The Untold Secrets of FFN in Transformers

Описание: Transformers changed the entire world of AI — but there is one component almost everyone ignores: the Feed Forward Neural Network (FFN).
In this video, I break down WHAT the FFN is, WHY it exists in every transformer layer, and HOW it works internally with a full step-by-step example.

We will cover:
• What is the Feed Forward Network (FFN) in Transformers
• Why Transformers need FFN after multi-head attention
• How FFN expands and compresses embeddings
• Role of activation functions ( ReLU)
• Why FFN uses shared weights
• How FFN processes every token in parallel
• Complete numeric example (3 → 6 → 3 dimensions)
• How FFN improves representation learning
• Where FFN fits in the Transformer block (Add & Norm)
• Why FFN is essential for models like GPT, BERT, T5, LLaMA

If you are learning Transformers for the first time, or preparing for ML/NLP interviews, or building your own model — this video will make the FFN concept extremely simple and practical.

Make sure to watch this as part of my Transformer Architecture Series.

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