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This invention describes a system that classifies sensor data using a machine learning model. This model is trained with data that has been carefully labeled by a separate system, called an "agent computation component." This component queries specialized "agents" (like human experts or other advanced AI) to provide highly confident and timely analyses of the sensor data, which then trains the main classification model.
Why it matters: Filed before large language models could act as adaptable, high-confidence "agents" for data labeling and analysis. The ability to dynamically select and query diverse AI agents based on required confidence and latency is now significantly more powerful and scalable.
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