Moravec's Paradox and the Robot Olympics

What this post added

This post details the application of the π0.7 model to a new set of physical manipulation tasks, referred to as the "Robot Olympics." It demonstrates the model's ability to generalize and learn new skills with fine-tuning, achieving success rates on tasks like opening a self-closing door, turning a sock inside-out, using a key, peeling an orange, and cleaning a greasy pan. The post contrasts the performance of the fine-tuned π0.7 model with a baseline VLM, emphasizing the necessity of large-scale robot pre-training. It also discusses the challenges of physical intelligence and how multimodal models with diverse real-world data can overcome Moravec's paradox.