Learning Machines
Boman, Magnus (Swedish Institute of Computer Science) | Sahlgren, Magnus (Swedish Institute of Computer Science) | Görnerup, Olof (Swedish Institute of Computer Science) | Gillblad, Daniel (Swedish Institute of Computer Science)
This position paper explicates the notion of learning machines and how they may cooperate and compete to scale over multiple domains. We argue that important problem applications very soon will start to benefit from cross-domain learning housed in learning machines. We outline an architecture involving human-machine interplay, including education of, and assessments of the value of learning machines.
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