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2008

Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning

9 years 11 months ago
Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way to construct such a system is to let it learn from the large collections of text, images, and video that are available online. More specifically, the system should use a Bayesian probability model to construct hypotheses about both specific objects and events, and general patterns that explain the observed data. Keywords. probabilistic model, architecture, knowledge acquisition
Brian Milch
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where AGI
Authors Brian Milch
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