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AI Builder Deep dive Super Power Saturday London 2020


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Slide deck of my Super Power Saturday London 2020 session.

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AI Builder Deep dive Super Power Saturday London 2020

  1. 1. 🦄 Technology consultant @ 🦄 Co-organizer 🦄 MSFT BizApps MVP 🦄 Dutchy 🦄 Book nerd 🦄 Lover of all things Unicorn 🦄 2 cats – 1 husband Rebekka Aalbers #PowerAddict #LessCodeMorePower
  2. 2. Target audience You want to know more about AI Builder You have (some) experience with the tools in the Power Platform (CDS, Apps, Automation)
  3. 3. Goal Understand How, Why, and When to use AI Builder
  4. 4. Agenda
  5. 5. Why & What AI Builder
  6. 6. But first! Let’s generate some demo data! • Tweet something using #AIBuilder • Use a language you like (Latin script)
  7. 7. Why do I like the Power Platform tools – including AI Builder? Evolved to become a Consultant at a Microsoft Partner Landed by accident in the IT-department of an end customer Started out as business user
  8. 8. Guided point-and-click AI applications AI for every skill level Embedded within the Microsoft Power Platform and Dynamics 365
  9. 9. Public Preview June 10, 2019 GA on October 1st, 2019 incl. Dynamics 365 Sales Enterprise integration Key changes • AI Builder add-on and trial offers • AI capacity management in PPAC • GA scenarios are solution aware • Scalability and reliability of GA scenarios GA scenarios now require trial or paid capacity GA Preview
  10. 10. 2 Model types Custom models Prebuilt models
  11. 11. Select the model
  13. 13. Prediction Use your database and this AI model to determine the likelihood of specific business outcomes. Form Processing (preview) Read, extract, and process data from scans, emails, PDFs, and images.​ Object Detection (preview) Build an AI model that recognizes and counts visual objects.​ Text Classification (preview) Build an application that reviews, tags, and classifies large volumes of text to track sentiment, improve customer experiences, and mine valuable insights.​ Custom models
  14. 14. Prediction - GA Determine the likelihood of specific business outcomes – Boolean (Yes/No – True/False) Input: Data in 1 CDS entity Output: prediction written back into prediction field in CDS Use automatic schedule in CDS and in Power Automate Specifics: Uses CDS Entity Only 2 outcome possibilities (Yet!) Data requirements: Minimum of 50 records in total and 10 records historical outcome for each class. Best result with at least 1000 records.
  15. 15. Be aware of • Data quality – no empty fields / faulty data • Data quantity – enough data with options that reflects the expected outcome • Unwanted bias – unselect irrelevant or misleading fields • Accuracy score between 50 – 100% BUT! You are the one to determine if the accuracy makes sense!
  16. 16. Form processing - Preview Read, extract, and process data from scans, emails, PDFs, and images.​ Output: Extracted key-value pairs and table data. Use in Power Apps Canvas & Power Automate Specifics: JPG, png or PDF – max 4 MB – Latin alphabet High quality images – between 530 x 100 and 4200 x 4200 pixels Data requirements: 5 – 10 sample documents with the same layout. Must contain keys above or to the left of the value.
  17. 17. Not supported (Yet!) •Complex nested tables •Check boxes or radio buttons •PDF documents > 50 pages •Fillable PDF’s
  18. 18. Object detection - Preview Build an AI model that recognizes and counts visual objects.​ Output: Name and count of detected objects Use in Power Apps Canvas & Power Automate Specifics: JPG, png or BMP – max 6 MB Data requirements: minimum of 15 images per object – preferably 50 or more.
  19. 19. Lighting Object size Camera angle Background Use diverse images
  20. 20. Text classification- Preview Build an application that reviews, tags, and classifies large volumes of text to track sentiment, improve customer experiences, and mine valuable insights.​ Output: List of tags with certainty score in separate entity Auto generated on schedule in CDS & used in Power Automate Specifics: Uses CDS Entity Languages: English, French, German, Dutch, Italian, Spanish, Portuguese Data requirements: Text and tags in text fields in same entity – All tags in one field using a delimeter Max 5000 characters per text item - Minimum of 50 text items per tag.
  21. 21. Tips for your training data • No high rate of missing values • Check for typos • Check for inconsistent capitalizations • Check for inconsistent or incorrect labels Data quality • Remove duplicate or irrelevant fields • Remove fields with high correlation to the outcome Unwanted bias At least 100 records per tag Balanced use of tags in your data Training data similar to actual text
  22. 22. Business card reader​ Pull contact information from business cards, store this information in your database, and import it into your CRM system. Sentiment analysis (preview) Detect positive, negative, neutral and mixed sentiment in social media, customer reviews or any text data you want to analyze. Key phrase extraction (preview) Extract the main points and key phrases in text documents. Language detection (preview) Use this model to identify the predominant language of a text document. Text recognition (preview) Extract embedded printed and handwritten text from documents and images into machine-readable character streams. Prebuilt models
  23. 23. Éric Sauvé @ZePowerDiver
  24. 24. 2020 Release wave 1 New AI Models • Prebuilt Text classification model • Anomaly detection • Image moderation • Receipt scanning Usability • AI Builder connector • Entity extraction model • New Power Apps controls • New prebuilt Flow templates • ‘Try’ feature for the keyword extraction model. AND MORE…
  25. 25. Demo
  26. 26. Availability, Administration & Licensing
  27. 27. Availability per region
  28. 28. Custom model maintenance & deployment
  29. 29. Update custom model Create new version • From published version • Or • From last trained version Change settings or training data Publish or • Only for: • Prediction model • Text classification model Retrain model
  30. 30. Deployment through solutions* PROD Production environment Managed solution • Use model TEST /QA Sandbox environment Managed solution • Test model DEV Sandbox environment Unmanaged solution • Create model • Train model • Improve model
  33. 33. AI Builder License AI Builder Capacity Add-on $ 500 / subscription 1 million service credits Tenant level Credit consumption Training models Using models Credit calculation ???? – Calculator not available yet Credit allocation Allocate capacity to environments in Power Platform admin center
  34. 34. Q & A
  35. 35. Feedback • We really need your feedback. Log-in to the 365portal event page and click on the session title. • Make sure you have added the session to your schedule and you have checked in. • After you have Checked in to the session, You can leave feedback which will help the speaker and improve our future events for the community.
  36. 36. Join the Microsoft Business Applications Communities where you can connect with peers and experts and earn recognition for your contribution. Get answers to complex questions, learn from engaging discussions, read informative blogs, view webinars, and find product use examples in galleries. Connect · Learn · Share · Inspire Business Applications Communities