In a joint research effort forged in 2017, the MIT-IBM Watson AI Lab has put significant resources into a new approach to AI that could provide CX and digital transformation specialists with more accurate intent recognition. Known as "neuro-symbolic artificial intelligence," this approach could allow companies to do more with less data and provide for greater transparency and privacy. Employing the approach to Conversational AI could give brands the ability to "add common sense" to their chatbots, intelligent virtual agents and to the prompts provided to live agents. The science combines the probabilistic pattern recognition capabilities of today's Deep Neural Networks (DNNs) and "deep understanding" with an approach to AI that is based on representations of problems, logic and search that are considered more "human-readable." In a new report, Dan Miller, lead analyst and founder with Opus Research, presents the possibility for enterprises to improve automated conversational systems with significant implications for customer care, digital commerce and employee productivity.

You hear a lot about neural networks and deep learning these days. They can do a lot of impressive things like create pictures of cats that never existed and other potentially more useful examples. But symbolic AI is starting to get some attention too and when you combine the two, you get neuro-symbolic AI which may just be something to watch. Here are five things to know about neuro-symbolic AI. Neuro-symbolic networks are hybrids that take what neural networks can do and do it faster, easier, and sometimes in a way that might not have been able to be done before.

On the tray is an assortment of shapes: Some cubes, others spheres. The shapes are made from a variety of different materials and represent an assortment of sizes. In total there are, perhaps, eight objects. My question: "Looking at the objects, are there an equal number of large things and metal spheres?" The fact that it sounds as if it is is proof positive of just how simple it actually is.

On the tray is an assortment of shapes: Some cubes, others spheres. The shapes are made from a variety of different materials and represent an assortment of sizes. In total there are, perhaps, eight objects. My question: "Looking at the objects, are there an equal number of large things and metal spheres?" The fact that it sounds as if it is is proof positive of just how simple it actually is.