AWS Machine Learning - AI

JULY 3, 2024

Knowledge Bases for Amazon Bedrock is a fully managed capability that helps you securely connect foundation models (FMs) in Amazon Bedrock to your company data using Retrieval Augmented Generation (RAG). In the following sections, we demonstrate how to create a knowledge base with guardrails.

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AWS Machine Learning - AI

NOVEMBER 20, 2024

One of its key features, Amazon Bedrock Knowledge Bases , allows you to securely connect FMs to your proprietary data using a fully managed RAG capability and supports powerful metadata filtering capabilities. Context recall – Assesses the proportion of relevant information retrieved from the knowledge base.

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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. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.

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AWS Machine Learning - AI

MARCH 1, 2024

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With a knowledge base, 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

APRIL 23, 2024

This post explores the new enterprise-grade features for Knowledge Bases on Amazon Bedrock and how they align with the AWS Well-Architected Framework. AWS Well-Architected design principles RAG-based applications built using Knowledge Bases for Amazon Bedrock can greatly benefit from following the AWS Well-Architected Framework.

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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

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.

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AWS Machine Learning - AI

MAY 31, 2024

Knowledge Bases for Amazon Bedrock is a fully managed RAG capability that allows you to customize FM responses with contextual and relevant company data. Crucially, if you delete data from the source S3 bucket, it’s automatically removed from the underlying vector store after syncing the 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.

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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

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. You can simply connect QnAIntent to company knowledge sources and the bot can immediately handle questions using the allowed content.

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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

MARCH 20, 2025

It often requires managing multiple machine learning (ML) models, designing complex workflows, and integrating diverse data sources into production-ready formats. By converting unstructured document collections into searchable knowledge bases, organizations can seamlessly find, analyze, and use their data.

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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

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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TechBeacon

DECEMBER 3, 2020

The automated program, dubbed Tay, responded to tweets and incorporated the content of those tweets into its knowledge base, riffing off the topics to carry on conversations. In 2016, Microsoft released a prototype chatbot on Twitter.

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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

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 documents are chunked into smaller segments for more effective processing.

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CIO

NOVEMBER 1, 2024

The team opted to build out its platform on Databricks for analytics, machine learning (ML), and AI, running it on both AWS and Azure. The firm had a “mishmash” of BI and analytics tools in use by more than 200 team members across the four business units, and again, Beswick sought a standard platform to deliver the best efficiencies.

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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

AUGUST 5, 2024

Included with Amazon Bedrock is Knowledge Bases for Amazon Bedrock. As a fully managed service, Knowledge Bases for Amazon Bedrock makes it straightforward to set up a Retrieval Augmented Generation (RAG) workflow. 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.

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CIO

NOVEMBER 1, 2024

The team opted to build out its platform on Databricks for analytics, machine learning (ML), and AI, running it on both AWS and Azure. The firm had a “mishmash” of BI and analytics tools in use by more than 200 team members across the four business units, and again, Beswick sought a standard platform to deliver the best efficiencies.

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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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O'Reilly Media - Ideas

FEBRUARY 28, 2019

In a recent post , we described what it would take to build a sustainable machine learning practice. These projects are built and supported by a stable team of engineers, and supported by a management team that understands what machine learning is, why it’s important, and what it’s capable of accomplishing.

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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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Altexsoft

FEBRUARY 5, 2020

In this article, we’ll discuss what the next best action strategy is and how businesses define the next best action using machine learning-based recommender systems. You can choose from two approaches to enabling the next best action: rule-based or machine learning-based recommendations.

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Ivanti

JUNE 11, 2024

However, AI-based knowledge management can deliver outstanding benefits – especially for IT teams mired in manually maintaining knowledge bases. It uses machine learning algorithms to analyze and learn from large datasets, then uses that to generate new content.

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AWS Machine Learning - AI

DECEMBER 23, 2024

GraphRAG with Neptune is built into Amazon Bedrock Knowledge Bases , offering an integrated experience with no additional setup or additional charges beyond the underlying services. To learn more, see Retrieve data and generate AI responses with Amazon Bedrock Knowledge Bases.

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AWS Machine Learning - AI

JANUARY 22, 2025

The following screenshot shows an example of the event filters (1) and time filters (2) as seen on the filter bar (source: Cato knowledge base ). Retrieval Augmented Generation (RAG) Retrieve relevant context from a knowledge base, based on the input query. This context is augmented to the original query.

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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

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

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 11, 2025

One of the most critical applications for LLMs today is Retrieval Augmented Generation (RAG), which enables AI models to ground responses in enterprise knowledge bases such as PDFs, internal documents, and structured data. These five webpages act as a knowledge base (source data) to limit the RAG models response.

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AWS Machine Learning - AI

NOVEMBER 1, 2024

Although tagging is supported on a variety of Amazon Bedrock resources —including provisioned models, custom models, agents and agent aliases, model evaluations, prompts, prompt flows, knowledge bases, batch inference jobs, custom model jobs, and model duplication jobs—there was previously no capability for tagging on-demand foundation models.

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