by Andrea Fink, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, DFKI The humanoid robot RH5 was developed at the DFKI Robotics Innovation Center. Credit: DFKI, Annemarie Popp As sub-symbolic AI, like deep learning, continues to advance, its limitations in safety and reliability are becoming more apparent. Verification and stability are crucial in safety-critical domains such as humanoid robotics, which is rapidly evolving into a versatile tool for various applications. However, proving the correctness of AI-based self-learning algorithms is challenging due to their uncertain inferences and opaque decision-making processes. The German Research Read More