Human-level concept learning through probabilistic program induction

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Summary

A computational model is described that learns in a similar fashion and does so better than current deep learning algorithms and can generate new letters of the alphabet that look “right” as judged by Turing-like tests of the model's output in comparison to what real humans produce.

Type
article
Published
2015-12-11
Cited by
3,352
References
98

Keywords

Computer science, Alphabet, Artificial intelligence, Probabilistic logic, Turing

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