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This invention describes a computer system that helps understand and predict product demand in supply chains. You ask it a question in plain language, like 'What's the demand for oranges in Florida next month given the hurricane season?' The system then figures out what factors (like weather or disruptive events) might affect that demand, builds a map of how these factors are connected and influence demand, and then explains its prediction for future demand based on that map. The core idea is to use natural language to ask complex questions and get an understandable explanation for the forecast.
Why it matters: Filed before the widespread adoption and advanced capabilities of large language models (LLMs), which can now significantly enhance the natural language processing, context identification, and knowledge graph generation aspects described in the claims. The explainable AI component has also seen considerable development since 2021.
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