Edward discusses the advantages of recurrent neural networks (RNN) over traditional methods like linear autoregression and Markov chains. He highlights RNN's ability to process sequential data without predefined states, making it more expressive. Additionally, he shares insights from his experience with stochastic process models, emphasizing the efficiency and predictive power of RNN compared to slower training processes.
