Category: Artificial Intelligence

This post is co-written with Bar Fingerman from BRIA AI. This post explains how BRIA AI trained BRIA AI 2.0, a high-resolution (1024×1024) text-to-image diffusion model, on a dataset comprising petabytes of licensed images quickly and economically. Amazon SageMaker training jobs and Amazon SageMaker distributed training libraries took on the undifferentiated heavy lifting associated with infrastructure […]

This post shows you how to extend Amazon SageMaker Distribution with additional dependencies to create a custom container image tailored for geospatial analysis. Although the example in this post focuses on geospatial data science, the methodology presented can be applied to any kind of custom image based on SageMaker Distribution.

Large language models have become indispensable in generating intelligent and nuanced responses across a wide variety of business use cases. However, enterprises often have unique data and use cases that require customizing large language models beyond their out-of-the-box capabilities. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) […]

Amazon Bedrock Knowledge Bases is a fully managed service that helps you implement the entire Retrieval Augmented Generation (RAG) workflow from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows, pushing the boundaries for what you can do in your RAG workflows. However, it’s important to […]

Today, we’re excited to introduce two powerful new features for Amazon Bedrock: Prompt Management and Prompt Flows, in public preview. These features are designed to accelerate the development, testing, and deployment of generative artificial intelligence (AI) applications, enabling developers and business users to create more efficient and effective solutions that are easier to maintain. You […]

See how AWS is democratizing generative AI with innovations like Amazon Q Apps to make AI apps from prompts, Amazon Bedrock upgrades to leverage more data sources, new techniques to curtail hallucinations, and AI skills training.

Responsible AI is a longstanding commitment at Amazon. From the outset, we have prioritized responsible AI innovation by embedding safety, fairness, robustness, security, and privacy into our development processes and educating our employees. We strive to make our customers’ lives better while also establishing and implementing the necessary safeguards to help protect them. Our practical […]

Frontier large language models (LLMs) like Anthropic Claude on Amazon Bedrock are trained on vast amounts of data, allowing Anthropic Claude to understand and generate human-like text. Fine-tuning Anthropic Claude 3 Haiku on proprietary datasets can provide optimal performance on specific domains or tasks. The fine-tuning as a deep level of customization represents a key […]

As generative artificial intelligence (AI) inference becomes increasingly critical for businesses, customers are seeking ways to scale their generative AI operations or integrate generative AI models into existing workflows. Model optimization has emerged as a crucial step, allowing organizations to balance cost-effectiveness and responsiveness, improving productivity. However, price-performance requirements vary widely across use cases. For […]

Today, Amazon SageMaker announced a new inference optimization toolkit that helps you reduce the time it takes to optimize generative artificial intelligence (AI) models from months to hours, to achieve best-in-class performance for your use case. With this new capability, you can choose from a menu of optimization techniques, apply them to your generative AI […]