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AWS User Group Singapore / Amazon Lex -- JAWSDAYS 2017

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In this presentation, we cover the growth and experience of the AWS User Group Singapore. The second half covers the use of Amazon Lex to augment User Group activities

This was originally delivered at JAWSDAYS 2017 Tokyo:- http://jawsdays2017.jaws-ug.jp/session/1337/

Engage your users with a natural language conversational interface using voice and text.
You will learn how to:
– Create a chat bot to understand your users’ intentions and fulfil their requests.
– Engage in a conversation to extract key pieces of data from the user
– Fulfil the users’ intentions with AWS Lambda functions
– Integrate with Facebook Messenger

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AWS User Group Singapore / Amazon Lex -- JAWSDAYS 2017

  1. 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Alex Smith – Amazon Web Services Jo-Anne Tan – Gowild.sg JAWS DAYS 2017 Singapore AWS User Group Amazon Lex
  2. 2. AWS User Groups
  3. 3. AWS User Groups – ASEAN ASEAN 10 Member States • SG, TH, VN, ID, PH, MY, MM, KH, LA, BN https://aws.amazon.com/usergroups/
  4. 4. AWS User Groups – ASEAN Jakarta (Indonesia) Kuala Lumpur (Malaysia) Manila (Philippines) Singapore Bangkok (Thailand) Hanoi (Viet Nam) https://aws.amazon.com/usergroups/
  5. 5. AWS User Group - Singapore The “Little Red Dot” 5.75 Million • 3.9m Citizen/PR • 1.6m Other != China
  6. 6. AWS User Group - Singapore 4 Languages (-and more) Asia Pacific Hub “Kiasu”
  7. 7. Restarted regular meetings
  8. 8. Restarted regular meetings Passed 1000 members (2016-01-08)
  9. 9. Restarted regular meetings Passed 1000 members (2016-01-08) Changed to a better quality pizza shop
  10. 10. What worked well Regularity of meetings Good venue & AV Engineers.sg
  11. 11. Engineers.sg • Oct 2013 – PHP UG • >1200 videos • 40 Strong Team • More info: https://alexjs.co/engineers http://engineers.sg
  12. 12. What worked well Regularity of meetings Good venue & AV Engineers.sg
  13. 13. What worked well Regularity of meetings Good venue & AV Engineers.sg Beer
  14. 14. What didn’t work well AWS driven group Huge variance in talk quality Attendance/RSVP discrepancy
  15. 15. What’s next?
  16. 16. AWS User Group SG links: https://www.facebook.com/groups/awsugsg/ https://www.meetup.com/AWS-SG/ https://engineers.sg
  17. 17. What didn’t work well AWS driven group Huge variance in talk quality Attendance/RSVP discrepancy
  18. 18. Attendance vs RSVP Discrepancy User intent vs intended usage The trash can analogy Reduce the effort to comply
  19. 19. Amazon Lex
  20. 20. Why Did We Build Amazon Lex?
  21. 21. Advent of Conversational Interactions 1st Gen: Punch Cards & Memory Registers 2nd Gen: Pointers & Sliders 3nd Gen: Conversational Interfaces
  22. 22. Conversational Access On-Demand Accessible Efficient Natural
  23. 23. Conversational Access On-Demand Accessible Efficient Natural
  24. 24. Developer Challenges Speech Recognition Language Understanding Business Logic Disparate Systems Authentication Messaging platforms Scale Testing Security Availability Mobile Conversational interfaces need to combine a large number of sophisticated algorithms and technologies
  25. 25. Amazon Lex: New service for building conversational interfaces using voice and text
  26. 26. Amazon Lex - Features Text and Speech language understanding: Powered by the same technology as Alexa Enterprise SaaS Connectors: Connect to enterprise systems Deployment to chat services Designed for Builders: Efficient and intuitive tools to build conversations; scales automatically Versioning and alias support
  27. 27. Text and Speech Language Understanding Speech Recognition Natural Language Understanding Powered by the same Deep Learning technology as Alexa
  28. 28. Amazon Lex – Use Cases Informational Bots Chatbots for everyday consumer requests Application Bots Build powerful interfaces to mobile applications • News updates • Weather information • Game scores …. • Book tickets • Order food • Manage bank accounts …. Enterprise Productivity Bots Streamline enterprise work activities and improve efficiencies • Check sales numbers • Marketing performance • Inventory status …. Internet of Things (IoT) Bots Enable conversational interfaces for device interactions • Wearables • Appliances • Auto ….
  29. 29. Amazon Lex - Benefits High quality Text and Speech Language Understanding Built-in integration with the AWS platform Seamlessly deploy and scale Easy to use Cost effective
  30. 30. Lex Bot Structure Utterances Spoken or typed phrases that invoke your intent BookHotel Intents An Intent performs an action in response to natural language user input Slots Slots are input data required to fulfill the intent Fulfillment Fulfillment mechanism for your intent User input Response
  31. 31. Lex Bot Structure: Utterances Attend the user group Come to the meet up User inputs: I want to come to the next meetup Could I attend the next user group please Maps to RegisterUserForEvent intent RegisterUserForEvent intent UTTERANCES
  32. 32. Lex Bot Structure: Utterances Attend the user group on {eventDate} Come to the meet up on {eventDate} User inputs: I want to come to the next meetup on 12 March 2017 Could I attend the user group tomorrow please Maps to RegisterUserForEvent intent; eventDate=2017-12-03 RegisterUserForEvent intent UTTERANCES SLOTS eventDate AMAZON.DATE SLOT NAME SLOT TYPE
  33. 33. Lex Bot Structure: Fulfilment RegisterUserForEvent eventDate=2017-03-12 SLOT INTENT AWS Lambda Integration Intents and slots passed to AWS Lambda function for business logic implementation. Return to Client
  34. 34. Lambda input event { ..., "invocationSource": "FulfillmentCodeHook or DialogCodeHook", "userId": "user-id", "bot": {...}, "outputDialogMode": "Text or Voice”, "currentIntent": { "name": "intent-name", "slots": { "slot-name": "value", "slot-name": "value", "slot-name": "value" }, "confirmationStatus": "None, Confirmed, or Denied" } }
  35. 35. Lambda response object { ..., "dialogAction": { "type": "ElicitIntent, ElicitSlot, ConfirmIntent, Delegate, or Close", "fulfillmentState": "Fulfilled or Failed", "message": { "contentType": "PlainText or SSML", "content": "message to convey to the user" }, "intentName": "intent-name", "slots": { "slot-name": "value", "slot-name": "value", "slot-name": "value" }, "slotToElicit" : "slot-name", }
  36. 36. Response card { ..., responseCard: { "version": 1, "contentType": "application/vnd.amazonaws.card.generic", "genericAttachments": [ { "title": "Flowers", "subTitle": “Pick a flower”, "imageUrl: "…", "buttons": [ {"text": "tulips","value": "tulips"}, {"text": "lilies","value": "lilies"}, {"text": "roses","value": "roses"} ] } ] } Pick a flower
  37. 37. “Attend an Event” Attend event 12 March “Attend the event on 12 March” Automatic Speech Recognition Natural Language Understanding Intent/Slot Model Utterances “You are now confirmed for the next event on 12th March” Polly the on RegisterUserForEvent eventDate SLOT INTENT Validate eventDate slot value “You are now confirmed for the event on 12th March” Update DB
  38. 38. “Attend an Event” Attend event 12 March “Attend the event on 12 March” Automatic Speech Recognition Natural Language Understanding Intent/Slot Model Utterances “You are now confirmed for the next event on 12th March” Polly the on RegisterUserForEvent eventDate SLOT INTENT Validate eventDate slot value “You are now confirmed for the event on 12th March” Update DB
  39. 39. “Attend an Event” Attend event 12 March “Attend the event on 12 March” Automatic Speech Recognition Natural Language Understanding Intent/Slot Model Utterances “You are now confirmed for the next event on 12th March” Polly the on RegisterUserForEvent eventDate SLOT INTENT Validate eventDate slot value “You are now confirmed for the event on 12th March” Update DB
  40. 40. “Attend an Event” Attend event 12 March “Attend the event on 12 March” Automatic Speech Recognition Natural Language Understanding Intent/Slot Model Utterances “You are now confirmed for the next event on 12th March” Polly the on RegisterUserForEvent eventDate SLOT INTENT Validate eventDate slot value “You are now confirmed for the event on 12th March” Update DB
  41. 41. Event Manager Bot: Flow of Information GetUpcomingEvent INTENT GetUpcomingEventAgenda eventDate SLOT INTENT RegisterUserForEvent eventDate SLOT INTENTList summary of all events Show details for event on {eventDate} Register user for event on eventDate}
  42. 42. Event Manager Bot: Flow of Information GetUpcomingEvent INTENT GetUpcomingEventAgenda eventDate SLOT INTENT RegisterUserForEvent eventDate SLOT INTENT Do you want to hear more? YES NO “Okay. Bye!” ?
  43. 43. Thank You! http://aws.amazon.com/lex
  • hasan_99

    Dec. 18, 2018

In this presentation, we cover the growth and experience of the AWS User Group Singapore. The second half covers the use of Amazon Lex to augment User Group activities This was originally delivered at JAWSDAYS 2017 Tokyo:- http://jawsdays2017.jaws-ug.jp/session/1337/ Engage your users with a natural language conversational interface using voice and text. You will learn how to: – Create a chat bot to understand your users’ intentions and fulfil their requests. – Engage in a conversation to extract key pieces of data from the user – Fulfil the users’ intentions with AWS Lambda functions – Integrate with Facebook Messenger

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