Using public and private agricultural knowledge graphs to generate agricultural inferences

This invention helps farmers get insights about their fields by combining public and private agricultural data. It identifies public information, converts it into numerical "embeddings," and sends it to the farmer's private system. There, it's combined with the farmer's own data, also converted to embeddings, and processed by machine learning models to generate specific agricultural advice.

Why it matters: The claims specifically mention transformer networks, which have become significantly more powerful and accessible for generating complex inferences from diverse data since 2022. This makes the core machine learning component of the invention much more robust today.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, knowledge graphs, machine learning

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