Embodied AI systems fail to translate from simulation to real-world task execution

Companies developing embodied AI robots and autonomous systems struggle to move beyond proof-of-concept demonstrations to reliable real-world performance. Current AI models can run in controlled environments but fail when deployed in actual operational scenarios with unpredictable variables, causing expensive delays in commercialization and ROI realization.