AWS Machine Learning Blog

Category: Thought Leadership

Easily build semantic image search using Amazon Titan

Digital publishers are continuously looking for ways to streamline and automate their media workflows to generate and publish new content as rapidly as they can, but without foregoing quality. Adding images to capture the essence of text can improve the reading experience. Machine learning techniques can help you discover such images. “A striking image is […]

Operationalize LLM Evaluation at Scale using Amazon SageMaker Clarify and MLOps services

In the last few years Large Language Models (LLMs) have risen to prominence as outstanding tools capable of understanding, generating and manipulating text with unprecedented proficiency. Their potential applications span from conversational agents to content generation and information retrieval, holding the promise of revolutionizing all industries. However, harnessing this potential while ensuring the responsible and […]

How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

This post was co-written with Greg Benson, Chief Scientist; Aaron Kesler, Sr. Product Manager; and Rich Dill, Enterprise Solutions Architect from SnapLogic. Many customers are building generative AI apps on Amazon Bedrock and Amazon CodeWhisperer to create code artifacts based on natural language. This use case highlights how large language models (LLMs) are able to […]

Machine Learning with MATLAB and Amazon SageMaker

This post is written in collaboration with Brad Duncan, Rachel Johnson and Richard Alcock from MathWorks. MATLAB  is a popular programming tool for a wide range of applications, such as data processing, parallel computing, automation, simulation, machine learning, and artificial intelligence. It’s heavily used in many industries such as automotive, aerospace, communication, and manufacturing. In […]

How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

Today, personally identifiable information (PII) is everywhere. PII is in emails, slack messages, videos, PDFs, and so on. It refers to any data or information that can be used to identify a specific individual. PII is sensitive in nature and includes various types of personal data, such as name, contact information, identification numbers, financial information, […]

Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries. However, implementing security, data privacy, and governance controls are still key challenges faced by customers when implementing ML […]


Reinventing a cloud-native federated learning architecture on AWS

In this blog, you will learn to build a cloud-native FL architecture on AWS. By using infrastructure as code (IaC) tools on AWS, you can deploy FL architectures with ease. Also, a cloud-native architecture takes full advantage of a variety of AWS services with proven security and operational excellence, thereby simplifying the development of FL.


A generative AI-powered solution on Amazon SageMaker to help Amazon EU Design and Construction

The Amazon EU Design and Construction (Amazon D&C) team is the engineering team designing and constructing Amazon Warehouses across Europe and the MENA region. The design and deployment processes of projects involve many types of Requests for Information (RFIs) about engineering requirements regarding Amazon and project-specific guidelines. These requests range from simple retrieval of baseline […]

Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets

Multi-modal data is a valuable component of the financial industry, encompassing market, economic, customer, news and social media, and risk data. Financial organizations generate, collect, and use this data to gain insights into financial operations, make better decisions, and improve performance. However, there are challenges associated with multi-modal data due to the complexity and lack […]

Simplify access to internal information using Retrieval Augmented Generation and LangChain Agents

This post takes you through the most common challenges that customers face when searching internal documents, and gives you concrete guidance on how AWS services can be used to create a generative AI conversational bot that makes internal information more useful. Unstructured data accounts for 80% of all the data found within organizations, consisting of […]