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Evolution of Language Models

August 23, 2023
  • Rule-based: Depended on manually crafted rules for language analysis. Limited capabilities.
  • Statistical: Applied probabilistic techniques to model word sequences. Introduced n-gram models.
  • Neural Network-based: Architectures like RNNs and LSTMs improved context modeling.
  • Transfer Learning: Leveraging knowledge from pre-trained models accelerated development.
  • Self-Supervised: Models trained on unlabeled data via objectives like masked language modeling.
  • Large-Scale Models: Scaled up models like GPT-3 showed impressive generative abilities.