Synthetic Data Alone Insufficient for Robust Physical AI Training
Relying solely on synthetic data for training physical AI and robotics systems falls short when models are deployed in real-world environments. Experts highlight the need for real-world sensor data to capture unpredictable conditions that simulations often overlook. Synthetic data remains valuable for specific use cases, but anchoring training on real-world data is essential for robust performance.