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Amazon SageMaker Inference has been a popular tool for deploying advanced machine learning (ML) and generative AI models at scale. As AI applications become increasingly complex, customers want to deploy multiple models in a coordinated group that collectively process inference requests for an application. In addition, with the evolution ofContinue Reading

DeepSeek-R1 is a large language model (LLM) developed by DeepSeek AI that uses reinforcement learning to enhance reasoning capabilities through a multi-stage training process from a DeepSeek-V3-Base foundation. A key distinguishing feature is its reinforcement learning step, which was used to refine the model’s responses beyond the standard pre-training andContinue Reading

Open foundation models (FMs) have become a cornerstone of generative AI innovation, enabling organizations to build and customize AI applications while maintaining control over their costs and deployment strategies. By providing high-quality, openly available models, the AI community fosters rapid iteration, knowledge sharing, and cost-effective solutions that benefit both developersContinue Reading

Open foundation models (FMs) have become a cornerstone of generative AI innovation, enabling organizations to build and customize AI applications while maintaining control over their costs and deployment strategies. By providing high-quality, openly available models, the AI community fosters rapid iteration, knowledge sharing, and cost-effective solutions that benefit both developersContinue Reading

Generative AI has empowered customers with their own information in unprecedented ways, reshaping interactions across various industries by enabling intuitive and personalized experiences. This transformation is significantly enhanced by Retrieval Augmented Generation (RAG), which is a generative AI pattern where the large language model (LLM) being used references a knowledgeContinue Reading

The new efficient multi-adapter inference feature of Amazon SageMaker unlocks exciting possibilities for customers using fine-tuned models. This capability integrates with SageMaker inference components to allow you to deploy and manage hundreds of fine-tuned Low-Rank Adaptation (LoRA) adapters through SageMaker APIs. Multi-adapter inference handles the registration of fine-tuned adapters withContinue Reading

We’re excited to announce the availability of Meta Llama 3.1 8B and 70B inference support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. Meta Llama 3.1 multilingual large language models (LLMs) are a collection of pre-trained and instruction tuned generative models. Trainium and Inferentia, enabled by theContinue Reading