Neurosymbolic AI

The ongoing revolution in artificial intelligence (AI)--in image recognition, natural language processing and translation, and much more--has been driven by neural networks, specifically many-layer versions known as deep learning. These systems have well-known weaknesses, but their capability continues to grow, even as they demand ever more data and energy. At the same time, other critical applications need much more than just powerful pattern recognition, and deep learning does not provide the sorts of performance guarantees that are customary in computer science. To address these issues, some researchers favor combining neural networks with older tools for artificial intelligence. In particular, neurosymbolic AI incorporates the long-studied symbolic representation of objects and their relationships.