Category: Artificial Intelligence

In this post, we demonstrate how to fine-tune Meta’s latest Llama 3.2 text generation models, Llama 3.2 1B and 3B, using Amazon SageMaker JumpStart for domain-specific applications. By using the pre-built solutions available in SageMaker JumpStart and the customizable Meta Llama 3.2 models, you can unlock the models’ enhanced reasoning, code generation, and instruction-following capabilities to tailor them for your unique use cases.

Microsoft Teams is an enterprise collaboration tool that allows you to build a unified workspace for real-time collaboration and communication, meetings, and file and application sharing. You can exchange and store valuable organizational knowledge within Microsoft Teams. Microsoft Teams data is often siloed across different teams, channels, and chats, making it difficult to get a […]

Today we are announcing the general availability of Amazon Bedrock Prompt Management, with new features that provide enhanced options for configuring your prompts and enabling seamless integration for invoking them in your generative AI applications.

This post is cowritten with Mones Raslan, Ravi Sharma and Adele Gouttes from Zalando. Zalando SE is one of Europe’s largest ecommerce fashion retailers with around 50 million active customers. Zalando faces the challenge of regular (weekly or daily) discount steering for more than 1 million products, also referred to as markdown pricing. Markdown pricing is […]

To stay competitive, media, advertising, and entertainment enterprises need to stay abreast of recent dramatic technological developments. Generative AI has emerged as a game-changer, offering unprecedented opportunities for creative professionals to push boundaries and unlock new realms of possibility. At the forefront of this revolution is Stability AI’s  family of cutting-edge text-to-image AI models. These […]

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. In the first part of the series, we showed how AI administrators can build a […]

Generative AI has transformed customer support, offering businesses the ability to respond faster, more accurately, and with greater personalization. AI agents, powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses. In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data […]

In this post, we share how Hearst, one of the nation’s largest global, diversified information, services, and media companies, overcame these challenges by creating a self-service generative AI conversational assistant for business units seeking guidance from their CCoE.

The rise of large language models (LLMs) and foundation models (FMs) has revolutionized the field of natural language processing (NLP) and artificial intelligence (AI). These powerful models, trained on vast amounts of data, can generate human-like text, answer questions, and even engage in creative writing tasks. However, training and deploying such models from scratch is […]

AWS provides a powerful set of tools and services that simplify the process of building and deploying generative AI applications, even for those with limited experience in frontend and backend development. In this post, we explore a practical solution that uses Streamlit, a Python library for building interactive data applications, and AWS services like Amazon Elastic Container Service (Amazon ECS), Amazon Cognito, and the AWS Cloud Development Kit (AWS CDK) to create a user-friendly generative AI application with authentication and deployment.