Accelerate your generative AI distributed training workloads with the NVIDIA NeMo Framework on Amazon EKS
In today’s rapidly evolving landscape of artificial intelligence (AI), training large language […]
Read moreCategory: Machine learning
Governing the ML lifecycle at scale, Part 2: Multi-account foundations
Your multi-account strategy is the core of your foundational environment on AWS. […]
Read moreVideo auto-dubbing using Amazon Translate, Amazon Bedrock, and Amazon Polly
This post is co-written with MagellanTV and Mission Cloud. Video dubbing, or […]
Read moreHow Mixbook used generative AI to offer personalized photo book experiences
This post is co-written with Vlad Lebedev and DJ Charles from Mixbook. […]
Read moreUsing Agents for Amazon Bedrock to interactively generate infrastructure as code
In the diverse toolkit available for deploying cloud infrastructure, Agents for Amazon […]
Read moreAutomating model customization in Amazon Bedrock with AWS Step Functions workflow
Large language models have become indispensable in generating intelligent and nuanced responses […]
Read moreCreate custom images for geospatial analysis with Amazon SageMaker Distribution in Amazon SageMaker Studio
Amazon SageMaker Studio provides a comprehensive suite of fully managed integrated development […]
Read moreImprove RAG accuracy with fine-tuned embedding models on Amazon SageMaker
Retrieval Augmented Generation (RAG) is a popular paradigm that provides additional knowledge […]
Read moreHow BRIA AI used distributed training in Amazon SageMaker to train latent diffusion foundation models for commercial use
This post is co-written with Bar Fingerman from BRIA AI. This post […]
Read moreKnowledge Bases for Amazon Bedrock now supports advanced parsing, chunking, and query reformulation giving greater control of accuracy in RAG based applications
Knowledge Bases for Amazon Bedrock is a fully managed service that helps […]
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