{
  "id": 7588024,
  "title": "Build an AI-powered product tagging system with Amazon SageMaker serverless model customization",
  "url": "https://urgent.news/2026/09/15/build-an-ai-powered-product-tagging-system-with-amazon-sagemaker",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-15T16:11:36.000Z",
  "source": {
    "name": "AWS Machine Learning",
    "slug": "aws-machine-learning",
    "url": "https://aws.amazon.com/blogs/machine-learning/build-an-ai-powered-product-tagging-system-with-amazon-sagemaker-serverless-model-customization/"
  },
  "original_language": "en",
  "account": null,
  "summary": "Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) on Amazon SageMaker serverless model customization, then deploy it for asynchronous inference to build a cost-efficient product tagging system.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}