Better Dialogflow ES Bots
REST API
Webhooks
Slot filling
Context Lifespan
Conversation Design
Bot frameworks
Mobile
Debugging
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Machine Learning

Bot Frameworks Overview

How will the DialogFlow market evolve in the coming years?

A training course student recently asked me: “Would be interested in hearing your views on how the DF market will develop in┬áthe coming years and scope for profit.”

Dialogflow vs RASA NLU

Since the introduction of Dialogflow CX, it is fair to say that RASA NLU and Dialogflow have diverged into entirely different directions. That is, they are even less comparable now because of the state machine based approach used in Dialogflow CX. In addition (to the best of my knowledge), most of the new Dialogflow features are only going into CX and not into ES, and RASA has also evolved quite a bit but in different directions.

A simple method to evaluate multiple bot frameworks

Recently I was talking to someone who has built a cross-bot-framework conversation designer – like an abstraction layer which sits on top of all the major bot frameworks and provides drag-and-drop interfaces to design your bot. It is an interesting idea, but there is a major problem – all the bot frameworks are not the same. Dialogflow ES, Dialogflow CX, Watson Assistant, Amazon Lex, Microsoft LUIS, RASA NLU – all of them are very different from each other. In fact, they are so different from each other that any effort to unify them to build a higher level abstraction layer

Exporting your Dialogflow agent to RASA NLU

As it stands now, you will probably want to avoid migrating your Dialogflow agent to RASA because it will not work as well, especially if you used ideas from my site to create a bunch of conversational turns.

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