Lecture 11

Supply Chain Segmentation for Manufacturers

When it comes to supply chains, one size rarely fits all. Different products have different characteristics, lifecycles, and customers that can’t easily be shoehorned into a single planning and scheduling methodology. Yet, for generations that’s exactly how supply chains were managed—until multiproduct retailers realized that a more customized approach improved their bottom line.

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How Supply Chain Benefit from using Generative AIGenAI creates new content, such as numerical data, images, text, audio or video, based on data on which it has been trained. Recent advances make it simpler to use and realize value from, but the technology isn’t new. Already around 40% of supply chain organizations are investing in GenAI, focusing on knowledge management applications.
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Data Interpreter: An LLM Agent For Data Science

Large Language Model (LLM)-based agents have demonstrated remarkable effectiveness. However, their performance can be compromised in data science scenarios that require real-time data adjustment, expertise in optimization due to complex dependencies among various tasks, and the ability to identify logical errors for precise reasoning. In this study, we introduce the Data Interpreter, a solution designed to solve with code that emphasizes three pivotal techniques to augment problem-solving in data science: 1) dynamic planning with hierarchical graph structures for real-time data adaptability;2) tool integration dynamically to enhance code proficiency during execution, enriching the requisite expertise;3) logical inconsistency identification in feedback, and efficiency enhancement through experience recording. We evaluate the Data Interpreter on various data science and real-world tasks. Compared to open-source baselines, it demonstrated superior performance, exhibiting significant improvements in machine learning tasks, increasing from 0.86 to 0.95. Additionally, it showed a 26% increase in the MATH dataset and a remarkable 112% improvement in open-ended tasks.
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What should Data Science Education Do With LLMs:

Generative AI has taken the world by storm. Its massive potential has captured the attention of business leaders across industries, with 95% of executives agreeing it will be transformative for their company. And 100% anticipating workforceThe implications for supply chain leaders? There are countless opportunities to apply generative AI across end-to-end supply chain networks. Performance gains are waiting to be tapped in everything from sourcing and planning, through manufacturing and fulfilment, to aftersales and service changes as a result
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ChatGPT Statistics And Facts You Need to Know in 2024Over the last months, ChatGPT has broken several records. For instance, five days after its release, the chatbot crossed the million-user mark, and within two months, it skyrocketed to 100 million active users, securing its position as the second fastest-growing consumer app in history.And there is more: in less than a year, the platform hit 100 million weekly users, with this figure continuing to climb. The latest ChatGPT statistics reveal impressive growth, user familiarity, and session statistics, providing insights into its performance and impact. ChatGPT's social media traffic has also been significant, with substantial engagement from platforms like YouTube, X (formerly Twitter), LinkedIn, and Facebook.

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