Adji discusses the challenges of modeling sequential data and the importance of regularization in recurrent neural networks. He highlights traditional techniques like dropout and introduces a novel approach involving noise injection to enhance model performance. The conversation delves into the intricacies of handling high-dimensional data and the quest for improved learning methods.
