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Hi everyone! This is my first video of a series about OutSystems and GenAI. Today I talk about Fine-tuning of AI models and its advantages, compare it with data gathering tools like RAG, and finalize it showcasing one of my latest projects, the Knowledge2JSONL, a converter app that converts sets of documentation, into a proper question / answer format (chat completion) to allow to train models with a specific knowledge. Feel free to give me some feedback and ideas for this project or following videos. Hope you enjoy it! Video chapters: 00:00 - Introduction 04:28 - Neural Network and Weights Summary 07:49 - RAG vs Finetuning 15:47 - AI Foundry Finetuning 19:46 - Knowledge2JSONL App 29:05 - How the app works in Service Studio Some additional resources: A cool explanation of Neural Networks: ChatGPT is made from 100 million of these [The Perceptron] ( • ChatGPT is made from 100 million of t... ) IBM Video to compare Fine-tuning with RAG: RAG vs. Fine Tuning ( • RAG vs. Fine Tuning ) IBM Article of RAG vs. fine-tuning: https://www.ibm.com/think/topics/rag-...