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Neuro-symbolic AI combines neural networks' pattern recognition with symbolic reasoning's logical capabilities, creating more robust and interpretable AI systems.

This hybrid approach addresses limitations in traditional AI, particularly the need for explainability and reasoning, offering significant potential across various industries like healthcare and finance.

However, challenges remain, including the need for expertise in both fields and the lack of standardised tools. Successful adoption requires multidisciplinary teams, robust data architectures, and a focus on specific use cases where traditional AI proves inadequate.