Adji explains the concept of topic modeling, detailing how it identifies themes across documents using distributions over words. He discusses the application of LDA and neural topic models, highlighting the innovative use of RNNs to determine the relevance of topic content for predicting words. This approach bridges traditional modeling techniques with modern neural network capabilities, showcasing the flexibility of RNNs in natural language processing.
