Improving Language Understanding by Generative Pretraining
Understand how the shift from BERT’s bidirectional comprehension to GPT’s decoder-based generation revolutionized modern language models.
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We’ve reached a pivotal moment. BERT showed how an encoder-only model could revolutionize language understanding by reading text in both directions. But BERT was never built to create. Enter GPT, Generative Pretrained Transformer, a decoder-only model that flips the script. Instead of just understanding text, GPT predicts what comes next, turning transformers into storytellers and paving the way for modern generative AI.
What is GPT?
Introduced by OpenAI in the paper Improving Language Understanding by Generative Pre-Training, GPT was designed to harness the transformer decoder for text generation. Unlike BERT, which summarizes sentences, GPT predicts the next word in a sequence, one token at a time.
Think of it as reading a story and trying to guess how it continues. GPT excels at completing text, generating dialogue, and writing creatively because its design is optimized for continuation rather than classification.
OpenAI’s early experiments (GPT-1 trained on BookCorpus) proved this approach could outperform RNNs. Later versions, such as GPT-2, GPT-3, and beyond, ...