Next-generation natural language technologies: The deep learning agenda

The most appreciative advancements in statistical AI, the ones with the most meaning and potential to improve data's worth to the enterprise, are deep learning deployments of computer vision and natural language technologies. The distinctions between these applications involve much more than image recognition versus that of speech or language. Horizontal computer vision use cases pertain to some aspects of inter-machine intelligence, e.g., scanning videos or production settings for anomalies and generating alerts to initiate automated procedures to address them. Conversely, natural language technologies provide the most effective cognitive computing application for furthering human intelligence, decision making, and the action required to extract business value from such perceptivity. While the utility derived from image recognition largely varies according to the vertical, the capability for machines to understand natural language--for humans to interact with databases in layperson's terms across sources--strikes at the core of converting the unstructured data of language into informed action.