AWS Machine Learning Blog

Category: Artificial Intelligence

How VistaPrint delivers personalized product recommendations with Amazon Personalize

VistaPrint, a Cimpress business, is the design and marketing partner to millions of small businesses around the world. For more than two decades, VistaPrint has empowered small businesses to quickly and effectively create the marketing products – from promotional materials and signage to print advertising and more – to get the job done, regardless of […]

Automate the process to change image backgrounds using Amazon Bedrock and AWS Step Functions

Many customers, including those in creative advertising, media and entertainment, ecommerce, and fashion, often need to change the background in a large number of images. Typically, this involves manually editing each image with photo software. This can take a lot of effort, especially for large batches of images. However, Amazon Bedrock and AWS Step Functions […]

Efficiently fine-tune the ESM-2 protein language model with Amazon SageMaker

In this post, we demonstrate how to efficiently fine-tune a state-of-the-art protein language model (pLM) to predict protein subcellular localization using Amazon SageMaker. Proteins are the molecular machines of the body, responsible for everything from moving your muscles to responding to infections. Despite this variety, all proteins are made of repeating chains of molecules called […]

Alida gains deeper understanding of customer feedback with Amazon Bedrock

This post is co-written with Sherwin Chu from Alida. Alida helps the world’s biggest brands create highly engaged research communities to gather feedback that fuels better customer experiences and product innovation. Alida’s customers receive tens of thousands of engaged responses for a single survey, therefore the Alida team opted to leverage machine learning (ML) to […]

Unlocking Innovation: AWS and Anthropic push the boundaries of generative AI together

Amazon Bedrock is the best place to build and scale generative AI applications with large language models (LLM) and other foundation models (FMs). It enables customers to leverage a variety of high-performing FMs, such as the Claude family of models by Anthropic, to build custom generative AI applications. Looking back to 2021, when Anthropic first started […]

Knowledge Bases for Amazon Bedrock now supports hybrid search

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With a knowledge base, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data for fully managed Retrieval Augmented Generation (RAG). In a previous post, we described how Knowledge Bases for Amazon Bedrock manages the end-to-end […]

Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer

The rise of artificial intelligence (AI) has created opportunities to improve the customer experience in the contact center space. Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics. Self-service bots integrated with your call center can help […]

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

Amazon Bedrock provides a broad range of models from Amazon and third-party providers, including Anthropic, AI21, Meta, Cohere, and Stability AI, and covers a wide range of use cases, including text and image generation, embedding, chat, high-level agents with reasoning and orchestration, and more. Knowledge Bases for Amazon Bedrock allows you to build performant and […]

Unlock personalized experiences powered by AI using Amazon Personalize and Amazon OpenSearch Service

OpenSearch is a scalable, flexible, and extensible open source software suite for search, analytics, security monitoring, and observability applications, licensed under the Apache 2.0 license. Amazon OpenSearch Service is a fully managed service that makes it straightforward to deploy, scale, and operate OpenSearch in the AWS Cloud. OpenSearch uses a probabilistic ranking framework called BM-25 […]

Automate Amazon SageMaker Pipelines DAG creation

Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. In this post, we present a framework for automating the creation of a directed acyclic graph (DAG) for Amazon SageMaker Pipelines based on simple configuration files. The framework code and examples presented here only cover […]