Making AI BOT service easy, by AWS

Lets build a Conversational interface between a User[Human] and a AI powered Bot system.

AI capabilities in AWS* LEX:

ASR [Automatic Speech Recognition] will translate Voice into Text.

NLU [Natural Language understanding] will understand the correct Intent from your Input text/phrase/language.

Designing a new AI Product using LEX. It can understand Voice/Speech/Text/language.

Your new LEX Bot can be easily integrated with all AWS services. This Bot can be deployed to any Bot platform — Slack, Facebook Messenger, etc.

We can use Voice and Text, communication channels to get work done. This is a Natural way of communication.

User and Bot — interaction workflow:

Voice commands->translate to Text->Understanding Language of Text 
-> take Actions -> return Responses

NLU will try to understand your Input Text/Utterances and find the Correct Intent for your Utterance. If NLU does not find a Intent for your Input text, means your Bot is not working at optimum level.

**The Bot design concepts:

Bot

Intent — performs a specific Action

Utterances — Speech or Text phrases which specify your Intent

Slot — input fields required for the Intent

Fulfillment — take approval from User before taking Action

Action — API or DB call

Let’s understand in depth:

  1. Bot is your AI service, you will deploy to Facebook messenger and Slack
  2. Intent is what User wants to do ? commands for the Bot system
  3. Slot — input parameters for your Intent
  4. Attributes of an Slot = Slot name, Data Type[date, string, city, currency], Default values
  5. Bot is a collection of Intents
  6. Ur Intent will need collection of Slots for taking Action on behalf of User
  7. To take Action — the Bot will invoke the Lambda function and pass the validated Slot values taken from the User
  8. Finally, the response is returned to the User
  9. You can create Versions of your Bot, Intent and Slot
  10. We can Monitor our Bot