Progress: From Selling NLP to Providing NLP Services
December 11, 2017
Years ago, Progress Software owned an NLP system. I recall conversations with natural language processing wizards from Easy Ask. Larry Harris developed a natural language system in 1999 or 2000. Progress purchased EasyAsk in 2005 if memory serves. I interviewed Craig Bassin in 2010 as part of my Search Wizards Speak series.
The recollection I have was that Progress divested itself of EasyAsk in order to focus on enterprise applications other than NLP. No big deal. Software companies are bought and sold everyday.
However, what makes this recollection interesting to me is the information in “Beyond NLP: 8 Challenges to Building a Chatbot.” Progress went from a software company who owned an NLP system to a company which is advising people like me how challenging a chatbot system can be to build and make work. (I noted that the Wikipedia entry for Progress does not mention the EasyAsk acquisition and subsequent de-acquisition.) Either small potatoes or a milestone best jumped over I assume.)
Presumably it is easier to advise and get paid to implement than funding and refining an NLP system like EasyAsk. If you are not familiar with EasyAsk, the company positions itself in eCommerce site search with its “cognitive eCommerce” technology. EasyAsk’s capabilities include voice enabled natural language mobile search. This strikes me as a capability which is similar to that of a chatbot as I understand the concept.
History is history one of my high school teachers once observed. Let’s move on.
What are the eight challenges to standing up a chatbot which sort of works? Here they are:
- The chat interface
- NLP
- The “context” of the bot
- Loops, splits, and recursions
- Integration with legacy systems
- Analytics
- Handoffs
- Character, tone, and persona.
As I review this list, I note that I have to decide whether to talk to a chatbot or type into a box so a “customer care representative” can assist me. The “representative” is, the assumption is, a smart software robot.
I also notice that the bot has to have context. Think of a car dealer and the potential customer. The bot has to know that I want to buy a car. Seems obvious. But okay.
“Loops, splits, and recursions.” Frankly I have no idea what this means. I know that chatbot centric companies use jargon. I assume that this means “programming” so the NLP system returns a semi-on point answer.
Integration with legacy systems and handoffs seem to be similar to me. I would just call these two steps “integration” and be done with it.
The “character, tone, and persona” seems to apply to how the chatbot sounds; for example, the nasty, imperious tone of a Kroger automated check out system.
Net net: Progress is in the business of selling advisory and engineering services. The reason, in my opinion, was that Progress could not crack the code to make search and retrieval generate expected payoffs. Like some Convera executives, selling search related services was a more attractive path.
Stephen E Arnold, December 11, 2017
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