Fundamental’s Large Tabular Model NEXUS is now available on Amazon SageMaker JumpStart | Amazon Web Services
Today, we’re announcing support for Fundamental’s NEXUS model on Amazon SageMaker AI. With this launch, you can deploy a foundation…
Tag: SageMaker
Improve your agent’s tool-calling accuracy with SFT and DPO on Amazon SageMaker AI | Amazon Web Services
AI agents can autonomously handle complex, multi-step tasks, but their effectiveness depends on calling the right tools to retrieve information…
Comprehensive observability for Amazon SageMaker AI LLM inference: From GPU utilization to LLM quality | Amazon Web Services
Deploying large language models (LLMs) at scale on Amazon SageMaker AI Inference makes observability a critical pillar of any production…
Streamline external access to Amazon SageMaker MLflow using a REST API proxy | Amazon Web Services
Machine learning (ML) teams use MLflow to manage their ML lifecycle effectively. Amazon SageMaker MLflow provides comprehensive ML experiment tracking…
Build a custom portal with embedded Amazon SageMaker AI MLflow Apps | Amazon Web Services
As ML teams grow, embedding Amazon SageMaker AI MLflow Apps into a custom portal requires a scalable approach to access…
Announcing OpenAI-compatible API support for Amazon SageMaker AI endpoints | Amazon Web Services
Today, Amazon SageMaker AI introduces OpenAI-compatible API support for real-time inference endpoints. If you use the OpenAI SDK, LangChain, or…
Fine-tune LLM with Databricks Unity Catalog and Amazon SageMaker AI | Amazon Web Services
When you fine-tune large language models (LLMs) with Amazon SageMaker AI while using Databricks Unity Catalog, you might face unique…
Navigating EU AI Act requirements for LLM fine-tuning on Amazon SageMaker AI | Amazon Web Services
The EU AI Act requires organizations fine-tuning large language models (LLMs) to track computational resources measured in floating-point operations (FLOPs)…
Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO on SageMaker AI | Amazon Web Services
Training large language models requires accurate feedback signals, but traditional reinforcement learning (RL) often struggles with reward signal reliability. The…
Streamlining generative AI development with MLflow v3.10 on Amazon SageMaker AI | Amazon Web Services
Today, we’re excited to announce that Amazon SageMaker AI MLflow Apps now support MLflow version 3.10, bringing enhanced capabilities for…