This goes back to what DJ said "Many chatbots are "intent" identifiers, not learning AI's. This means, like Will stated, they identify an intent, but not learn. It's up to your code to determine what to do with that intent. "

This brings up a good discussion point. So dialogflow has machine learning and it can have rule based learning but what they are geared towards more so is text based chat.

That's what these services are designed for, Dialogflow, Watson (for it's chatbot service), the Microsoft Azure Chatbot server - they are designed to make a chat agent that is usually text based (but they can use speech easily - hopefully that nuance doesn't confuse anyone).

The machine learning can do things like if you have an intent for asking about "directions to the hotel" but you misspell it as "derections to ther hotle" - machine learning being turned on comes into play to help compensate for that.

Or "directions hotel" machine learning or rule based learned may help compensate for fragmented sentence to be understood.

And Dialogflow has a pre-built "small talk" agent which is a generalized chat agent probably close to a general Pandorbot with a few distinctions. But if you want it to adapt to what you are saying, like in DJ's example you do have to add some coding and scripting in the agent.

On the plus side, it is extremely easy to change and customize the intents for the agents in Dialogflow. If you watched my video you saw me mention that the agent's responses did not sound very "Spock" like for my "JD Spock" robot, it's very easy to adjust them.

Pandorabots is much different in my mind because it uses AIML files to configure the chatbot "brain" which is technology that has been around since 2001 and I would say prior to AIML the same chatbot setup was around for a years prior, at least since 1996. Because in 1996 I had a shareware chatbot that used text based files that could keep track of my input the same way such as my name. It was goofy. For all I know it was the great grandfather of Pandorbots. I don't say this to dismiss Pandorabots, just to clarify their technology.

Because the more everyone talks about their robot chat needs, I think everyone is saying they are interested in different functional chat qualities and I don't think necessarily any one of the services fulfill everyone's wants for their robot.

But much like the first person to put peanut butter and jelly together, if you intermix solutions, you might be on to something.

Justin, thanks for clearing that up...easy for me to get off the trail. I can tell I struggle with the "one program to rule them all", the complete "push button for real life human robot"...not yet coming to a store near you. I need to focus on the task at hand, the limitations and what needs to be demonstrated

Justin, Thanks for the over-view. It answered questions and added more. Time and investigation will work it out. My desire is to incorporate the Omron to help drive specific chats for the face detected or the age / gender if the face is unknown. I assume agents for each detection will be needed.

Will, Have you decided to stay with Watson, or Dialogflow ? No mater which is picked, it seems development is needed to meet the needs.

I see tough decisions and work ahead, looking for the magic mushroom.

Ron

I’m my opinion it looks like Dialogflow is the easiest solution. Easy as in David C has already created a framework and a great foundation. Looking thru the videos that Justin linked to, Dialogflow is simple and clear to setup. It may not be the magic mushroom but it will get the job done!

Came across this today. Make your NAO bot Smarter . Looks like a tech talk webinar type thing but maybe worth joining. More info on this page.

It is 1pm eastern Monday the 16th of January.

"In this tech talk, we will show you how you can add intelligence to a NAO robot with IBM Data Science Experience and IBM Conversation service."

https://developer.ibm.com/code/events/ibm-code-tech-talk-make-a-nao-robot-smarter/

I would also be very happy if we would keep dialogflow as our main tool for natural language and intent recognition... Its easy to use and offers good integration with our DIY projects!

I also tend to think that it is not the solution for everything...but it will help to build an intend driven workflow for our robots. It is never to be seen as a chatbot, the main purpose of dialogflow is natural language recognition and intent based response!

@DJ is there a way you could share the source code the api.ai plugin?

I added the source code link to the plugin description. Available here: https://synthiam.com/redirect/legacy?table=plugin&id=193