Building machines that learn and think with people
Nature Human Behavior, 2024. [All Versions]. [Preprint]. This perspective shows how the science of collaborative cognition can be put to work to engineer systems that really can be called ‘thought partners’, systems built to meet humans' expectations and complement humans…
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Building Machines That Learn and Think Like People cambridge.org
Behavioral and Brain Sciences, 2017. [All Versions]. [Preprint]. Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as…
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The future of open human feedback nature.com
Nature Machine Intelligence, 2025. [All Versions]. Human feedback on conversations with language models is central to how these systems learn about the world, improve their capabilities and are steered towards desirable and safe behaviours. However, this feedback is mostly…
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Embodied large language models enable robots to complete complex tasks in unpredictable environments nature.com
Nature Machine Intelligence, 2025. [All Versions]. Completing complex tasks in unpredictable settings challenges robotic systems, requiring a step change in machine intelligence. Sensorimotor abilities are considered integral to human intelligence. Thus, biologically inspired…
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Rapid trail-and-error learning with simulation supports flexible tool use and physical reasoning. pnas.org
Proceedings of the National Academy of Sciences, 2020. [All Versions]. [Project]. [Appendix]. Many animals, and an increasing number of artificial agents, display sophisticated capabilities to perceive and manipulate objects. But human beings remain distinctive in their…
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Using human brain activity to guide machine learning nature.com
Scientific Report, 2018. [All Versions].
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Generating new concepts with hybrid neuro-symbolic models. arxiv.org
CogSci'20, 2020. [All Versions].
AGI & CoCoSci › Papers > Bayesian Modeling > Bayesian Induction: “Nature Human Behavior, 2024. [All Versions]. [Preprint]. This perspective shows how the science of collaborative cognition can be put to work to engineer systems that really can be called ‘thought partners’, systems built to meet humans' expectations and complement humans…”