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But what is a GPT? Visual intro to Transformers | Chapter 5, Deep Learning

3Blue1Brown · Read on 2026-10-27

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Key points, each with its quote

  • GPT stands for Generative Pre-trained Transformer, with the transformer architecture being the core deep learning model driving modern generative AI. — ✓ “GPT stand for Generative Pre-trained Transformer.” (0:00)
  • A generative language model produces text through autoregression by predicting a probability distribution for the next token, sampling a token, appending it to the context, and repeating. — ✓ “This process here of repeated prediction and sampling” (2:21)
  • Input text is split into tokens and converted into high-dimensional vectors (word embeddings) via an embedding matrix W_E, which in GPT-3 uses 12,288 dimensions across a vocabulary of 50,257 tokens. — ✓ “In GPT-3, they have 12,288 dimensions.” (13:13)
  • Geometric directions in high-dimensional embedding spaces naturally encode semantic meanings and concepts such as gender, tense, or plurality. — ✓ “directions in the space have a kind of semantic meaning.” (13:53)
  • The transformer processes token vectors through alternating attention blocks (enabling communication between tokens) and multilayer perceptrons (processing tokens independently). — ✓ “back and forth between attention blocks and multilayer perceptron blocks” (5:01)
  • The final token vector is mapped to a set of scores (logits) across the vocabulary using an unembedding matrix W_U, which are converted to probabilities using the softmax function. — ✓ “This matrix is called the unembedding matrix” (20:58)
  • The softmax temperature parameter T controls generation entropy, where higher values yield more uniform/creative distributions and T=0 strictly selects the maximum-likelihood token. — ✓ “when T is larger, you give more weight to” (23:36)

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Transcript

The initials GPT stand for Generative Pre-trained Transformer. So that first word is straightforward enough. These are bots that generate new text. Pre-trained refers to how the model went through a process of learning from a massive amount of data, and the prefix insinuates that there's more room t…

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