The article discusses the challenges and advancements in integrating neural audio codecs with language models (LLMs) to improve audio understanding and generation. It highlights the limitations of current speech LLMs, which often rely on text transcription, and explains how neural audio codecs can facilitate direct audio processing, allowing models to predict audio continuations more effectively. The piece also covers technical aspects of tokenizing audio and the development of the Mimi codec.