Every Neural Network Explained - RNN - Recurrent Neural Networks

Summary

The transcript explores the evolution of language models, tracing their development from early recurrent neural networks to more advanced architectures, focusing on how researchers transformed words into mathematical vectors to enable computational language understanding. It details the technical process of converting words into numerical representations, using matrix multiplication and hidden states to predict subsequent words in a sequence. Despite initial limitations of recurrent neural networks for processing long sentences, the narrative highlights the foundational machine learning principles that ultimately paved the way for more sophisticated language models like ChatGPT.