AWS Machine Learning - AI

NOVEMBER 7, 2024

The solution presented in this post takes approximately 15–30 minutes to deploy and consists of the following key components: Amazon OpenSearch Service Serverless maintains three indexes : the inventory index, the compatible parts index, and the owner manuals index. The following diagram illustrates the workflow of the agent.

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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 22, 2024

Since Amazon Bedrock is serverless, you don’t have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. Furthermore, our solutions are designed to be scalable, ensuring that they can grow alongside your business.

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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

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. However, some components may incur additional usage-based costs.

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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

JANUARY 29, 2025

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. Accelerate your generative AI application development by integrating your supported custom models with native Bedrock tools and features like Knowledge Bases, Guardrails, and Agents.

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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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AWS Machine Learning - AI

NOVEMBER 6, 2024

Limited scalability – As the volume of requests increased, the CCoE team couldn’t disseminate updated directives quickly enough. Going forward, the team enriched the knowledge base (S3 buckets) and implemented a feedback loop to facilitate continuous improvement of the solution.

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AWS Machine Learning - AI

SEPTEMBER 24, 2024

It’s a fully serverless architecture that uses Amazon OpenSearch Serverless , which can run petabyte-scale workloads, without you having to manage the underlying infrastructure. This solution uses Amazon Bedrock LLMs to find answers to questions from your knowledge base. Choose your new knowledge base to open it.

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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

MARCH 20, 2025

It integrates with existing applications and includes key Amazon Bedrock features like foundation models (FMs), prompts, knowledge bases, agents, flows, evaluation, and guardrails. Justin Ossai is a GenAI Labs Specialist Solutions Architect based in Dallas, TX.

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AWS Machine Learning - AI

JANUARY 22, 2025

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and quickly integrate and deploy them into your applications using AWS tools without having to manage the infrastructure. These filters need to be added and updated manually for each query.

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AWS Machine Learning - AI

JANUARY 29, 2025

With Amazon Bedrock Knowledge Bases , you securely connect FMs in Amazon Bedrock to your company data for RAG. Amazon Bedrock Knowledge Bases facilitates data ingestion from various supported data sources; manages data chunking, parsing, and embeddings; and populates the vector store with the embeddings.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

API Gateway is serverless and hence automatically scales with traffic. The advantage of using Application Load Balancer is that it can seamlessly route the request to virtually any managed, serverless or self-hosted component and can also scale well. It’s serverless so you don’t have to manage the infrastructure.

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AWS Machine Learning - AI

OCTOBER 1, 2024

Voice-based assistants like Alexa demonstrate how we are entering an era of conversational interfaces. We explore how to build a fully serverless, voice-based contextual chatbot tailored for individuals who need it. All the services that we use are serverless and fully managed by AWS. We discuss this later in the post.

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AWS Machine Learning - AI

SEPTEMBER 26, 2024

Although Amazon Q is a great way to get started with no code for business users, Amazon Bedrock Knowledge Bases offers more flexibility at the API level for generative AI developers; we explore both these solutions in the following sections. How do I keep my generative AI applications up to date with an ever-evolving knowledge base?”

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AWS Machine Learning - AI

MARCH 20, 2025

The Asure team was manually analyzing thousands of call transcripts to uncover themes and trends, a process that lacked scalability. Staying ahead in this competitive landscape demands agile, scalable, and intelligent solutions that can adapt to changing demands.

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AWS Machine Learning - AI

MAY 13, 2024

It’s serverless, so you don’t have to manage any infrastructure. To implement our RAG system, we utilized a dataset of 95,000 radiology report findings-impressions pairs as the knowledge source. This dataset was uploaded to Amazon Simple Service (Amazon S3) data source and then ingested using Knowledge Bases for Amazon Bedrock.

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AWS Machine Learning - AI

MARCH 7, 2025

During the solution design process, Verisk also considered using Amazon Bedrock Knowledge Bases because its purpose built for creating and storing embeddings within Amazon OpenSearch Serverless. Vaibhav Singh is a Product Innovation Analyst at Verisk, based out of New Jersey. Tarik Makota is a Sr.

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AWS Machine Learning - AI

OCTOBER 15, 2024

By using Amazon Bedrock Agents , action groups , and Amazon Bedrock Knowledge Bases , we demonstrate how to build a migration assistant application that rapidly generates migration plans, R-dispositions, and cost estimates for applications migrating to AWS.

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AWS Machine Learning - AI

AUGUST 2, 2024

An approach to product stewardship with generative AI Large language models (LLMs) are trained with vast amounts of information crawled from the internet, capturing considerable knowledge from multiple domains. However, their knowledge is static and tied to the data used during the pre-training phase.

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AWS Machine Learning - AI

OCTOBER 23, 2024

Built using Amazon Bedrock Knowledge Bases , Amazon Lex , and Amazon Connect , with WhatsApp as the channel, our solution provides users with a familiar and convenient interface. Cost efficiency is achieved through minimized development resources and lower operational costs compared to maintaining custom knowledge management systems.

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AWS Machine Learning - AI

MAY 30, 2024

With Bedrock’s serverless experience, one can get started quickly, privately customize FMs with their own data, and easily integrate and deploy them into applications using the AWS tools without having to manage any infrastructure. The VitechIQ user experience can be split into two process flows: document repository, and knowledge retrieval.

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AWS Machine Learning - AI

JANUARY 29, 2025

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. Accelerate your generative AI application development by integrating your supported custom models with native Bedrock tools and features like Knowledge Bases, Guardrails, and Agents.

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AWS Machine Learning - AI

MARCH 5, 2025

To scale ground truth generation and curation, you can apply a risk-based approach in conjunction with a prompt-based strategy using LLMs. Scaling ground truth generation with a pipeline To automate ground truth generation, we provide a serverless batch pipeline architecture, shown in the following figure. 201% $12.2B

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AWS Machine Learning - AI

MARCH 14, 2024

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage any infrastructure. Knowledge base responses come with source citations to improve transparency and minimize hallucinations.

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AWS Machine Learning - AI

MAY 9, 2024

Verisk FAST’s AI companion aims to alleviate this burden by not only providing 24/7 support for business processing and configuration questions related to FAST, but also tapping into the immense knowledge base to provide an in-depth, tailored response. However, they understood that this was not a one-and-done effort.

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AWS Machine Learning - AI

SEPTEMBER 9, 2024

Because Amazon Bedrock is serverless, you don’t have to manage infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you’re already familiar with. Outside of work, he enjoys playing lawn tennis and reading books.

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AWS Machine Learning - AI

SEPTEMBER 18, 2024

After the profile is converted into text that explains the profile, a RAG framework is launched using Amazon Bedrock Knowledge Bases to retrieve related industry insights (articles, pain points, and so on). Building your knowledge base for the industry insights document is the final prerequisite.

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AWS Machine Learning - AI

OCTOBER 23, 2024

The serverless experience offered by Amazon Bedrock enables quick deployment, private customization, and secure integration of these models into applications without the need to manage underlying infrastructure. It can handle large volumes of data and interactions, which is crucial for enterprises requiring robust applications.

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AWS Machine Learning - AI

SEPTEMBER 23, 2024

An LLM is prompted to formulate a helpful answer based on the user’s questions and the retrieved chunks. Amazon Bedrock Knowledge Bases offers a streamlined approach to implement RAG on AWS, providing a fully managed solution for connecting FMs to custom data sources.

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AWS Machine Learning - AI

JUNE 5, 2024

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using the AWS tools without having to manage any infrastructure. Jason Westra is a Senior Solutions Architect for AWS AI/ML startups.

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Cloudera

DECEMBER 20, 2023

Pinecone | Vector Database Highlights: The partnership will see Cloudera integrate Pinecone’s best-in-class vector database into Cloudera Data Platform (CDP), enabling organizations to easily build and deploy highly scalable, real time, AI-powered applications on Cloudera.

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AWS Machine Learning - AI

MARCH 28, 2024

One of the main advantages of the MoE architecture is its scalability. It provides a modular and flexible framework for combining LLMs with other components, such as knowledge bases, retrieval systems, and other AI tools, to create powerful and customizable applications. AJ Dhimine is a Solutions Architect at AWS.

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Altexsoft

MARCH 30, 2023

Moreover, it automatically grows and reduces cloud resources to meet demand changes and guarantee cost-effectiveness along with scalability. Besides that, Databricks maintains a unified Knowledge Base where users can look for an answer to a specific question or a solution to a particular problem, no matter where they run the lakehouse.

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AWS Machine Learning - AI

JULY 30, 2024

Mediasearch Q Business supercharges the way you consume media files by using them as part of the knowledge base used by Amazon Q Business to generate reliable answers to user questions. Mediasearch Q Business builds on the Mediasearch solution powered by Amazon Kendra and enhances the search experience using Amazon Q Business.

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