Facebook Research Understanding Dialog

Pointing towards Facebooks interest in AI and chatbots.  Dialog understanding is hard.

The long game towards understanding dialog
By: Alexandre Lebrun, Antoine Bordes, Leon Bottou, Marco Baroni

Building an effective dialog system
At Facebook AI Research (FAIR), understanding dialogue is an ambitious and long-term AI research goal.

A truly effective dialogue system will be an assistive technology that will likely include a chatbot-type of system being able to interact with people through natural language communication. This could help people better understand the world around them and communicate more effectively with others, effectively bridging communication gaps. Researching and developing these kinds of technologies will only become more important as the amount of digital content continues to grow.

The attempt to understand and interpret dialogue is not a new one. As far back as 20 years, there were several efforts to build a machine a person could talk to and teach how to have a conversation. These incorporated technology and engineering, but were single purposed with a very narrow focus, using pre-programmed scripted responses.

Thanks to progress in machine learning, particularly in the last few years, having AI agents being able to converse with people in natural language has become a more realistic endeavor that is garnering attention from both the research community and industry.

However, most of today’s dialogue systems continue to be scripted: their natural language understanding module may be based on machine learning, but what they execute or answer is in general dictated by if/then statements or rules engines. While they are improvement on what existed decades ago, it is in large part due to the large databases of content used to create and script their responses.  .... " 

Facebook Research.