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Designing an animal-like brain: black-box “deep learning algorithms” to solve problems, with an (approximately) Bayesian “consciousness” or “executive functioning organ” that attempts to make sense of all these inferences

By Andrew

cat-brain-compare-human-brain

The journal Behavioral and Brain Sciences will be publishing this paper, “Building Machines That Learn and Think Like People,” by Brenden Lake, Tomer Ullman, Joshua Tenenbaum, and Samuel Gershman. Here’s the abstract:

Recent progress in artificial intelligence (AI) 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 object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. …read more

Source:: http://andrewgelman.com/2016/12/14/designing-animal-like-brain-black-box-deep-learning-algorithms-solve-problems-approximately-bayesian-consciousness-executive-functioning-organ-attempts-make-sense-o/

      



This post first appeared on Measurement Databases For Industry & Science, please read the originial post: here

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Designing an animal-like brain: black-box “deep learning algorithms” to solve problems, with an (approximately) Bayesian “consciousness” or “executive functioning organ” that attempts to make sense of all these inferences

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