What are Parameters | The Real Meaning Behind Model Sizes | AI Fundamentals Decoded | MIK
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What are Parameters | The Real Meaning Behind Model Sizes | AI Fundamentals Decoded | MIK
5 368 просмотров · 2 недели назад
codestorywithMIK
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5 368 просмотров · 2 недели назад
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Hi Everyone, welcome to the 10th video of our brand new Playlist: "AI Fundamentals Decoded" by codestorywithMIK.
In our previous videos, we explored the Context Window in LLMs.
Whenever we look at open-source AI models or download one from Hugging Face, we constantly see tags like "7B", "8B", or "70B". But what does that "B" actually mean? Does 7 billion parameters mean the model memorized 7 billion facts? In this video, we break down what parameters, weights, and biases actually are using a simple 2-input neural network example and the intuitive "Billions of Tiny Dials" analogy!
Video Title : What Does 7B or 70B Actually Mean? | What Are Parameters? | AI Fundamentals Decoded | codestorywithMIK
Topic : What Are Model Parameters, Weights, Biases & Model Sizes
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Video Summary :
In this episode, we decode the mystery of parameters in artificial intelligence. We show how an AI model learns via iterative adjustment (predict ➔ compare error ➔ adjust ➔ repeat). Through an easy math walkthrough (inputs × weights + bias), we see what parameters mathematically look like, why models have billions of them, and picture them as fine-tuning dials. We also dispel the myth that parameters equal stored facts and explain why a larger model isn't automatically better for every real-world hardware setup.
✨ Timelines✨
00:10 Recap of Attention
00:25 7b, 70b models
01:52 Parameters
02:38 Training
05:47 What is LLM Adjusted ?
07:45 Neural Network
11:18 Simplest Analogy
12:44 Things to know
15:37 Ending Notes
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