AI Infused Search

This is the presentation I used for the Global AI Tour 2021.

Transcript

1. AI Infused Search
   Daron Yöndem
   http://daron.me
   @daronyondem
   

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2. Levels of Artificial Intelligence
   Easy Medium Hard
   Use an
   existing model
   Customize a
   pre-trained model
   Train a new model
   from scratch
   A pre existing
   Service like a box
   around someone's face
   It can recognize face
   But we need specific
   faces
   Lot’s of time and
   effort needed
   

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3. What is Azure Cognitive Search?
   • A search engine for full text search
   • Rich indexing, with text analysis and optional AI enrichment for
   content extraction and transformation
   • Simple syntax, full Lucene syntax, and typeahead search
   • REST APIs and client libraries in Azure SDKs for .NET, Python, Java,
   and JavaScript
   • State-of-art ranking algorithms through semantic search (preview)
   

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4. Putting the pieces together
   

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5. Indexers
   • Crawler that extracts searchable text and metadata from an
   external Azure data source
   • Azure SQL, Azure Cosmos DB, Azure Table Storage and Blob Storage
   • In Preview: Amazon Redshift, Salesforce Objects, Snowflake
   

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6. AI Enrichment
   • An extension of indexers
   • Built-in skills from Microsoft or custom skills
   • Natural language processing
   • Entity recognition, language detection, key phrase extraction, text
   manipulation, sentiment detection, and PII detection.
   • Image processing skills
   • Optical Character Recognition (OCR) and identification of visual
   features, such as facial detection, image interpretation, image
   recognition
   

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7. AI Enrichment Flow
   

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8. Knowledge Store
   

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9. AI Enrichment
   DEMO
   

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10. Semantic Search
    • Language Understanding
    • Semantic Captions and Highlights
    • Semantic Answers
    • Semantic ranking instead of similarity scoring algorithm.
    • Spell Check
    

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11. Semantic Search
    DEMO
    

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12. Why not a database search?
    • Linguistic-aware text processing (stemming, lemmatization,
    word forms) in 56 languages
    • Autocorrection of misspelled words, synonyms, suggestions,
    scoring controls, facets, and custom tokenization.
    • Offload search
    

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13. Why a database search?
    • Paging in Azure Search relies on the $skip parameter, which is
    currently capped at a maximum of 100000. (use of partitions to
    read all data)
    • No backup / restore
    • Static schema
    • No joins if needed.
    • Optimized heavily for query performance, slower write
    performance
    

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14. Resources
    Semantic Search Sign Up
    https://aka.ms/SemanticSearchPreviewSignup
    Azure Search Documentation
    https://drn.fyi/35mz2e7
    Quickstart: Use cognitive skillset in the Azure portal
    https://drn.fyi/3iFnBpB
    

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15. Thanks
    http://daron.me | @daronyondem
    Grab slides on http://decks.daron.me/
    

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