VLMs have the potential to significantly enhance the capabilities of robotic systems beyond what is demonstrated by MOKA. One key aspect is the ability of VLMs to understand and generate complex language instructions, allowing robots to interpret a wide range of tasks specified in natural language. This can enable robots to perform more diverse and intricate manipulation tasks with greater flexibility and adaptability. Additionally, VLMs can leverage vast amounts of pre-existing knowledge from their training data, enabling robots to make more informed decisions based on a broader understanding of concepts and contexts. Furthermore, advancements in VLMs could lead to improved reasoning abilities, better generalization across different scenarios, and enhanced interaction capabilities between robots and humans through natural language interfaces.