Fix evaluation bias to unlock better models on Amazon Bedrock

原文摘要 · 中英对照

Property Finder found that 96.8% of their vision-AI evaluation labels were inherited from the incumbent model, hiding its true accuracy. See how they built unbiased ground truth, applied evolutionary prompt optimization, and selected a more accurate, cost-effective model on Amazon Bedrock, cutting cost by 86% across 11 image-quality attributes.

Property Finder 发现其 96.8% 的视觉 AI 评估标签继承自现有模型，掩盖了其真实准确率。了解他们如何构建无偏的基准真值、应用进化式提示优化，并在 Amazon Bedrock 上选择更准确、更具成本效益的模型，在 11 个图像质量属性上将成本降低 86%。