What Happens After Attention in Transformers? | Feed-Forward Network (FFN) Explained скачать в хорошем качестве

What Happens After Attention in Transformers? | Feed-Forward Network (FFN) Explained

After self-attention and multi-head attention, how does a transformer actually understand information? In this video, we explain the Feed-Forward Neural Network (FFN) in transformers using simple language, real-world examples, and whiteboard visuals. You will learn: • Why attention alone is not enough • What the Feed-Forward Network does inside a transformer • What non-linearity means and why it is important • How FFN processes each token independently • Where FFN fits in models like GPT This video is part of our Generative AI and Transformer architecture series. If this video helped you, like, share, and subscribe to MyTechNotes for more easy-to-understand AI content.