Property Finder cuts Amazon Bedrock vision costs 86% after fixing evaluation bias
Overview
Property Finder says it found that 96.8 percent of its evaluation labels came from its incumbent vision model, which made alternatives look worse.
After building expert-annotated ground truth and tuning prompts, it moved to Llama 4 Maverick 17B Instruct on Amazon Bedrock. The AWS Machine Learning Blog post reports Micro F1 rising from 0.55 to 0.81 on the development set and estimated costs falling 86 percent. The pipeline extracts all attributes for an image in a single call.
The figures come from a first-party post co-authored with Property Finder staff, and the post does not describe production results beyond the development set.
Written by AI from the articles below · updated Oct 27, 1:35 PM ET
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The articles in this story. Times are ET.
- AWS Machine Learning BlogOfficialPickProperty Finder fixes evaluation bias to cut Amazon Bedrock vision costs 86 percent
AIProperty Finder found that 96.8 percent of its evaluation labels came from its incumbent vision model, which made alternatives look worse. After building expert-annotated ground truth and tuning prompts, it switched to Llama 4 Maverick 17B Instruct on Amazon Bedrock. The post reports Micro F1 rising from 0.55 to 0.81 on the development set, with estimated costs down 86 percent.
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