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What Is Neuro-Symbolic AI And Why Are Researchers Gushing Over It

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Building thinking machines have been a human obsession since ages, and right through history, we have seen many researchers working on the concept of generating intelligent machines. While neural networks are the most popular form of AI that has been able to accomplish it, ‘symbolic AI’ once played a crucial role in doing so. It was used in IBM Watson to beat human players in Jeopardy in 2011 until it was taken over by neural networks trained by deep learning.  While neural networks have given us many exciting developments, researchers believe that for AI to advance, it must understand not only the ‘what’ but also the ‘why’ and even process the cause-effect relationships.  The current deep learning models are flawed in its lack of model interpretability and the
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Srishti Deoras
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.
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