Stu Frost’s Post

Very good intro to Causal AI for decision making. Closely aligned with the Geminos vision.

Causal AI makes inferences using causality rather than just correlation, allowing organizations to identify the drivers leading to specific outcomes. EY's Travis Wolf and Carl B. March explain how in this article for Supply Chain Management Review Magazine. #supplychain #AI #causalAI #EY

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For those who are seeking to apply AI in industrial setting especially supply chain and manufacturing operations, this article did a great job articulating the value of Decision Intelligence enabled by LLM + Causal Graph (Thanks for sharing Apostolos Lymperis Travis Wolf Carl B. March). This approach make insights be more actionable, not only tell what happened/is happening/will happen, but also suggest what action should be taken where and when there is most impact ("point of action"), and this kind of intelligence is 1) explainable; 2) no hallucination. To see it in action in machine problem solving in shop floor, check this demo video https://lnkd.in/gEfMuUJu.

💡 Which AI should you choose, for what purpose, and how to implement it concretely? AI in supply chain is multifaceted: forecasting, simulation, alerting, and — most importantly — decision-making. Need to dispatch and plan multiple or complex resources? Then, decision-making AI will undoubtedly be a game-changer by prescribing a directly implementable action plan 🎯 Read this article to unlock the next level of operational performance 👇 https://lnkd.in/e9ypbfzU Nicolas Abgrall I Nicolas Lengaigne I Jean-Christophe Elineau I Jean Paul Chiron I Sophie LAMARQUE I SprintProject

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Developing common approaches and holistic data strategies are crucial for scaling AI beyond short-term wins.

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