Artificial Intelligence Is Stuck. Here’s How to Move It Forward.

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Artificial Intelligence Is Stuck. Here’s How to Move It Forward.
I fear, however, that neither of our two current approaches to funding A. I.
research — small research labs in the academy and significantly larger labs in private industry — is poised to succeed.
Integrating that sort of knowledge of the world may be the next great hurdle in A. I., a prerequisite to grander projects like using A. I.
to advance medicine and scientific understanding.
To get computers to think like humans, we need a new A. I.
paradigm, one that places “top down” and “bottom up” knowledge on equal footing.
Presumably, my daughter relied on an implicit theory of how her body moves, along with an implicit
theory of physics — how one complex object travels through the aperture of another.
Some of the best image-recognition systems, for example, can successfully distinguish dog breeds, yet remain
capable of major blunders, like mistaking a simple pattern of yellow and black stripes for a school bus.
My daughter had never seen anyone else disembark in quite this way; she invented it on her own —
and without the benefit of trial and error, or the need for terabytes of labeled data.

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