Remove Engineering Remove Generative AI Remove Machine Learning
article thumbnail

Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. Many commercial generative AI solutions available are expensive and require user-based licenses.

article thumbnail

Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

The emergence of generative AI has ushered in a new era of possibilities, enabling the creation of human-like text, images, code, and more. Solution overview For this solution, you deploy a demo application that provides a clean and intuitive UI for interacting with a generative AI model, as illustrated in the following screenshot.

article thumbnail

Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle.

article thumbnail

Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. In the context of Amazon Bedrock , observability and evaluation become even more crucial.

article thumbnail

Supercharge your auto scaling for generative AI inference – Introducing Container Caching in SageMaker Inference

AWS Machine Learning - AI

Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI models for inference. In our tests, we’ve seen substantial improvements in scaling times for generative AI model endpoints across various frameworks.

article thumbnail

Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning - AI

With the QnABot on AWS (QnABot), integrated with Microsoft Azure Entra ID access controls, Principal launched an intelligent self-service solution rooted in generative AI. Generative AI models (for example, Amazon Titan) hosted on Amazon Bedrock were used for query disambiguation and semantic matching for answer lookups and responses.

article thumbnail

Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although these dynamic routing approaches offer powerful capabilities, they require careful consideration of engineering trade-offs, including latency, cost optimization, and system maintenance complexity.