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3 Questions: Using AI to help Olympic skaters land a quint

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, data, IDSS, Interview, Literature, Mechanical engineering, MIT Sloan School of Management, Research, School of Engineering, Sports and fitness

Olympic figure skating looks effortless. Athletes sail across the ice, then soar into the air, spinning like a top, before landing on a single blade just 4-5 millimeters wide. To help figure skaters land quadruple axels, Salchows, Lutzes, and maybe even the elusive quintuple without looking the least bit stressed, Jerry Lu MFin ’24 developed

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How to Build a Privacy-Preserving Federated Pipeline to Fine-Tune Large Language Models with LoRA Using Flower and PEFT

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In this tutorial, we demonstrate how to federate fine-tuning of a large language model using LoRA without ever centralizing private text data. We simulate multiple organizations as virtual clients and show how each client adapts a shared base model locally while exchanging only lightweight LoRA adapter parameters. By combining Flower’s federated learning simulation engine with

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