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SG_UserGroup_Oct20_2022_NLP_AzureLangStudio.pptx

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SG_UserGroup_Oct20_2022_NLP_AzureLangStudio.pptx

  1. 1. INTRODUCTION TO AZURE COGNITIVE SERVICE LANGUAGE STUDIO : DIY NLP PRIYANKA H SHAH
  2. 2. compuwizpiyu@gmail.com Linkedin.com/in/compuwizpi yu @fuzzymind1 Microsoft MVP AI AI Offering Lead, Growth Markets • Lead for Innovation(Data and AI), AI/IoT Offering lead • Data science and Big data solution engineer. • Passionate about new technologies, love to code, blog / talk about AI, ML.NET, Microsoft technology stack. • Environment enthusiast PRIYANKA H SHAH
  3. 3. Agenda • Throwback to Azure NLP • About Language Studio • Cognitive Language services suite and OPEN AI GPT • Demo • Q and A
  4. 4. THROWBACK TO AZURE NLP Do you remember: •LUIS : Conversational AI •Q and A maker : FAQ answering bot •Text Analytics : Extract insights from text
  5. 5. Types of Cognitive Services  Anomaly Detector  Personalizer  Content Moderator DECISION  Bing Auto Suggest  Bing Custom Search  Bing Entity Search  Bing News Search  Bing Image Search  Bing Spell check  Bing Video search  Bing Visual search  Bing Web search WEB SEARCH  Immersive reader  Language Understanding  Text Analytics.  Q and A maker  Text Translator LANGUAGE  Speech to Text  Text to Speech  Speaker Recognition  Speech Translation. SPEECH  Computer Vision  Custom Vision  Face recognition  Ink / Form recognizer  Video Indexer VISION
  6. 6. WHY ADVANCED NLP? •We are in the middle of a paradigm shift from search driven to an intelligent enterprise
  7. 7. DATA EXPLOSION MEANS MORE TIME SPENT IN SEARCHING OR MORE RISKS AS RESULT OF GUESSING ANALYSIS GAP VOLUME VARIETY VELOCITY INFORMATION EXPLOSION ABILITY TO ANALYZE AND WE SPEND TOO MUCH TIME SEARCHING Knowledge workers spend less than 40% of the average workweek on task specific to their jobs Communication and collaborating internally Searching and gathering information 39% 14% 19% 28% Reading and answering e-mail 39% 14% 19% 28% 7
  8. 8. 8 HOW DO YOU ENABLE YOUR WORKERS AS PART OF YOUR INTELLIGENT ENTERPRISE? Improved collaboration (expert networks)? Single and intuitive user interfaces? Consolidation of content platforms? Personalized content and search? What else? Enterprise challenges with data
  9. 9. ENTERPRISE KNOWLEDGE FINDER ENGINE AI assisted search Summarization & Preview Feedback & Analytics Video and Image Search Cognitive search Personalized • Ingest – Enrich – Explore. Cognitive Search unlocks value from your data • Natural Language Processing allows more natural search terms to be used to explore in a more intuitive way • Promote preferred and popular resources across multiple platforms • Use AI to summarise document contents • Let users see the key contents of a document before they commit to downloading and reading • Allow users to provide feedback and rate the usefulness of content • Track and show most frequently viewed documents and articles • Refine and update search rankings based on feedback and analytics • Unlock insights from videos • Full searchable transcripts, visual information, people, faces, and branding used • AI displays image metadata in results vs. just file name • ML to augment cognitive results based on profile and usage patters providing personalised results
  10. 10. KNOWLEDGE FINDER HELPS ACHIEVE 15% INCREASE IN EMPLOYEE EXPERIENCE 10 Client context: • Leading financial planning firm in Australia needed to improve the efficiency for their advisors by having relevant and prompt access to information related to financial products. • Information was located on multiple platforms which made content search through consolidation of data a challenge. • A recent acquisition of another business meant the client had to look at additional sources of content. Results 15% improved experience in finding relevant content A reduced result set was provided with relevance score and synopsis of output “It’s great, easy to use and quick to find what I am looking for” “I like that I can review the synopsis before opening the document to make sure it’s the right information” “ Absolutely amazing, the search function is great and the articles are easy to follow” “ I love it, I regularly use the knowledge finder and it is so easy to use”
  11. 11. HOW IT WORKS IN THE BACKGROUND 11 Ingest Enrich Explore Cognitive skills Pull data from storage. Reads the raw data and extract content from file formats such as PDFs, videos, and Office documents. Use cognitive skills to augment data as it’s ingested. Out of the box support for OCR, entity recognition, key phrase extraction, language detection, image analysis, and more. The additional knowledge is combined by applying AI models. The data and annotations are stored in Azure Search offering keyword search, understands multiple languages, and faceted navigation. ADVANCED NLP MODELS Term boosters Apply custom weighting to key phrases and terms to ensure prominence in results
  12. 12. KNOWLEDGE FINDING WITH AI USES A WIDE ARRAY OF ADVANCED TECHNOLOGIES 12 Frontend Infographing Visualization of contextualized information Bundled Content Grouping like content together NLP Solving natural language questions / problems Social Collaboration Interact with a closed group of experts Cognitive Analytics Best Information Best possible information in a heartbeat Next Best Action Suggested actions on what to do next Auto Crawling Receive information instead of searching for it People-centric Expert search Find the best people related to a topic Internal Docs Web Content Internal Informational Databases Social Content
  13. 13. AZURE COGNITIVE SERVICES FOR LANGUAGE Azure Cognitive Service for Language is a cloud-based service that provides Natural Language Processing (NLP) features for understanding and analyzing text. Use this service to help build intelligent applications using the web-based Language Studio, REST APIs, and client libraries. This Language service unifies Text Analytics, QnA Maker, and LUIS and provides several new features as well. These features can either be: Pre-configured, which means the AI models that the feature uses are not customizable. You just send your data, and use the feature's output in your applications. Customizable, which means you'll train an AI model using our tools to fit your data specifically.
  14. 14. LANGUAGE STUDIO
  15. 15. FEATURES OF LANGUAGE STUDIO • Identify important concepts • Identify entities and their relationships within documents. Assign labels such as dates, personally identifiable information, or your domain-specific terms. • Better understand customer perception • Analyze positive and negative sentiment in social media, customer reviews, and other sources to get a pulse on your brand. • Comprehend information faster • Extract sentences that collectively convey the essence of a document. • Automate workflows • Classify documents using your domain-specific labels to improve decision making. • Process medical text • Process unstructured medical data to improve patient care. • Converse with customers • Enable a conversational interface for users to interact with your applications, bots, and Internet of Things (IoT) devices using natural language.
  16. 16. Demo Demo

Editor's Notes

  • * Talk about video done by client for employee broadcast in organisation both Avanade and Client.

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