Foundation models

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Beyond the basics: A comprehensive foundation model selection framework for generative AI

Amazon Bedrock, Artificial Intelligence, Best Practices, Foundation models, Generative AI, Thought Leadership /

Most organizations evaluating foundation models limit their analysis to three primary dimensions: accuracy, latency, and cost. While these metrics provide a useful starting point, they represent an oversimplification of the complex interplay of factors that determine real-world model performance. Foundation models have revolutionized how enterprises develop generative AI applications, offering unprecedented capabilities in understanding and […]

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Fine-tune OpenAI GPT-OSS models using Amazon SageMaker HyperPod recipes

Amazon SageMaker, Amazon SageMaker AI, Announcements, Artificial Intelligence, Foundation models /

This post is the second part of the GPT-OSS series focusing on model customization with Amazon SageMaker AI. In Part 1, we demonstrated fine-tuning GPT-OSS models using open source Hugging Face libraries with SageMaker training jobs, which supports distributed multi-GPU and multi-node configurations, so you can spin up high-performance clusters on demand. In this post,

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Fine-tune OpenAI GPT-OSS models on Amazon SageMaker AI using Hugging Face libraries

Amazon SageMaker, Amazon SageMaker AI, Announcements, Artificial Intelligence, Foundation models /

Released on August 5, 2025, OpenAI’s GPT-OSS models, gpt-oss-20b and gpt-oss-120b, are now available on AWS through Amazon SageMaker AI and Amazon Bedrock. These pre-trained, text-only Transformer models are built on a Mixture-of-Experts (MoE) architecture that activates only a subset of parameters per token, delivering high reasoning performance while reducing compute costs. They specialize in

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Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization

Amazon Nova, Amazon SageMaker AI, Artificial Intelligence, Foundation models, Intermediate (200) /

At the AWS Summit in New York City, we introduced a comprehensive suite of model customization capabilities for Amazon Nova foundation models. Available as ready-to-use recipes on Amazon SageMaker AI, you can use them to adapt Nova Micro, Nova Lite, and Nova Pro across the model training lifecycle, including pre-training, supervised fine-tuning, and alignment. In this

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Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI

Amazon Nova, Amazon SageMaker, Amazon SageMaker AI, Announcements, Artificial Intelligence, Foundation models /

Evaluating the performance of large language models (LLMs) goes beyond statistical metrics like perplexity or bilingual evaluation understudy (BLEU) scores. For most real-world generative AI scenarios, it’s crucial to understand whether a model is producing better outputs than a baseline or an earlier iteration. This is especially important for applications such as summarization, content generation,

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Implementing on-demand deployment with customized Amazon Nova models on Amazon Bedrock

Amazon Bedrock, Artificial Intelligence, Foundation models /

Amazon Bedrock offers model customization capabilities for customers to tailor versions of foundation models (FMs) to their specific needs through features such as fine-tuning and distillation. Today, we’re announcing the launch of on-demand deployment for customized models ready to be deployed on Amazon Bedrock. On-demand deployment for customized models provides an additional deployment option that

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Accelerate AI development with Amazon Bedrock API keys

Amazon Bedrock, Amazon Machine Learning, Announcements, Artificial Intelligence, Foundation models /

Today, we’re excited to announce a significant improvement to the developer experience of Amazon Bedrock: API keys. API keys provide quick access to the Amazon Bedrock APIs, streamlining the authentication process so that developers can focus on building rather than configuration. CamelAI is an open-source, modular framework for building intelligent multi-agent systems for data generation,

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End-to-End model training and deployment with Amazon SageMaker Unified Studio

Advanced (300), AIML, Amazon SageMaker, Amazon SageMaker Unified Studio, Foundation models, Generative AI, Technical How-to /

Although rapid generative AI advancements are revolutionizing organizational natural language processing tasks, developers and data scientists face significant challenges customizing these large models. These hurdles include managing complex workflows, efficiently preparing large datasets for fine-tuning, implementing sophisticated fine-tuning techniques while optimizing computational resources, consistently tracking model performance, and achieving reliable, scalable deployment.The fragmented nature of

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Driving cost-efficiency and speed in claims data processing with Amazon Nova Micro and Amazon Nova Lite

Amazon Bedrock, Amazon Nova, Artificial Intelligence, Foundation models, Generative AI /

Amazon operations span the globe, touching the lives of millions of customers, employees, and vendors every day. From the vast logistics network to the cutting-edge technology infrastructure, this scale is a testament to the company’s ability to innovate and serve its customers. With this scale comes a responsibility to manage risks and address claims—whether they

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Deploy Qwen models with Amazon Bedrock Custom Model Import

Amazon Bedrock, Announcements, Artificial Intelligence, Foundation models, Generative AI /

We’re excited to announce that Amazon Bedrock Custom Model Import now supports Qwen models. You can now import custom weights for Qwen2, Qwen2_VL, and Qwen2_5_VL architectures, including models like Qwen 2, 2.5 Coder, Qwen 2.5 VL, and QwQ 32B. You can bring your own customized Qwen models into Amazon Bedrock and deploy them in a fully managed, serverless environment—without having to

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