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DXC Industrialized A.I. – Von der Data Story zum industrialisierten A.I. Service

DXC Industrialized A.I. – Von der Data Story zum industrialisierten A.I. Service

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DXC Industrialized A.I. – Von der Data Story zum industrialisierten A.I. Service

  1. 1. © 2017 DXC Technology Company. All rights reserved. DXC Industrialized A.I. May, 2019 From data story to industrialized A.I. service
  2. 2. May 10, 2019 2 • AI, How it Starts • Map the AI Journey • DXC’s Industrialized AI Agenda
  3. 3. © 2017 DXC Technology Company. All rights reserved. How it Starts The journey begins
  4. 4. May 10, 2019 4DXC Proprietary and Confidential PD_9991a-19 Cognitive Computing Simulating, specifically, the perception and reasoning aspects of human intelligence: • Natural-Language Processing • Speech • Vision Artificial Intelligence Any program that does something that we would think of as intelligent in humans AI is defined by the application of the technology rather than the technology itself. What is considered AI may change over time. AI at DXC: • Extend Domain Expertise • Perform Complex Planning • Infer intent Unsupervised Supervised Discover new patterns Learn specific patterns Cat Not Cat Artificial Intelligence Machine Learning Any program that improves its performance through experience rather than explicit programming. Deep Learning Machine learning based on neural networks
  5. 5. May 10, 2019 5DXC Proprietary and Confidential PD_9991a-19 Strong versus weak A.I.
  6. 6. May 10, 2019 6DXC Proprietary and Confidential PD_9991a-19 AI or ML? Face detection Infer one is upset Schedule a repair (Predictive Maintenance) Predict equipment breakdown Sort documents by topic (e.g. emails) Cluster documents by similarity AI ML AI ML AI ML
  7. 7. © 2017 DXC Technology Company. All rights reserved. How get to Enterprise Scale A.I. Experience? The first steps
  8. 8. May 10, 2019 8DXC Proprietary and Confidential Enterprise-Scale Data Science Experience Industrialized AI Master The Industrialized AI Master journey
  9. 9. May 10, 2019 9DXC Proprietary and Confidential Create Data Stories Run Agile Transformation Industry Consulting Experience Industrialized AI Leader The Industry Consultant
  10. 10. May 10, 2019 10DXC Proprietary and Confidential Enterprise-Scale Data Science Experience Industrialized AI Master Create Data Stories Run Agile Transformation Industry Consulting Experience Industrialized AI Leader The Industry Consultant Journey
  11. 11. May 10, 2019 11DXC Proprietary and Confidential A Common Mistake with AI Projects • Without a hypothesis: convincing stakeholders to take the leap Data Write algorithms Find patterns Tell a story Stakeholder commitment Big Gap
  12. 12. May 10, 2019 12DXC Proprietary and Confidential From Ideas to Innovation Buildathons are a great way to begin innovating with AI. We have created some effective formats to make sure the best ideas are transformed into finalized products ready to be launched. 1 2 weeks Preparation 2 48 hours Buildathon 3 3 months Industrialize For 2 weeks leading up to a buildathon, the preparation phase allows us to collect data, ideate and refine ideas. A post-buildathon phase where we industrialize the solution through a carefully structured AI innovation program. Teams composed of data scientists, data engineers and analytics developers create an AI solution in 48 hours around a theme.
  13. 13. May 10, 2019 13DXC Proprietary and Confidential Various skill sets of the DXC team AI Leaders Those who have sizzling ideas and are looking for a team. They have a vision of how AI can transform the company. Their talents include building, testing and analyzing AI solutions. Love collaboration and innovation. Experts in munging data and building analytics platforms. They know how to scale AI and make an impact. They know how to build data- driven apps that reach employees, and change how business is done. The secret ingredient to any team. Data Scientists Data Engineers Analytics Developers
  14. 14. May 10, 2019 14DXC Proprietary and Confidential PD_9991a-19 Analytical Layer Information Layer Operational Layer Benefit Layer Ticket classification Topic-based index system Incident Ticket Handbooks NLP pipeline Automatic ontology/ topic assignment Optimized ServiceInstruction article + recommendations Solutioning support Savings Quality + Speed + Efficiency Increase Feedback loop Customer Satisfaction 50M IT tickets issued At the forefront of technology, ITSM is heavily impacted by the rapid change of the IT landscape 10% less time spent Assigning service tickets according to their identified topic to specific teams, obsoletes manual distribution. 10k pages of manuals read Handbooks for knowledge manag ment continue to be the primary resource to go to NLP >95%classification accuracy State of the art Deep Learning classification algorithms achieve highest scores in real-time Digital Assistance for services like maintenance / other services Enhance/ improve ontology/ corpus 20% more efficiency Ontologically indexed Knowledge Base articles and article recommendations boosts ticket-team productivity 15% cost savings By cutting out inefficient workflow steps through automation and efficiency gains through digital assistance 25% more satisfaction Faster ticket resolution and the increased quality leads to increased customer satisfaction Version & Release Date index System. Feedback loop
  15. 15. May 10, 2019 15DXC Proprietary and Confidential PD_9991a-19 What Clients See (The AI Market) Platform Product “Solution” Platform Product Platform Product
  16. 16. May 10, 2019 16DXC Proprietary and Confidential Enterprise-Scale Data Science Experience Industrialized AI Master Run AI experiment Perform AI Forensics Machine Learning Experience Industrialized AI Data Scientist The data science journey
  17. 17. May 10, 2019 17DXC Proprietary and Confidential Approach using Python and RASA.io Dataset Questions, Answers, Links, Tags, Importance, … e.g. mechanics. stackexchange.com Dataset Data Preprocessing From Posts.xml to a cleaned and preprocessed dataframe User Feedback Loop Machine Learning & Application Development Develop a Chatbot with Intent Recognition with the aid of Natural Language Processing & Understanding
  18. 18. DXC Proprietary and Confidential May 10, 2019 Industrializing AI
  19. 19. May 10, 2019 19DXC Proprietary and Confidential Seed Stage • Curate the idea Early Stage • Solve the problem Growth Stage • Perfect the data supply chain Maturity • Automate the infrastructure The AI Garage • Virtual meetups • Virtual Build-a-thons Industrialized Co-located Build-a-thons Focused Sprints Managed Services Industrialized Industrialized Iterations 0.X functional operational managed functional operational managed functional operational managed Iterations 1.1…1.X Iterations 2…N Give the Client an AI Startup Experience Crawl Walk Run Investment: Participation Investment: ~$100K - $400K Investment: ~$0.5M-$1M Investment: ~$5M
  20. 20. May 10, 2019 20DXC Proprietary and Confidential Industrialized AI Strategy: Use AI to Open New Innovation Capacity Genesis Custom built Product Commodity Visibility
  21. 21. May 10, 2019 21DXC Proprietary and Confidential Industrialized AI Strategy: Use AI to Open New Innovation Capacity Genesis Custom built Product Commodity Visibility Mature, stable commodities
  22. 22. May 10, 2019 22DXC Proprietary and Confidential Industrialized AI Strategy: Use AI to Open New Innovation Capacity Genesis Custom built Product Commodity Visibility Highly visible in the enterprise
  23. 23. May 10, 2019 23DXC Proprietary and Confidential Enterprise-Scale Data Science Experience Industrialized AI Master Build Utility AI Services Build data pipelines Industrialized AI Data Engineer Data Engineering Experience The data engineering journey
  24. 24. May 10, 2019 24DXC Proprietary and Confidential Data Science is OSEMN You are awesome. I am awesome. Data Science is OSEMN. OSEMN Pipeline •O —Obtaining our data •S — Scrubbing / Cleaning our data •E —Exploring / Visualizing our data will allow us to find patterns and trends •M —Modeling our data will give us our predictive power as a wizard •N —Interpreting our data
  25. 25. May 10, 2019 25DXC Proprietary and Confidential Obtain Your Data Skills Required: •Database Management •Querying Relational Databases •Retrieving Unstructured Data •Distributed Storage Extract the data into usable format
  26. 26. May 10, 2019 26DXC Proprietary and Confidential Scrubbing / Cleaning Your Data Objective: •Examine the data: understand every feature you’re working with, identify errors, missing values, and corrupt records •Clean the data: throw away, replace, and/or fill missing values/errors Skills Required: •Scripting language •Data Wrangling Tools •Distributed Processing
  27. 27. May 10, 2019 27DXC Proprietary and Confidential PD_9991a-19 Build and Manage Industrialized Data Pipelines REST API Event Queue Establish automated, continuous and secure access to source data REST API Streaming data REST API Realtime Analytics Batch data REST API File/Data store REST API Batch Analytics Data AnalyticsData Engineering Maintain a comprehensive set of data pipelines needed to create and validate actionable insight Integrate data and use automation to maintain global context Match data to expected format, structure, schema, and content We work with clients to… Enrich data with additional features (and AI insights) that increase the ability to predict target outcomes REST API
  28. 28. May 10, 2019 28DXC Proprietary and Confidential PD_9991a-19 Real-Time Data Historical Ticket Dataset Streaming Ticket Data AWS CodeBuild RASA Runtime in AWS ECS Back-End Inference Parse text, Determine intent Real-Time Data Trained NLP Model Performance MetricsBatch Data Real-time ticket intent prediction Web Application for analysis, visualization, reporting of NLP data NLP predictions AWS S3 Storage Training Set Test Set Train Generate Model, measure effectiveness AWS CloudWatch Target System Current Model AI Utility – Actual Deployment Hypothesis: We can use NLP technology to process service requests and determine the maintenance intent Ingest Data Pipeline Deploy and Secure Analyze, Design, Train, Test, Score
  29. 29. May 10, 2019 29DXC Proprietary and Confidential Exploring (Exploratory Data Analysis) Objective: •Find patterns in your data through visualizations and charts •Extract features by using statistics to identify and test significant variables Skills Required: •Python •R •Inferential statistics •Experimental Design •Data Visualization
  30. 30. May 10, 2019 30DXC Proprietary and Confidential Modeling (Machine Learning) Objective: •In-depth Analytics: create predictive models/algorithms •Evaluate and refine the model Skills Required: •Machine Learning: Supervised/Unsupervised algorithms •Evaluation methods •Machine Learning Libraries: Python (Sci-kit Learn) / R (CARET) •Linear algebra & Multivariate Calculus
  31. 31. May 10, 2019 31DXC Proprietary and Confidential Best Practice: An Incremental, Agile Approach Stakeholder commitment Hypothesis Get data Write algorithmsGenerate evidence Decide on hypothesis credibility ✓ Take an action Data science Small 4-6 week sprints Scale globally across the enterprise and adapt to fluctuating enterprise demand Map to standard concepts and make insights repeatableUse experiments to produce reliable measurable results Produce insights that can be distributed and used throughout the enterprise Data engineering
  32. 32. May 10, 2019 32DXC Proprietary and Confidential Interpreting (Data Storytelling) Objective: •Identify business insights: return back to business problem •Visualize your findings accordingly: keep it simple and priority driven •Tell a clear and actionable story: effectively communicate to non-technical audience Skills Required: •Business Domain Knowledge •Data Visualization Tools •Communication: Presenting/Speaking & Reporting/Writing
  33. 33. May 10, 2019 33DXC Proprietary and Confidential AI - 4. Industrialize your AI A. Operationalization (Managed Platform and Managed Security) Use Case: productionize Sandbox-environment B. Industrialization (AI Utility, Closed AI Loop) Use Case: End-to-end Automation and Scalability -> Example „Knowledge Management (KM) Article Prediction Mechanism” a. Reduce human effort b. Reduce incident resolution time c. Enhance knowledge management d. Enhance consistency of incident resolution Results:
  34. 34. DXC Proprietary and Confidential May 10, 2019 AI Utility Process Flow & Model Management Labeling Team Created Arthur Shlain romthe Noun Pro ect NLP for Intent Recognition 6) Determine intent Test Results 1) Parse text with NLP 2) Create Categorization Model Tags. Synonyms 3) Train Model 4) Validate Categorization Model 5) Operationalize Model 7) Route to L2 support Historical DB with questions and intent Data Scientists
  35. 35. May 10, 2019 35DXC Proprietary and Confidential PD_9991a-19 Real-Time Data Historical Ticket Dataset Streaming Ticket Data AWS CodeBuild AWS ECS (Docker) Back-End Inference Parse text, Determine intent Real-Time Data Trained NLP Model Performance MetricsBatch Data Real-time ticket intent prediction Web Application for analysis, visualization, reporting of NLP data NLP predictions AWS S3 Storage Training Set Test Set Train Generate Model, measure effectiveness AWS CloudWatch Target System Current Model A Simple NLP Pipeline using Rasa NLU Hypothesis: We can use NLP technology to process service requests and determine the maintenance intent Only this part used for the current badge pipeline: - name: "intent_featurizer_count_vectors" - name: "intent_classifier_tensorflow_embedding" intent_tokenization_flag: true intent_split_symbol: "+"
  36. 36. May 10, 2019 36DXC Proprietary and Confidential PD_9991a-19 • Make entry into the cloud–with either Amazon AWS, Microsoft Azure, IBM or HPE Helion Virtual Private Cloud (VPC)– uncomplicated and unintimidating, minimizing costly learning steps through a high-touch service approach, not widely available Why choose DXC Technology? • For production in a hybrid model, DXC advises and implements deployments with a range of options, including HPE Helion VPC, on-premises and public cloud environments. • Our breadth of expertise and methods provide options few competitors offer • Get accelerators like reference architectures and deployment automation, extended analytic capability options, blueprints and runbooks that cover the initial setup, onboarding and ongoing run with SLAs • We provide the richest standardized package in the industry • Best practices for analytic applications and data workload optimization – DXC combines the long term commitment to business intelligence (BI) and data management with access to a broad variety of real life cases. • We have proven expertise managing Hadoop, related analytic technologies and cloud native services for enterprise solutions Full service enablement Best Practices and Expertise Easy and safe setup Integration and expansion options
  37. 37. May 10, 2019 37DXC Proprietary and Confidential Enterprise-Scale Data Science Experience Industrialized AI Master Create Data Stories Run Agile Transformation Industry Consulting Experience Industrialized AI Leader Build Utility AI Services Build data pipelines Industrialized AI Data Engineer Data Engineering Experience Run AI experiment Perform AI Forensics Machine Learning Experience Industrialized AI Data Scientist DXC Industrialized AI The journey has begun Learning happens everywhere
  38. 38. May 10, 2019 38 Where are you on the journey to industrialized AI? Contact us for a free copy of the booklet
  39. 39. DXC Proprietary and Confidential Thank you.
  40. 40. DXC Proprietary and Confidential Sources: • https://blog.openai.com/better-language-models/ • https://d4mucfpksywv.cloudfront.net/better-language- models/language_models_are_unsupervised_multitask_learners.pdf • http://www.informatik.uni-oldenburg.de/~iug08/ki/Grundlagen_Starke_KI_vs._Schwache_KI.html • https://towardsdatascience.com/overfitting-vs-underfitting-a-conceptual-explanation-d94ee20ca7f9 • https://deepmind.com/blog/alphafold/ • https://towardsdatascience.com/a-beginners-guide-to-the-data-science-pipeline-a4904b2d8ad3 • https://openai.com/blog/ai-and-compute/

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