AI (Artificial Intelligence)

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

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

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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Amazon MGM Studios turns to AI to cut costs and speed up film and TV production

Amazon MGM Studios is rolling out new artificial intelligence tools to streamline filmmaking and television production. Led by veteran executive Albert Cheng, the initiative aims to reduce costs, accelerate workflows, and expand creative possibilities while keeping human creators at the centre of the process.

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Human-in-the-loop approach for AI data quality: a practical guide

If you’ve ever watched model performance dip after a “simple” dataset refresh, you already know the uncomfortable truth: data quality doesn’t fail loudly—it fails gradually. A human-in-the-loop approach for AI data quality is how mature teams keep that drift under control while still moving fast. This isn’t about adding people everywhere. It’s about placing humans

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Designing Effective Multi-Agent Architectures

Papers on agentic and multi-agent systems (MAS) skyrocketed from 820 in 2024 to over 2,500 in 2025. This surge suggests that MAS are now a primary focus for the world’s top research labs and universities. Yet there is a disconnect: While research is booming, these systems still frequently fail when they hit production. Most teams

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