Innate knowledge in the human brain is crucial to this kind of reasoning that we do in extrapolating. We don't know exactly what's innate, but there are at least about a dozen things that are inundable. The field of developmental psychology is dominated by people who want to learn everything from scratch. But i think one of the biggest problems with machine learning is it has no idea how to nail down these ideas.
Artificial intelligence is everywhere around us. Deep-learning algorithms are used to classify images, suggest songs to us, and even to drive cars. But the quest to build truly “human” artificial intelligence is still coming up short. Gary Marcus argues that this is not an accident: the features that make neural networks so powerful also prevent them from developing a robust common-sense view of the world. He advocates combining these techniques with a more symbolic approach to constructing AI algorithms.
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Gary Marcus received his Ph.D. in cognitive science from MIT. He is founder and CEO of Robust.AI, and was formerly a professor of psychology at NYU as well as founder of Geometric Intelligence. Among his books are Rebooting AI: Building Machines We Can Trust (with Ernest Davis).
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