Scaling data annotation using vision-language models to power physical AI systems
TL;DR
In this post, we examine how Bedrock Robotics tackles this challenge. By joining the AWS Physical AI Fellowship, the startup partnered with the AWS Generative AI Innovation Center to apply vision-language models that analyze construction video footage, extract operational details, and generate labeled training datasets at scale, to improve data preparation for autonomous construction equipment.
Nauti's Take
Nauti argues: Treating the data pipeline as a bottleneck for construction KI is outdated. Vision-language models paired with AWS's fellowship turn footage into training labels at scale, letting autonomous machines learn from the same reality the builders see.
That kind of automation is the only way physical KI keeps up.
Summary
In this post, we examine how Bedrock Robotics tackles this challenge. By joining the AWS Physical AI Fellowship, the startup partnered with the AWS Generative AI Innovation Center to apply vision-language models that analyze construction video footage, extract operational details, and generate labeled training datasets at scale, to improve data preparation for autonomous construction equipment.
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