Traditional machine learning remains relevant and effective despite the rise of large language models (LLMs). The article highlights five reasons for its continued importance, such as its efficiency in certain tasks, ease of interpretation, and ability to work with smaller datasets, which makes it a valuable tool in various applications.

Pinterest has improved its search relevance by implementing a large language model (LLM)-based pipeline that enhances how search queries align with Pins. The system utilizes knowledge distillation to scale a student relevance model from a teacher model, integrating enriched text features and conducting extensive offline and online experiments to validate its effectiveness. Results indicate significant improvements in search feed relevance and fulfillment rates across diverse languages and regions.