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AI Builder Deepdive DynamicsPower! Brussels 2019


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Slide deck of my DyanmicsPower! Brussels session.

Session description:
AI Builder is here!
The Citizen Developer style tool to easily add Artificial Intelligence to your PowerApps and Flows.
In this session we will take a deep dive into this great new tool in the Power Platform stack. How to build your own models and how to embed them in your apps and flows.
We will look at the what is possible, but also what are the limits and boundaries you need to take in consideration.
We will cover best practices and tips and tricks.
In a nutshell: everything you need to know to get started yourself.

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AI Builder Deepdive DynamicsPower! Brussels 2019

  1. 1. Rebekka Aalbers AI Builder Deep Dive
  2. 2. ➢ Technology consultant @ ➢ Co-organizer ➢ Dutchy ➢ Book nerd ➢ Lover of all things Unicorn ➢ 3 cats – 1 husband Rebekka Aalbers #PowerAddict #LessCodeMorePower
  3. 3. Special thanks to our local sponsors
  4. 4. Target audience You who want to know more about AI Builder You have (some) experience with the tools in the Power Platform (CDS, Apps, Automation)
  5. 5. Goal Understand how, why, and when to use AI Builder
  6. 6. Agenda
  7. 7. Why & What AI Builder
  8. 8. But first! Let’s generate some demo data! • Tweet something using #AIBuilder • Use a language you like (Latin script)
  9. 9. 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
  10. 10. Guided point-and-click AI applications AI for every skill level Embedded within the Microsoft Power Platform and Dynamics 365
  11. 11. GA on October 1st 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 New! New! New! New!
  12. 12. 2 Model types Custom models Prebuilt models
  13. 13. Select the model
  15. 15. 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
  16. 16. 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.
  17. 17. Coming Q4 CY19 • Related entities • Filtering of training data set • Scheduling • Predict two or more outcomes • Predict a number Q1 CY20 • Power Apps component to explain prediction output Ideas • Forecasting time series • Data lake support
  18. 18. 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!
  19. 19. 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.
  20. 20. Not supported (Yet!) •Complex nested tables •Check boxes or radio buttons •PDF documents > 50 pages •Fillable PDF’s
  21. 21. Coming Q4 CY19 • Support for larger file sizes • Support for TIFF files Q1 CY20 • Manually tag fields not automatically detected Ideas • Combo box detection • Specialized model (e.g. invoices) • Multiple document types in one model
  22. 22. 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.
  23. 23. Lighting Object size Camera angle Background Use diverse images
  24. 24. 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.
  25. 25. Coming Q4 CY19 • Prebuilt models (e.g. Key Phrase, Sentiment, Language) Q1 CY20 • Improved data labelling and correction experience • Prebuilt models (e.g. Entity, Intent) • Power Apps and Power Automate integration • Solution import and export • GA Ideas • Multi-entity and additional sources • Filtering • Continuous learning and feedback • New scenarios
  26. 26. 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
  27. 27. 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
  28. 28. Coming Q4 CY19 • Prebuilt models on Build page • Power Apps OCR component Q1 CY20 • Power Automate templates • Text recognition app templates • Text recognition v2 • GA Ideas • Receipts • Speech
  29. 29. Demo
  30. 30. Availability, Administration & Licensing
  31. 31. Availability per region
  32. 32. Custom model maintenance & deployment
  33. 33. 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
  34. 34. 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
  37. 37. 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
  38. 38. Q & A
  39. 39. Special thanks to our local sponsors
  40. 40. The End