Interactive AI Diagram
What is a Transformer ?
Neural network architecture using self-attention to process sequences in parallel
Input Text
Embeddings
Self-Attention
Weighs importance
of each word
Feed Forward
Neural network
processing
Output Text
✓ Simple Explanation
Transformer reads entire sentence at once, figures out which
words are most important to each other, then generates output
—like reading a whole page instead of word-by-word.
⚡ Advanced Details
Uses multi-head self-attention mechanism with O(n²) complexity,
positional encodings, and residual connections. Enables parallel
processing unlike RNNs—foundation for GPT, BERT, and T5.
This diagram illustrates the back-and-forth interaction between a user and an AI model like ChatGPT, where the user provides instructions and receives an output.