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There has been a debate in the past few years between the symbolists and the connectionists about the future of artificial intelligence. The symbolists say that traditional, explainable, logic-based approaches still hold tremendous promise while the connectionists say that the power of deep learning, for all its current opacity and narrow application, holds the key to more general forms of machine intelligence. This week, I speak with David Cox, IBM Director of the MIT-IBM Watson AI Lab, which is blending the two traditions in what they call neuro-symbolic AI in hopes to move AI forward.
By Craig S. Smith4.7
5555 ratings
There has been a debate in the past few years between the symbolists and the connectionists about the future of artificial intelligence. The symbolists say that traditional, explainable, logic-based approaches still hold tremendous promise while the connectionists say that the power of deep learning, for all its current opacity and narrow application, holds the key to more general forms of machine intelligence. This week, I speak with David Cox, IBM Director of the MIT-IBM Watson AI Lab, which is blending the two traditions in what they call neuro-symbolic AI in hopes to move AI forward.

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