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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

NOVEMBER 19, 2024

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. Third, we’ll explore the robust infrastructure services from AWS powering AI innovation, featuring Amazon SageMaker , AWS Trainium , and AWS Inferentia under AI/ML, as well as Compute topics.

AWS

AWS ML ML AI

Evaluate large language models for your machine translation tasks on AWS

AWS Machine Learning Blog

JANUARY 7, 2025

The solution offers two TM retrieval modes for users to choose from: vector and document search. When using the Amazon OpenSearch Service adapter (document search), translation unit groupings are parsed and stored into an index dedicated to the uploaded file. This is covered in detail later in the post.

AWS

AWS Python AI AI

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

AWS Machine Learning Blog

NOVEMBER 18, 2024

Between monitoring, analyzing, and documenting architectural findings, a lack of crucial information can leave your organization vulnerable to potential risks and inefficiencies. Prerequisites For this walkthrough, the following are required: An AWS account. AWS Management Console access. A Python 3.12 environment.

AWS

AWS AI AI Machine Learning

Syngenta develops a generative AI assistant to support sales representatives using Amazon Bedrock Agents

Flipboard

DECEMBER 3, 2024

Syngenta and AWS collaborated to develop Cropwise AI , an innovative solution powered by Amazon Bedrock Agents , to accelerate their sales reps’ ability to place Syngenta seed products with growers across North America. The collaboration between Syngenta and AWS showcases the transformative power of LLMs and AI agents.

AWS

AWS AI AI Machine Learning

Build AWS architecture diagrams using Amazon Q CLI and MCP

AWS Machine Learning Blog

JUNE 30, 2025

Creating professional AWS architecture diagrams is a fundamental task for solutions architects, developers, and technical teams. These diagrams serve as essential communication tools for stakeholders, documentation of compliance requirements, and blueprints for implementation teams.

AWS

AWS Database Python Clustering

MLFlow Mastery: A Complete Guide to Experiment Tracking and Model Management

KDnuggets

JUNE 23, 2025

A project contains: Source code : The Python scripts or notebooks for training and evaluation. Example MLproject file: name: my_ml_project conda_env: conda.yaml entry_points: main: parameters: data_path: {type: str, default: "data.csv"} epochs: {type: int, default: 10} command: "python train.py --data_path {data_path} --epochs {epochs}" 3.

Machine Learning

Machine Learning Machine Learning Natural Language Processing Data Science

Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

AWS Machine Learning Blog

JANUARY 7, 2025

To address this need, AWS generative AI best practices framework was launched within AWS Audit Manager , enabling auditing and monitoring of generative AI applications. Figure 1 depicts the systems functionalities and AWS services. Select AWS Generative AI Best Practices Framework for assessment. Choose Create assessment.

AWS

AWS AI AI Database

Introducing SageMaker Core: A new object-oriented Python SDK for Amazon SageMaker

AWS Machine Learning Blog

OCTOBER 15, 2024

We’re excited to announce the release of SageMaker Core , a new Python SDK from Amazon SageMaker designed to offer an object-oriented approach for managing the machine learning (ML) lifecycle. The SageMaker Core SDK comes bundled as part of the SageMaker Python SDK version 2.231.0

Python

Python AWS ML ML

Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning Blog

APRIL 1, 2025

Were excited to announce the open source release of AWS MCP Servers for code assistants a suite of specialized Model Context Protocol (MCP) servers that bring Amazon Web Services (AWS) best practices directly to your development workflow. This post is the first in a series covering AWS MCP Servers.

AWS

AWS AI AI Python

Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning Blog

NOVEMBER 7, 2024

Access to car manuals and technical documentation helps the agent provide additional context for curated guidance, enhancing the quality of customer interactions. The workflow includes the following steps: Documents (owner manuals) are uploaded to an Amazon Simple Storage Service (Amazon S3) bucket.

AWS

AWS Python AI Database

Automate invoice processing with Streamlit and Amazon Bedrock

AWS Machine Learning Blog

NOVEMBER 14, 2024

Streamlit is an open source framework for data scientists to efficiently create interactive web-based data applications in pure Python. 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.

AWS

AWS Python AI AI

Multilingual content processing using Amazon Bedrock and Amazon A2I

AWS Machine Learning Blog

NOVEMBER 13, 2024

The market size for multilingual content extraction and the gathering of relevant insights from unstructured documents (such as images, forms, and receipts) for information processing is rapidly increasing. These languages might not be supported out of the box by existing document extraction software.

AWS

AWS Machine Learning ML Machine Learning

HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

AWS Machine Learning Blog

JANUARY 15, 2025

Powered by generative AI services on AWS and large language models (LLMs) multi-modal capabilities, HCLTechs AutoWise Companion provides a seamless and impactful experience. This personalized document helps the customer gain a deeper understanding of the vehicle and supports their decision-making process.

AWS

AWS SQL AI AI

Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 1: ModelTrainer

AWS Machine Learning Blog

DECEMBER 12, 2024

Amazon SageMaker has redesigned its Python SDK to provide a unified object-oriented interface that makes it straightforward to interact with SageMaker services. The higher-level abstracted layer is designed for data scientists with limited AWS expertise, offering a simplified interface that hides complex infrastructure details.

ML

ML ML Python AWS

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning Blog

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.

AWS

AWS AI AI Python

Serving LLMs using vLLM and Amazon EC2 instances with AWS AI chips

AWS Machine Learning Blog

NOVEMBER 26, 2024

Using vLLM on AWS Trainium and Inferentia makes it possible to host LLMs for high performance inference and scalability. Deploy vLLM on AWS Trainium and Inferentia EC2 instances In these sections, you will be guided through using vLLM on an AWS Inferentia EC2 instance to deploy Meta’s newest Llama 3.2 You will use inf2.xlarge

AWS

AWS AI AI Artificial Intelligence

Create a generative AI assistant with Slack and Amazon Bedrock

Flipboard

NOVEMBER 27, 2024

In this post, we show you how to integrate the popular Slack messaging service with AWS generative AI services to build a natural language assistant where business users can ask questions of an unstructured dataset. In this example, we ingest the documentation of the Amazon Well-Architected Framework into the knowledge base.

AWS

AWS AI AI Database

Simplify multimodal generative AI with Amazon Bedrock Data Automation

AWS Machine Learning Blog

DECEMBER 17, 2024

This new capability from Amazon Bedrock offers a unified experience for developers of all skillsets to easily automate the extraction, transformation, and generation of relevant insights from documents, images, audio, and videos to build generative AI powered applications.

AWS

AWS AI AI Python

Fine-tune and host SDXL models cost-effectively with AWS Inferentia2

AWS Machine Learning Blog

FEBRUARY 6, 2025

We show how to then prepare the fine-tuned model to run on AWS Inferentia2 powered Amazon EC2 Inf2 instances , unlocking superior price performance for your inference workloads. After the model is fine-tuned, you can compile and host the fine-tuned SDXL on Inf2 instances using the AWS Neuron SDK. An Amazon Web Services (AWS) account.

AWS

AWS Machine Learning Machine Learning Deep Learning

Unlock organizational wisdom using voice-driven knowledge capture with Amazon Transcribe and Amazon Bedrock

AWS Machine Learning Blog

OCTOBER 30, 2024

Formalizing and documenting this invaluable resource can help organizations maintain institutional memory, drive innovation, enhance decision-making processes, and accelerate onboarding for new employees. However, effectively capturing and documenting this knowledge presents significant challenges.

AWS

AWS AI AI ML

Run small language models cost-efficiently with AWS Graviton and Amazon SageMaker AI

Flipboard

JUNE 5, 2025

AWS has always provided customers with choice. In terms of hardware choice, in addition to NVIDIA GPUs and AWS custom AI chips, CPU-based instances represent (thanks to the latest innovations in CPU hardware) an additional choice for customers who want to run generative AI inference, like hosting small language models and asynchronous agents.

AWS

AWS AI AI ML

Automate document translation and standardization with Amazon Bedrock and Amazon Translate

AWS Machine Learning Blog

MAY 1, 2025

Maintaining consistency and alignment across these global operations can be difficult, especially when it comes to updating and sharing business documents and processes. In this post, we show how you can automate language localization through translating documents using Amazon Web Services (AWS).

AWS

AWS AI AI Machine Learning

John Snow Labs Medical LLMs are now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

NOVEMBER 25, 2024

The model is deployed in an AWS secure environment and under your virtual private cloud (VPC) controls, helping provide data security. Discover the Medical LLM – Small model in SageMaker JumpStart You can access the FMs through SageMaker JumpStart in the SageMaker Studio UI and the SageMaker Python SDK.

AWS

AWS ML ML Machine Learning

Amazon Bedrock Prompt Management is now available in GA

AWS Machine Learning Blog

NOVEMBER 7, 2024

For this example, we enter the following: You are an expert financial analyst with years of experience in summarizing complex financial documents. For this post, we use the following prompt: Summarize the following financial document for {{company_name}} with ticker symbol {{ticker_symbol}}: Please provide a brief summary that includes 1.

AWS

AWS ML ML AI

Optimize RAG in production environments using Amazon SageMaker JumpStart and Amazon OpenSearch Service

Flipboard

JULY 2, 2025

For businesses, RAG offers a powerful way to use internal knowledge by connecting company documentation to a generative AI model. When an employee asks a question, the RAG system retrieves relevant information from the company’s internal documents and uses this context to generate an accurate, company-specific response.

AWS

AWS Clustering K-nearest Neighbors Algorithm

Transforming credit decisions using generative AI with Rich Data Co and AWS

AWS Machine Learning Blog

FEBRUARY 10, 2025

It aims to boost team efficiency by answering complex technical queries across the machine learning operations (MLOps) lifecycle, drawing from a comprehensive knowledge base that includes environment documentation, AI and data science expertise, and Python code generation. Its also adept at troubleshooting coding errors.

AWS

AWS Data Science AI AI

Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 2: ModelBuilder

AWS Machine Learning Blog

DECEMBER 12, 2024

In Part 1 of this series, we introduced the newly launched ModelTrainer class on the Amazon SageMaker Python SDK and its benefits, and showed you how to fine-tune a Meta Llama 3.1 Shweta Singh is a Senior Product Manager in the Amazon SageMaker Machine Learning (ML) platform team at AWS, leading SageMaker Python SDK.

ML

ML ML Python AWS

Empower your generative AI application with a comprehensive custom observability solution

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

AWS

AWS AI AI Data Scientist

Reduce conversational AI response time through inference at the edge with AWS Local Zones

AWS Machine Learning Blog

MARCH 3, 2025

Hybrid architecture with AWS Local Zones To minimize the impact of network latency on TTFT for users regardless of their locations, a hybrid architecture can be implemented by extending AWS services from commercial Regions to edge locations closer to end users. Next, create a subnet inside each Local Zone. Amazon Linux 2).

AWS

AWS AI AI Deep Learning

AWS Machine Learning: A Beginner’s Guide

How to Learn Machine Learning

DECEMBER 24, 2024

If you’re diving into the world of machine learning, AWS Machine Learning provides a robust and accessible platform to turn your data science dreams into reality. Whether you’re a solo developer or part of a large enterprise, AWS provides scalable solutions that grow with your needs. Hey dear reader!

Machine Learning

Machine Learning Machine Learning AWS ML

Generate and evaluate images in Amazon Bedrock with Amazon Titan Image Generator G1 v2 and Anthropic Claude 3.5 Sonnet

AWS Machine Learning Blog

NOVEMBER 18, 2024

Solution overview This solution is running in AWS Region us-east-1. It exposes an API endpoint through Amazon API Gateway that proxies the initial prompt request to a Python-based AWS Lambda function, which calls Amazon Bedrock twice. In this post, we will review the console, the terminal, and AWS CLI. Anthropic Claude 3.5

AWS

AWS Python AI AI

NeMo Retriever Llama 3.2 text embedding and reranking NVIDIA NIM microservices now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

MARCH 18, 2025

With this launch, you can now deploy NVIDIAs optimized reranking and embedding models to build, experiment, and responsibly scale your generative AI ideas on AWS. As part of NVIDIA AI Enterprise available in AWS Marketplace , NIM is a set of user-friendly microservices designed to streamline and accelerate the deployment of generative AI.

AWS

AWS AI AI Computer Science

Multi-tenancy in RAG applications in a single Amazon Bedrock knowledge base with metadata filtering

AWS Machine Learning Blog

APRIL 7, 2025

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies and AWS. For example, imagine a consulting firm that manages documentation for multiple healthcare providerseach customers sensitive patient records and operational documents must remain strictly separated.

Database

Database AWS Natural Language Processing AI

Create a document lake using large-scale text extraction from documents with Amazon Textract

AWS Machine Learning Blog

JANUARY 8, 2024

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). In this post, we focus on processing a large collection of documents into raw text files and storing them in Amazon S3.

AWS

AWS Python ML ML

Introducing Stable Diffusion 3.5 Large in Amazon SageMaker JumpStart

AWS Machine Learning Blog

NOVEMBER 14, 2024

This new cutting-edge image generation model, which was trained on Amazon SageMaker HyperPod , empowers AWS customers to generate high-quality images from text descriptions with unprecedented ease, flexibility, and creative potential. Large model is available today in the following AWS Regions: US East (N. By adding Stable Diffusion 3.5

AWS

AWS ML ML Machine Learning

Dynamic metadata filtering for Amazon Bedrock Knowledge Bases with LangChain

Flipboard

MARCH 4, 2025

Amazon Bedrock Knowledge Bases has a metadata filtering capability that allows you to refine search results based on specific attributes of the documents, improving retrieval accuracy and the relevance of responses. Improving document retrieval results helps personalize the responses generated for each user.

AWS

AWS Data Science Deep Learning Deep Learning

Build a scalable AI assistant to help refugees using AWS

AWS Machine Learning Blog

JUNE 3, 2025

This post details our technical implementation using AWS services to create a scalable, multilingual AI assistant system that provides automated assistance while maintaining data security and GDPR compliance. Amazon Titan Embeddings also integrates smoothly with AWS, simplifying tasks like indexing, search, and retrieval.

AWS

AWS AI AI Machine Learning

Implement smart document search index with Amazon Textract and Amazon OpenSearch

AWS Machine Learning Blog

SEPTEMBER 8, 2023

For modern companies that deal with enormous volumes of documents such as contracts, invoices, resumes, and reports, efficiently processing and retrieving pertinent data is critical to maintaining a competitive edge. What if there was a way to process documents intelligently and make them searchable in with high accuracy?

AWS

AWS Clustering ML ML

Integrate foundation models into your code with Amazon Bedrock

AWS Machine Learning Blog

NOVEMBER 6, 2024

For this post, we run the code in a Jupyter notebook within VS Code and use Python. Prerequisites Before you dive into the integration process, make sure you have the following prerequisites in place: AWS account – You’ll need an AWS account to access and use Amazon Bedrock. We walk through a Python example in this post.

AWS

AWS Python Machine Learning Machine Learning

Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

AWS Machine Learning Blog

MARCH 19, 2025

At Amazon Web Services (AWS), we recognize that many of our customers rely on the familiar Microsoft Office suite of applications, including Word, Excel, and Outlook, as the backbone of their daily workflows. Using AWS, organizations can host and serve Office Add-ins for users worldwide with minimal infrastructure overhead.

AWS

AWS AI AI Cloud Computing

Enhance productivity with Amazon Bedrock Agents and Powertools for AWS Lambda

Flipboard

JANUARY 27, 2025

Introducing Amazon Bedrock Agents and Powertools for AWS Lambda To address these challenges, we can leverage two powerful tools that work seamlessly together: Amazon Bedrock Agents utilize functional calling to invoke AWS Lambda functions with embedded business logic. User: Does AWS have any recent FedRAMP compliance documents?

AWS

AWS Python Artificial Intelligence Artificial Intelligence

Minimize generative AI hallucinations with Amazon Bedrock Automated Reasoning checks

Flipboard

APRIL 1, 2025

To improve factual accuracy of large language model (LLM) responses, AWS announced Amazon Bedrock Automated Reasoning checks (in gated preview) at AWS re:Invent 2024. For example, AWS customers have direct access to automated reasoning-based features such as IAM Access Analyzer , S3 Block Public Access , or VPC Reachability Analyzer.

AWS

AWS AI AI Computer Science

Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

AWS Machine Learning Blog

APRIL 11, 2024

Organizations across industries want to categorize and extract insights from high volumes of documents of different formats. Manually processing these documents to classify and extract information remains expensive, error prone, and difficult to scale. Categorizing documents is an important first step in IDP systems.

AWS

AWS Database Algorithm ML

Faster distributed graph neural network training with GraphStorm v0.4

AWS Machine Learning Blog

FEBRUARY 11, 2025

Today, AWS AI released GraphStorm v0.4. Prerequisites To run this example, you will need an AWS account, an Amazon SageMaker Studio domain, and the necessary permissions to run BYOC SageMaker jobs. Using SageMaker Pipelines to train models provides several benefits, like reduced costs, auditability, and lineage tracking. million edges.

AWS

AWS Python ML ML

Your guide to generative AI and ML at AWS re:Invent 2024

Evaluate large language models for your machine translation tasks on AWS

Trending Sources

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

Syngenta develops a generative AI assistant to support sales representatives using Amazon Bedrock Agents

Build AWS architecture diagrams using Amazon Q CLI and MCP

MLFlow Mastery: A Complete Guide to Experiment Tracking and Model Management

Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

Introducing SageMaker Core: A new object-oriented Python SDK for Amazon SageMaker

Introducing AWS MCP Servers for code assistants (Part 1)

Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

Automate invoice processing with Streamlit and Amazon Bedrock

Multilingual content processing using Amazon Bedrock and Amazon A2I

HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 1: ModelTrainer

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

Serving LLMs using vLLM and Amazon EC2 instances with AWS AI chips

Create a generative AI assistant with Slack and Amazon Bedrock

Simplify multimodal generative AI with Amazon Bedrock Data Automation

Fine-tune and host SDXL models cost-effectively with AWS Inferentia2

Unlock organizational wisdom using voice-driven knowledge capture with Amazon Transcribe and Amazon Bedrock

Run small language models cost-efficiently with AWS Graviton and Amazon SageMaker AI

Automate document translation and standardization with Amazon Bedrock and Amazon Translate

John Snow Labs Medical LLMs are now available in Amazon SageMaker JumpStart

Amazon Bedrock Prompt Management is now available in GA

Optimize RAG in production environments using Amazon SageMaker JumpStart and Amazon OpenSearch Service

Transforming credit decisions using generative AI with Rich Data Co and AWS

Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 2: ModelBuilder

Empower your generative AI application with a comprehensive custom observability solution

Reduce conversational AI response time through inference at the edge with AWS Local Zones

AWS Machine Learning: A Beginner’s Guide

Generate and evaluate images in Amazon Bedrock with Amazon Titan Image Generator G1 v2 and Anthropic Claude 3.5 Sonnet

NeMo Retriever Llama 3.2 text embedding and reranking NVIDIA NIM microservices now available in Amazon SageMaker JumpStart

Multi-tenancy in RAG applications in a single Amazon Bedrock knowledge base with metadata filtering

Create a document lake using large-scale text extraction from documents with Amazon Textract

Introducing Stable Diffusion 3.5 Large in Amazon SageMaker JumpStart

Dynamic metadata filtering for Amazon Bedrock Knowledge Bases with LangChain

Build a scalable AI assistant to help refugees using AWS

Implement smart document search index with Amazon Textract and Amazon OpenSearch

Integrate foundation models into your code with Amazon Bedrock

Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

Enhance productivity with Amazon Bedrock Agents and Powertools for AWS Lambda

Minimize generative AI hallucinations with Amazon Bedrock Automated Reasoning checks

Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

Faster distributed graph neural network training with GraphStorm v0.4

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