The article discusses the challenges and advancements in integrating neural audio codecs with language models (LLMs) to improve speech understanding and generation. It highlights the limitations of current speech LLMs compared to text-based models and introduces the concept of using audio codecs to better model and predict audio continuations. The exploration includes technical details about tokenizing audio and training models to handle the complexities of sound data.