Roland discusses the challenges of instilling metaphorical understanding in language models, particularly in code generation tasks. He emphasizes the importance of grounding these models in visual or perceptual inputs to enhance their comprehension of spatial relationships and procedural knowledge. Without this grounding, he argues, models may struggle to grasp the deeper implications of tasks like variable swapping.
