Model routing refers to the process of selecting the best-performing AI model for a specific task. Researchers from IBM Research argue that while model routing may seem simple, it can be complex and nuanced due to various factors such as model size, computational resources, and data quality. They propose a new approach called 'model routing is simple until it isn't' which takes into account these complexities and provides a more accurate selection of models. --- Why it matters: This matters because AI engineers often struggle with selecting the right model for their task, leading to suboptimal performance or inefficient use of resources. This research aims to improve the accuracy of model selection, which can have significant implications for applications such as natural language processing and computer vision. Source: https://huggingface.co/blog/ibm-research/model-routing-is-simple-until-it-isnt