AWS Machine Learning - AI

DECEMBER 11, 2024

Earlier this year, we published the first in a series of posts about how AWS is transforming our seller and customer journeys using generative AI. Field Advisor serves four primary use cases: AWS-specific knowledge search With Amazon Q Business, weve made internal data sources as well as public AWS content available in Field Advisors index.

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AWS Machine Learning - AI

OCTOBER 31, 2024

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

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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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AWS Machine Learning - AI

NOVEMBER 7, 2024

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. You also need to consider the operational characteristics and noisy neighbor risks.

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AWS Machine Learning - AI

NOVEMBER 1, 2024

Organizations need to prioritize their generative AI spending based on business impact and criticality while maintaining cost transparency across customer and user segments. This visibility is essential for setting accurate pricing for generative AI offerings, implementing chargebacks, and establishing usage-based billing models.

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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. On the AWS CloudFormation console, create a new stack.

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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

MARCH 20, 2025

With Amazon Bedrock Data Automation, enterprises can accelerate AI adoption and develop solutions that are secure, scalable, and responsible. Cross-Region inference enables seamless management of unplanned traffic bursts by using compute across different AWS Regions. For example, a request made in the US stays within Regions in the US.

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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. RAG is a popular technique that combines the use of private data with large language models (LLMs).

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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

NOVEMBER 6, 2024

The challenge: Enabling self-service cloud governance at scale Hearst undertook a comprehensive governance transformation for their Amazon Web Services (AWS) infrastructure. The CCoE implemented AWS Organizations across a substantial number of business units.

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AWS Machine Learning - AI

JULY 1, 2024

Organizations strive to implement efficient, scalable, cost-effective, and automated customer support solutions without compromising the customer experience. You can simply connect QnAIntent to company knowledge sources and the bot can immediately handle questions using the allowed content. Create an Amazon Lex bot.

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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

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. The workflow is as follows: The user logs into SageMaker Unified Studio using their organizations SSO from AWS IAM Identity Center.

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CIO

NOVEMBER 1, 2024

As part of MMTech’s unifying strategy, Beswick chose to retire the data centers and form an “enterprisewide architecture organization” with a set of standards and base layers to develop applications and workloads that would run on the cloud, with AWS as the firm’s primary cloud provider. The biggest challenge is data.

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AWS Machine Learning - AI

MARCH 11, 2025

OpenAI launched GPT-4o in May 2024, and Amazon introduced Amazon Nova models at AWS re:Invent in December 2024. 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.

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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

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

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

AUGUST 5, 2024

Amazon Transcribe is an AWS AI service that makes it straightforward to convert speech to text. In this post, we show how Amazon Transcribe and Amazon Bedrock can streamline the process to catalog, query, and search through audio programs, using an example from the AWS re:Think podcast series. and the AWS SDK for Python (Boto3).

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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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CIO

NOVEMBER 1, 2024

As part of MMTech’s unifying strategy, Beswick chose to retire the data centers and form an “enterprisewide architecture organization” with a set of standards and base layers to develop applications and workloads that would run on the cloud, with AWS as the firm’s primary cloud provider. The biggest challenge is data.

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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. Prerequisites To perform this solution, complete the following: Create and activate an AWS account. Install Python 3.7

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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. This serverless approach eliminates the need for infrastructure management while providing enterprise-grade security and scalability.

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AWS Machine Learning - AI

JANUARY 29, 2025

Large organizations often have many business units with multiple lines of business (LOBs), with a central governing entity, and typically use AWS Organizations with an Amazon Web Services (AWS) multi-account strategy. LOBs have autonomy over their AI workflows, models, and data within their respective AWS accounts.

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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. Our partnership with AWS and our commitment to be early adopters of innovative technologies like Amazon Bedrock underscore our dedication to making advanced HCM technology accessible for businesses of any size.

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AWS Machine Learning - AI

SEPTEMBER 24, 2024

Working with the AWS Generative AI Innovation Center , DoorDash built a solution to provide Dashers with a low-latency self-service voice experience to answer frequently asked questions, reducing the need for live agent assistance, in just 2 months. You can deploy the solution in your own AWS account and try the example solution.

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AWS Machine Learning - AI

MARCH 18, 2025

Today, were announcing a significant enhancement to Amazon Bedrock Guardrails: AWS Identity and Access Management (IAM) policy-based enforcement. Antonio Rodriguez is a Principal Generative AI Specialist Solutions Architect at AWS. Although some of these calls might include the required guardrail, others dont.

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AWS Machine Learning - AI

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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AWS Machine Learning - AI

MARCH 14, 2024

Generative AI with AWS The emergence of FMs is creating both opportunities and challenges for organizations looking to use these technologies. With Amazon Bedrock, your content is not used to improve the base models and is not shared with third-party model providers. This supports safer adoption.

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AWS Machine Learning - AI

FEBRUARY 25, 2025

This post demonstrates how you can use Amazon Bedrock Agents to create an intelligent solution to streamline the resolution of Terraform and AWS CloudFormation code issues through context-aware troubleshooting. This setup makes sure that AWS infrastructure deployments using IaC align with organizational security and compliance measures.

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AWS Machine Learning - AI

MARCH 13, 2025

The security measures are inherently integrated into the AWS services employed in this architecture. Using batch inference in Amazon Bedrock demonstrates efficient batch processing capabilities and anticipates further scalability with AWS planning to deploy more cloud instances.

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AWS Machine Learning - AI

APRIL 24, 2024

With AWS generative AI services like Amazon Bedrock , developers can create systems that expertly manage and respond to user requests. It uses the provided conversation history, action groups, and knowledge bases to understand the context and determine the necessary tasks. The AI assistant interprets the user’s text input.

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Xebia

MARCH 11, 2025

With the rise of AI, you also need a knowledge base. These knowledge bases can be hosted in OpenSearch. This is a textbook example coming from the AWS documentation pages. The truth is it is easy, but it all depends on how much you care about the data you are ingesting. Let me go one step back.

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AWS Machine Learning - AI

JULY 11, 2024

This solution shows how Amazon Bedrock agents can be configured to accept cloud architecture diagrams, automatically analyze them, and generate Terraform or AWS CloudFormation templates. Diagram analysis and query generation : The Amazon Bedrock agent forwards the architecture diagram location to an action group that invokes an AWS Lambda.

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AWS Machine Learning - AI

MARCH 7, 2025

An AWS Batch job reads these documents, chunks them into smaller slices, then creates embeddings of the text chunks using the Amazon Titan Text Embeddings model through Amazon Bedrock and stores them in an Amazon OpenSearch Service vector database. Vaibhav Singh is a Product Innovation Analyst at Verisk, based out of New Jersey.

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AWS Machine Learning - AI

AUGUST 6, 2024

The solution is powered by Amazon Bedrock and customized with data to go beyond traditional email-based systems. And, we’ll cover related announcements from the recent AWS New York Summit. To offer greater flexibility and accuracy in building RAG-based applications, we announced multiple new capabilities at the AWS New York Summit.

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