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.

To view and download this free Opus Research report, please complete the brief contact form below.

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