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- W3048482316 abstract "Abstract In ‘Computing Machinery and Intelligence’, Turing, sceptical of the question ‘Can machines think?’, quickly replaces it with an experimentally verifiable test: the imitation game. I suggest that for such a move to be successful the test needs to be relevant, expansive, solvable by exemplars, unpredictable , and lead to actionable research. The Imitation Game is only partially successful in this regard and its reliance on language, whilst insightful for partially solving the problem, has put AI progress on the wrong foot, prescribing a top-down approach for building thinking machines. I argue that to fix shortcomings with modern AI systems a nonverbal operationalisation is required. This is provided by the recent Animal-AI Testbed, which translates animal cognition tests for AI and provides a bottom-up research pathway for building thinking machines that create predictive models of their environment from sensory input." @default.
- W3048482316 created "2020-08-18" @default.
- W3048482316 creator A5012483737 @default.
- W3048482316 date "2020-08-13" @default.
- W3048482316 modified "2023-09-24" @default.
- W3048482316 title "Building Thinking Machines by Solving Animal Cognition Tasks" @default.
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- W3048482316 doi "https://doi.org/10.1007/s11023-020-09535-6" @default.
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