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In today’s rapidly evolving landscape of artificial intelligence (AI), training large language models (LLMs) poses significant challenges. These models often require enormous computational resources and sophisticated infrastructure to handle the vast amounts of data and complex algorithms involved. Without a structured framework, the process can become prohibitively time-consuming, costly, and complex. Enterprises struggle with managing …

Accelerate your generative AI distributed training workloads with the NVIDIA NeMo Framework on Amazon EKS Read More »

Your multi-account strategy is the core of your foundational environment on AWS. Design decisions around your multi-account environment are critical for operating securely at scale. Grouping your workloads strategically into multiple AWS accounts enables you to apply different controls across workloads, track cost and usage, reduce the impact of account limits, and mitigate the complexity …

Governing the ML lifecycle at scale, Part 2: Multi-account foundations Read More »

Here’s how this model came to be.

This post is co-written with MagellanTV and Mission Cloud.  Video dubbing, or content localization, is the process of replacing the original spoken language in a video with another language while synchronizing audio and video. Video dubbing has emerged as a key tool in breaking down linguistic barriers, enhancing viewer engagement, and expanding market reach. However, …

Video auto-dubbing using Amazon Translate, Amazon Bedrock, and Amazon Polly Read More »

This post is co-written with Vlad Lebedev and DJ Charles from Mixbook. Mixbook is an award-winning design platform that gives users unrivaled creative freedom to design and share one-of-a-kind stories, transforming the lives of more than six million people. Today, Mixbook is the #1 rated photo book service in the US with 26 thousand five-star …

How Mixbook used generative AI to offer personalized photo book experiences Read More »

In the diverse toolkit available for deploying cloud infrastructure, Agents for Amazon Bedrock offers a practical and innovative option for teams looking to enhance their infrastructure as code (IaC) processes. Agents for Amazon Bedrock automates the prompt engineering and orchestration of user-requested tasks. After being configured, an agent builds the prompt and augments it with …

Using Agents for Amazon Bedrock to interactively generate infrastructure as code Read More »

Retrieval Augmented Generation (RAG) is a popular paradigm that provides additional knowledge to large language models (LLMs) from an external source of data that wasn’t present in their training corpus. RAG provides additional knowledge to the LLM through its input prompt space and its architecture typically consists of the following components: Indexing: Prepare a corpus …

Improve RAG accuracy with fine-tuned embedding models on Amazon SageMaker Read More »

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 …

How BRIA AI used distributed training in Amazon SageMaker to train latent diffusion foundation models for commercial use Read More »

Amazon SageMaker Studio provides a comprehensive suite of fully managed integrated development environments (IDEs) for machine learning (ML), including JupyterLab, Code Editor (based on Code-OSS), and RStudio. It supports all stages of ML development—from data preparation to deployment, and allows you to launch a preconfigured JupyterLab IDE for efficient coding within seconds. Additionally, its flexible …

Create custom images for geospatial analysis with Amazon SageMaker Distribution in Amazon SageMaker Studio Read More »

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) …

Automating model customization in Amazon Bedrock with AWS Step Functions workflow Read More »