Скачать или смотреть Supervised Fine Tuning Explained

Supervised Fine-Tuning (SFT) Explained Simply

#SupervisedFineTuning #SFT #GenerativeAI #LargeLanguageModels #LLMTraining #MachineLearning #ArtificialIntelligence #AIExplained #TechTutorial #DeepLearning #FineTuning #VLRTraining #AICoding #DataScience #NeuralNetworks

Have you ever wondered why ChatGPT answers your questions politely instead of just rambling? The secret isn't just "training"—it is a specific process called Supervised Fine-Tuning (SFT).

In this video, I explain how SFT transforms a raw AI model (like a student who memorized a library) into a helpful assistant (like a doctor treating patients). We cover the difference between Pre-training and Fine-tuning, how models learn to follow instructions, and why SFT is crucial for AI safety and structure.

What you will learn:

The difference between a Base Model and an Instruct Model.

The "Medical Student vs. Doctor" analogy to understand AI training.

How SFT stops AI from guessing and makes it follow orders.

Real examples of prompt responses before and after SFT.

The 3 goals of SFT: Structure, Tone, and Safety.

Timestamps
00:00 - Why is ChatGPT polite? 00:21 - Pre-training Analogy: The Medical Student 00:46 - SFT Analogy: The Residency 00:57 - Base Model vs. SFT Model Goals 01:26 - Real Example: Newton's First Law 01:52 - Why SFT is Crucial (Structure, Tone, Safety) 02:10 - Summary: Learning Language vs. Being Helpful

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