In a business environment overwhelmed by too much information but not enough knowledge, technology has been little help to date; in fact, most analysts still resort to tools like Google Search to find the vital intelligence they need. As a result, we can’t read and understand textual information any faster than our grandparents could, making US the bottlenecks in our own decision-making processes in such critical fields as security, healthcare, finance, law and multinational business.

Fortunately, today there are new machine-driven technologies that are moving us beyond simple textual search and natural language processing to achieve natural language understanding (NLU), where we can quickly and easily discover the true meaning and implications of the text being researched.

Learning Objectives:

• Share new approaches to achieving natural language understanding and explain their pros and cons
• Present case studies that demonstrate the value of NLU in public and private sectors
• Help companies assess and prioritize the top challenges where NLU can be most effective
• Outline what resources you will need to have to be successful implementing NLU
• Identify the potential risks to the success of these types of projects