Sunil emphasizes the need for a new tokenizer that fundamentally understands numbers to enhance the performance of LLMs. He discusses the importance of utilizing existing deterministic tools for numerical tasks, which can lead to more accurate results. By integrating function calling and developing a domain-specific language, the approach aims to minimize errors in number-heavy outputs, ultimately improving the reliability of LLMs.
