AWS Machine Learning Blog

Category: AWS Amplify

Embodied AI Chess with Amazon Bedrock

In this post, we demonstrate Embodied AI Chess with Amazon Bedrock, bringing a new dimension to traditional chess through generative AI capabilities. Our setup features a smart chess board that can detect moves in real time, paired with two robotic arms executing those moves. Each arm is controlled by different FMs—base or custom. This physical implementation allows you to observe and experiment with how different generative AI models approach complex gaming strategies in real-world chess matches.

Revolutionize trip planning with Amazon Bedrock and Amazon Location Service

In this post, we show you how to build a generative AI-powered trip-planning service that revolutionizes the way travelers discover and explore destinations. By using advanced AI technology and Amazon Location Service, the trip planner lets users translate inspiration into personalized travel itineraries. This innovative service goes beyond traditional trip planning methods, offering real-time interaction through a chat-based interface and maintaining scalability, reliability, and data security through AWS native services.

Deploy a serverless web application to edit images using Amazon Bedrock

In this post, we explore a sample solution that you can use to deploy an image editing application by using AWS serverless services and generative AI services. We use Amazon Bedrock and an Amazon Titan FM that allow you to edit images by using prompts.

Generative AI-powered American Sign Language avatars

GenASL: Generative AI-powered American Sign Language avatars

In this post, we dive into the architecture and implementation details of GenASL, which uses AWS generative AI capabilities to create human-like ASL avatar videos. GenASL is a solution that translates speech or text into expressive ASL avatar animations, bridging the gap between spoken and written language and sign language.

Enhance your media search experience using Amazon Q Business and Amazon Transcribe

In today’s digital landscape, the demand for audio and video content is skyrocketing. Organizations are increasingly using media to engage with their audiences in innovative ways. From product documentation in video format to podcasts replacing traditional blog posts, content creators are exploring diverse channels to reach a wider audience. The rise of virtual workplaces has […]

Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

Computer vision (CV) is one of the most common applications of machine learning (ML) and deep learning. Use cases range from self-driving cars, content moderation on social media platforms, cancer detection, and automated defect detection. Amazon Rekognition is a fully managed service that can perform CV tasks like object detection, video segment detection, content moderation, […]

Creating an end-to-end application for orchestrating custom deep learning HPO, training, and inference using AWS Step Functions

Amazon SageMaker hyperparameter tuning provides a built-in solution for scalable training and hyperparameter optimization (HPO). However, for some applications (such as those with a preference of different HPO libraries or customized HPO features), we need custom machine learning (ML) solutions that allow retraining and HPO. This post offers a step-by-step guide to build a custom deep […]

Rust detection using machine learning on AWS

Visual inspection of industrial environments is a common requirement across heavy industries, such as transportation, construction, and shipbuilding, and typically requires qualified experts to perform the inspection. Inspection locations can often be remote or in adverse environments that put humans at risk, such as bridges, skyscrapers, and offshore oil rigs. Many of these industries deal […]

Building a medical image search platform on AWS

Improving radiologist efficiency and preventing burnout is a primary goal for healthcare providers. A nationwide study published in Mayo Clinic Proceedings in 2015 showed radiologist burnout percentage at a concerning 61% [1]. In additon, the report concludes that “burnout and satisfaction with work-life balance in US physicians worsened from 2011 to 2014. More than half […]