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Amazon Bedrock adds reinforcement fine-tuning simplifying how developers build smarter, more accurate AI models
Organizations face a challenging trade-off when adapting AI models to their specific business needs: settle for generic models that produce average results, or tackle the complexity and expense of advanced model customization. Traditional approaches force a choice...
New serverless customization in Amazon SageMaker AI accelerates model fine-tuning
Today, I’m happy to announce new serverless customization in Amazon SageMaker AI for popular AI models, such as Amazon Nova, DeepSeek, GPT-OSS, Llama, and Qwen. The new customization capability provides an easy-to-use interface for the latest fine-tuning techniques...
Introducing checkpointless and elastic training on Amazon SageMaker HyperPod
Today, we’re announcing two new AI model training features within Amazon SageMaker HyperPod: checkpointless training, an approach that mitigates the need for traditional checkpoint-based recovery by enabling peer-to-peer state recovery, and elastic training, enabling...