Sunil discusses the innovative integration of time series data with large language models, emphasizing a hybrid approach that combines traditional models with advanced techniques. He critiques the limitations of LLMs in understanding numerical relationships, proposing that traditional models can enhance LLM inputs for better outcomes. The conversation highlights the ongoing experimentation and evolution in this field over the past two and a half years.
