April 15, 2024, 4:42 a.m. | Mohannad Alhakami, Dylan R. Ashley, Joel Dunham, Francesco Faccio, Eric Feron, J\"urgen Schmidhuber

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.08093v1 Announce Type: cross
Abstract: 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 …

abstract advanced algorithms artificial artificial intelligence arxiv baby cs.ai cs.lg cs.ro design general intelligence machine machine learning machine learning algorithms robot robotic robotics robust success type

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