Ever wondered how Large Language Models (LLMs) like GPT actually work under the hood?

I created this visual guide to demystify the Transformer Architecture, the foundational design behind most modern language models.

🧠 At a high level:

• The Encoder processes input text and builds a deep semantic understanding.
• The Decoder takes this understanding to generate new language.
• Attention mechanisms decide “which tokens matter most” when making predictions.
• Multi-Head Attention allows the model to learn patterns like object and spatial relationships (e.g., “cat: brown” vs. “cat: sat outside”).

💡 Fun fact: Some models have over 100 attention heads and 64+ layers, refining token embeddings with every guess.

🔁 This process repeats every single time a new token is generated, until the model completes its output.

Created as part of my AI learning journey — hope it helps others make sense of this incredible innovation.

👇 Let me know if you’d like a printable version or want to chat about how this architecture powers everything from translation to creative writing.

#AI #MachineLearning #Transformers #LLM #DeepLearning #NLP #AIforEveryone #LearningTogether #RachelLearnsAI