Artificial Intelligence systems cannot yet match human abilities to apply knowledge to situations that vary from what they have been programmed for, or trained for. In visual object recognition methods of inference exploiting top-down information (from a model) have been shown to be effective for recognising entities in difficult conditions. Here this type of inference, called `projection', is shown to be a key mechanism to solve the problem of applying knowledge to varied or challenging situations, across a range of AI domains, such as vision, robotics, or language. Finally the relevance of projection to tackling the commonsense knowledge problem is discussed.
翻译:人工智能系统尚不能与人的能力相匹配,将知识应用于与它们所规划或训练的不同情况。在视觉物体识别方法中,利用自上而下的信息(模型)的推论方法已证明对在困难条件下识别实体有效。在这里,被称为“预测”的这类推论被证明是解决将知识应用于各种或具有挑战性的情况的关键机制,涉及如视觉、机器人或语言等一系列AI领域。最后讨论了预测与解决常识知识问题的相关性。