Improve the performance of your Generative AI applications with Prompt Optimization on Amazon Bedrock

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Exploring the benefits of artificial intelligence while maintaining digital sovereignty

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From accelerating research and enhancing customer experiences to optimizing business processes, improving patient outcomes, and enriching public services, the transformative potential of AI is being realized across sectors... Many organizations, including those in the public sector and regulated industries, are investing in generative AI applications powered by large language models (LLMs) and ot...

Search enterprise data assets using LLMs backed by knowledge graphs

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In this solution, we integrate large language models (LLMs) hosted on Amazon Bedrock backed by a knowledge base that is derived from a knowledge graph built on Amazon Neptune to create a powerful search paradigm that enables natural language-based questions to integrate search across documents stored in Amazon Simple Storage Service (Amazon S3), data lake tables hosted on the AWS Glue Data Catalo...

Embodied AI Chess with Amazon Bedrock

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Generative AI continues to transform numerous industries and activities, with one such application being the enhancement of chess, a traditional human game, with sophisticated AI and large language models (LLMs)... Using the Custom Model Import feature in Amazon Bedrock, you can now create engaging matches between foundation models (FMs) fine-tuned for chess gameplay, combining classical strategy ...

Amazon FSx for Lustre increases throughput to GPU instances by up to 12x

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EFA is a network interface for Amazon EC2 instances that makes it possible to run applications requiring high levels of inter-node communications at scale... As datasets grow and new technologies emerge, you can adopt increasingly powerful GPU and HPC instances such as Amazon EC2 P5, Trn1, and Hpc7a... Until now, when accessing FSx for Lustre file systems, the use of traditional TCP networking li...

Efficiently train models with large sequence lengths using Amazon SageMaker model parallel

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Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters and larger input sequence length... Longer sequence lengths and the sheer number of trainable parameters demand innovative approaches to model development and deployment... To maximize perf...

Getting started with Amazon Bedrock Agents custom orchestrator

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For greater orchestration control, Amazon Bedrock Agents has launched the custom orchestrator feature, which users can use to fine-tune agent behavior and manage tool interactions at each workflow step... This customization allows organizations to tailor agent functionality to their specific operational needs, improving precision, adaptability, and efficiency... In this post, we explore how cust...