Bases for Amazon Bedrock , a fully managed end-to-end Retrieval Augmented Generation (RAG) workflow. If a knowledge base ID is configured , the Bot Fulfillment Lambda function forwards the request to the knowledge base.

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AWS Machine Learning - AI

DECEMBER 18, 2024

Enterprises that have adopted ServiceNow can improve their operations and boost user productivity by using Amazon Q Business for various use cases, including incident and knowledge management. Navigate to the deployed web experience URL and sign with your AWS IAM Identity Center credentials.

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AWS Machine Learning - AI

MARCH 19, 2024

In the evolving landscape of manufacturing, the transformative power of AI and machine learning (ML) is evident, driving a digital revolution that streamlines operations and boosts productivity. Answers are generated through the Amazon Bedrock knowledge base with a RAG approach. Choose Create knowledge base.

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AWS Machine Learning - AI

NOVEMBER 6, 2024

Data source curation and authorization – The CCoE team created several Amazon Simple Storage Service (Amazon S3) buckets to store their curated content, including cloud governance best practices, patterns, and guidance. They set up a general bucket for all users and specific buckets tailored to each business unit’s needs.

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AWS Machine Learning - AI

APRIL 24, 2024

It uses the provided conversation history, action groups, and knowledge bases to understand the context and determine the necessary tasks. This is based on the instructions that are interpreted by the assistant as per the system prompt and user’s input. Additionally, you can access device historical data or device metrics.

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