AWS Machine Learning Blog

MAY 15, 2025

As part of this initiative, Vxceed developed LimoConnectQ using Amazon Bedrock and AWS Lambda. This solution enables efficient document searching, simplifies trip booking, and enhances operational decisions while maintaining data security and protection. Book airport to my office transfer next Monday at 10 AM.

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AWS Machine Learning Blog

OCTOBER 29, 2024

This solution uses decorators in your application code to capture and log metadata such as input prompts, output results, run time, and custom metadata, offering enhanced security, ease of use, flexibility, and integration with native AWS services.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using Amazon Web Services (AWS) services without having to manage infrastructure. AWS Lambda The API is a Fastify application written in TypeScript.

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AWS Machine Learning Blog

JULY 15, 2024

Today, Mixbook is the #1 rated photo book service in the US with 26 thousand five-star reviews. Years ago, Mixbook undertook a strategic initiative to transition their operational workloads to Amazon Web Services (AWS) , a move that has continually yielded significant advantages.

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AWS Machine Learning Blog

DECEMBER 4, 2024

SageMaker Unified Studio combines various AWS services, including Amazon Bedrock , Amazon SageMaker , Amazon Redshift , Amazon Glue , Amazon Athena , and Amazon Managed Workflows for Apache Airflow (MWAA) , into a comprehensive data and AI development platform. Navigate to the AWS Secrets Manager console and find the secret -api-keys.

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AWS Machine Learning Blog

APRIL 16, 2024

Managing your Amazon Lex bots using AWS CloudFormation allows you to create templates defining the bot and all the AWS resources it depends on. AWS CloudFormation provides and configures those resources on your behalf, removing the risk of human error when deploying bots to new environments. Resources: # 1.

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Flipboard

JUNE 3, 2025

To meet the feature requirements, the system operation process includes the following steps: Charging data is processed through the EV service before entering the database. The charging history data and pricing data are stored in the EV database. In the following section, we dive deep into these steps and the AWS services used.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Yes, the AWS re:Invent season is upon us and as always, the place to be is Las Vegas! You marked your calendars, you booked your hotel, and you even purchased the airfare. are the sessions dedicated to AWS DeepRacer ! Generative AI is at the heart of the AWS Village this year. And last but not least (and always fun!)

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Flipboard

APRIL 23, 2025

To assist in this effort, AWS provides a range of generative AI security strategies that you can use to create appropriate threat models. For all data stored in Amazon Bedrock, the AWS shared responsibility model applies. The following diagram illustrates how RBAC works with metadata filtering in the vector database.

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AWS Machine Learning Blog

JULY 10, 2024

Today at the AWS New York Summit, we announced a wide range of capabilities for customers to tailor generative AI to their needs and realize the benefits of generative AI faster. Each application can be immediately scaled to thousands of users and is secure and fully managed by AWS, eliminating the need for any operational expertise.

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AWS Machine Learning Blog

OCTOBER 23, 2024

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. Pre-built templates tailored to various use cases are included, significantly enhancing both employee and customer experiences.

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AWS Machine Learning Blog

MAY 30, 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 are already familiar with. The framework for connecting Anthropic Claude 2 and CBRE’s sample database was implemented using LangChain.

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AWS Machine Learning Blog

MARCH 4, 2024

Looking back to 2021, when Anthropic first started building on AWS, no one could have envisioned how transformative the Claude family of models would be. In addition, proprietary data is never exposed to the public internet, never leaves the AWS network, is securely transferred through VPC, and is encrypted in transit and at rest.

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AWS Machine Learning Blog

APRIL 14, 2025

AWS has introduced a multi-agent collaboration capability for Amazon Bedrock Agents , enabling developers to build, deploy, and manage multiple AI agents working together on complex tasks. Hotel booking required for 5 days. It searches its historical database, analyzing patterns from similar user profiles to recommend the destination.

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Flipboard

NOVEMBER 20, 2024

Prerequisites Before proceeding with this tutorial, make sure you have the following in place: AWS account – You should have an AWS account with access to Amazon Bedrock. She speaks at internal and external conferences such AWS re:Invent, Women in Manufacturing West, YouTube webinars, and GHC 23. model in Amazon Bedrock.

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AWS Machine Learning Blog

APRIL 9, 2025

Although Amazon Bedrock agents can self-correct through their reasoning and action ( ReAct ) strategy, repeated tool execution might be acceptable for non-critical tasks but risky for business-critical operations, such as database modifications. Ryan Sachs is a Solutions Architect at AWS, specializing in GenAI application development.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The number of companies launching generative AI applications on AWS is substantial and building quickly, including adidas, Booking.com, Bridgewater Associates, Clariant, Cox Automotive, GoDaddy, and LexisNexis Legal & Professional, to name just a few. Innovative startups like Perplexity AI are going all in on AWS for generative AI.

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AWS Machine Learning Blog

MARCH 14, 2024

Generative AI with AWS The emergence of FMs is creating both opportunities and challenges for organizations looking to use these technologies. You can use AWS PrivateLink with Amazon Bedrock to establish private connectivity between your FMs and your VPC without exposing your traffic to the internet.

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PyImageSearch

MAY 12, 2025

Home Table of Contents Build a Search Engine: Deploy Models and Index Data in AWS OpenSearch Introduction What Will We Do in This Blog? However, we will also provide AWS OpenSearch instructions so you can apply the same setup in the cloud. This is useful for running OpenSearch locally for testing before deploying it on AWS.

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AWS Machine Learning Blog

FEBRUARY 14, 2024

In this post, we discuss how to use the comprehensive capabilities of Amazon Bedrock to perform complex business tasks and improve the customer experience by providing personalization using the data stored in a database like Amazon Redshift. This solution contains two major components. This solution contains two major components.

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AWS Machine Learning Blog

OCTOBER 23, 2024

By automating document ingestion, chunking, and embedding, it eliminates the need to manually set up complex vector databases or custom retrieval systems, significantly reducing development complexity and time. The solution’s scalability quickly accommodates growing data volumes and user queries thanks to AWS serverless offerings.

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Flipboard

MAY 1, 2025

An agent uses a function call to invoke an external tool (like an API or database) to perform specific actions or retrieve information it doesnt possess internally. You ask the agent to Book a 5-day trip to Europe in January and we like warm weather.

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PyImageSearch

MAY 19, 2025

run_opensearch.sh Running OpenSearch Locally A script to start OpenSearch using Docker for local testing before deploying to AWS. Register the Sentence Transformer model in AWS OpenSearch: AWS users must ensure that OpenSearch can access the model before indexing. These can be used for evaluation and comparison.

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AWS Machine Learning Blog

DECEMBER 18, 2024

Training an LLM is a compute-intensive and complex process, which is why Fastweb, as a first step in their AI journey, used AWS generative AI and machine learning (ML) services such as Amazon SageMaker HyperPod. The team opted for fine-tuning on AWS. To further enrich the dataset, Fastweb generated synthetic Italian data using LLMs.

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Flipboard

APRIL 16, 2025

Solution overview The AI-powered asset inventory labeling solution aims to streamline the process of updating inventory databases by automatically extracting relevant information from asset labels through computer vision and generative AI capabilities. The function updates the asset inventory database with the new extracted data.

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AWS Machine Learning Blog

MAY 8, 2023

In a previous post , we discussed MLflow and how it can run on AWS and be integrated with SageMaker—in particular, when tracking training jobs as experiments and deploying a model registered in MLflow to the SageMaker managed infrastructure. To automate the infrastructure deployment, we use the AWS Cloud Development Kit (AWS CDK).

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Flipboard

NOVEMBER 24, 2023

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

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Snorkel AI

JUNE 4, 2025

Seeking to build an AI system that could extract, analyze, and present insights from vast, complex datasets, the company partnered with Snorkel AI , Amazon Web Services (AWS), and Anthropic. Cost-effective AI solutions: AWS’s managed services allow enterprises to optimize costs associated with deploying and maintaining AI applications.

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AWS Machine Learning Blog

AUGUST 7, 2024

It works by first retrieving relevant responses from a database, then using those responses as context to feed the generative model to produce a final output. For example, retrieving responses from its database before generating a response could provide more relevant and coherent responses. Scott Fitzgerald.

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AWS Machine Learning Blog

APRIL 30, 2025

This post explores key insights and lessons learned from AWS customers in Europe, Middle East, and Africa (EMEA) who have successfully navigated this transition, providing a roadmap for others looking to follow suit. Il Sole 24 Ore leveraged its vast internal knowledge with a Retrieval Augmented Generation (RAG) solution powered by AWS.

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AWS Machine Learning Blog

MARCH 7, 2025

Today, Amazon Web Services (AWS) announced the general availability of Amazon Bedrock Knowledge Bases GraphRAG (GraphRAG), a capability in Amazon Bedrock Knowledge Bases that enhances Retrieval-Augmented Generation (RAG) with graph data in Amazon Neptune Analytics. For Knowledge Base details , enter a name and an optional description.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Internally, Amazon Bedrock uses embeddings stored in a vector database to augment user query context at runtime and enable a managed RAG architecture solution. The document embeddings are split into chunks and stored as indexes in a vector database. We use the Amazon letters to shareholders dataset to develop this solution.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Building a production-ready solution in AWS involves a series of trade-offs between resources, time, customer expectation, and business outcome. The AWS Well-Architected Framework helps you understand the benefits and risks of decisions you make while building workloads on AWS.

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Towards AI

JUNE 18, 2024

Many of you asked for an electronic version of our new book, so after working out the kinks, we are finally excited to release the electronic version of “Building LLMs for Production.” We’ve heard many feedback from you guys wanting to have both the e-book and book for different occasions. We listened.

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AWS Machine Learning Blog

NOVEMBER 24, 2023

The platform enables you to create managed agents for complex business tasks without the need for coding, such as booking travel, processing insurance claims, creating ad campaigns, and managing inventory. This solution is available in the AWS Solutions Library. AWS Lambda – AWS Lambda provides serverless compute for processing.

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AWS Machine Learning Blog

JANUARY 31, 2024

In addition to semantic search, you can use embeddings to augment your prompts for more accurate results through Retrieval Augmented Generation (RAG)—but in order to use them, you’ll need to store them in a database with vector capabilities. You can use it via either the Amazon Bedrock REST API or the AWS SDK. Nitin Eusebius is a Sr.

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AWS Machine Learning Blog

FEBRUARY 12, 2025

The key is to choose a solution that can effectively host your database and compute infrastructure. This architecture uses Amazon ECS for hosting the service, Amazon CloudFront as a CDN, AWS WAF as a firewall, and Amazon MemoryDB for providing a semantic cache. Securing your generative AI system is another crucial aspect.

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