Neuro-Symbolic AI: Coming Together of Two Opposing AI Approaches

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You thought AI is intelligent? Well, it has a long road ahead. Artificial Intelligence programs still can’t answer many basic questions that even a toddler comfortably can. David Cox, Director of MIT-IBM Watson AI lab says, “It’s time to reinvent artificial intelligence.” And, according to him, neuro-symbolic AI is the answer. We take a quick look into what ails present AI, and how AI engineers can revolutionize the discipline with neuro-symbolic AI. A Snapshot of AI limitationsSay, an AI program is asked to “Look at the picture below and tell if there are an equal number of large things and metal spheres?”

It will be impossible for a state-of-the-art AI neural network program to answer this simple question. This may sound strange after an incredibly successful era of the 2010s, filled with breakthroughs and ostensibly no AI winter. But, that’s largely the reality. Cox thinks it’s time to make AI smarter and more intelligent, and Neuro-Symbolic AI can accomplish this. Exploring Neuro-Symbolic AIStrictly speaking, neuro-symbolic AI is not new. Essentially, it combines the two already existing approaches of AI, which once were pitted against each other. Those two …

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