Inside ChatGPT: Decoder-Only Transformer Explained

In this video, we break down the forward pass of a decoder only Transformer the architecture behind the GPT family. What actually happens when you type a prompt We walk through it step by step Tokenization Token embeddings and positional embeddings Masked multi head self attention Residual connections and layer normalization Feed forward neural networks Softmax and next token prediction We clarify the difference between encoder only transformers like BERT decoder only transformers like GPT and encoder decoder architectures and focus entirely on how a decoder only model generates text in an autoregressive way. From query key and value matrices To contextual representations To why masking prevents the model from cheating This is a clean intuitive walkthrough of how a dense Transformer actually produces the next token. If you have ever wondered what is happening inside GPT at inference time this is the mental model you need. #Transformers #GPT #DeepLearning #MachineLearning #NeuralNetworks #SelfAttention #LargeLanguageModels #AIExplained #ArtificialIntelligence #LLM