Robustness in AI Models

Robotics Transformers are neural network models adapted from NLP architectures, such as Transformer models, to enhance robotic applications. They excel in processing sequential data, enabling robots to learn control policies, interpret sensor inputs, and perform complex tasks more efficiently. By capturing long-range dependencies and context, Robotics Transformers improve autonomous decision-making and adaptability in dynamic environments.