Deploy Amazon SageMaker pipelines using AWS Controllers for Kubernetes

Kubernetes is a popular orchestration platform for managing containers. Its scalability and load-balancing capabilities make it ideal for handling the variable workloads typical of machine learning (ML) applications. DevOps engineers often use Kubernetes to manage and scale ML applications, but before an ML model is available, it must be trained and evaluated and, if the […]

Effectively manage foundation models for generative AI applications with Amazon SageMaker Model Registry

Generative artificial intelligence (AI) foundation models (FMs) are gaining popularity with businesses due to their versatility and potential to address a variety of use cases. The true value of FMs is realized when they are adapted for domain specific data. Managing these models across the business and model lifecycle can introduce complexity. As FMs are […]

Build an ecommerce product recommendation chatbot with Amazon Bedrock Agents

Many ecommerce applications want to provide their users with a human-like chatbot that guides them to choose the best product as a gift for their loved ones or friends. To enhance the customer experience, the chatbot need to engage in a natural, conversational manner to understand the user’s preferences and requirements, such as the recipient’s […]

How Thomson Reuters Labs achieved AI/ML innovation at pace with AWS MLOps services

This post is co-written by Danilo Tommasina and Andrei Voinov from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted information organizations for businesses and professionals. TR provides companies with the intelligence, technology, and human expertise they need to find trusted answers, enabling them to make better decisions more quickly. TR’s customers […]