Artificial intelligence has made great strides in many areas lately, yet it
has had comparatively little success in general-use robotics. We believe one of
the reasons for this is the disconnect between traditional robotic design and
the properties needed for open-ended, creativity-based AI systems. To that end,
we, taking selective inspiration from nature, build a robust, partially soft
robotic limb with a large action space, rich sensory data stream from multiple
cameras, and the ability to connect with others to enhance the action space and
data stream. As a proof of concept, we train two contemporary machine learning
algorithms to perform a simple target-finding task. Altogether, we believe that
this design serves as a first step to building a robot tailor-made for
achieving artificial general intelligence.

通过从自然中选择性启示，我们构建了具有大规模行动空间、多个相机提供的丰富传感数据流以及与其他系统连接以增强行动空间和数据流的强大且部分软性的机器人肢体。作为概念验证，我们训练了两种当代机器学习算法来执行简单的目标寻找任务，将这一设计视为构建用于实现人工通用智能的机器人的第一步。