BUILDING AI SCALE. Dr. Arati Deo Managing Director AI Practice Lead, India

Transcription

1 BUILDING AI SCALE Dr. Arati Deo Managing Director AI Practice Lead, India

2 WE ARE IN AN UNPRECEDENTED PERIOD OF TECHNOLOGY INNOVATION Mainframe Client-Server and PCs Web 1.0 ecommerce Web 2.0, Cloud, Mobile Artificial Intelligence IoT and Smart Machines Big Data, Analytics, Visualization Big Data, Analytics, Visualization IoT and Smart Machines Artificial Intelligence Quantum Computing Web 2.0, Cloud, Mobile Web 1.0 Ecommerce Client Server and PCs Quantum Computing Mainframe 1950 Turing Test Copyright 2018 Accenture All rights reserved. 2

3 WHAT IS ARTIFICIAL INTELLIGENCE (AI)? More natural interactions between people and machines Video Analytics Multiple Technologies that enable computers to Sense (e.g., computer vision, audio processing or sensor processing) Natural Language Processing Sensor Processing Deep Learning Robotic Process Automation Biometrics Comprehend (e.g., natural language processing or knowledge representation) Mini Bots Knowledge Representation Expert Systems Emotion Recognition Act (e.g., inference engines, predictions or expert systems) Learn and self-tune (e.g., machine learning, deep learning) Neural Networks Computer Vision Machine Learning Inference Engines Gesture Recognition Ontologies Copyright 2018 Accenture All rights reserved. 3

4 WHAT S DIFFERENT ABOUT AI SOLUTIONS More complex to debug and support Ongoing monitoring & evaluation Business Requirement to AI Problem Defn. Choice of solution is non-unique Model Deployment AI Development Lifecyle Data Collection Heavy Data Dependence New, lessunderstood technology Production Data Pipeline Model Development Probabilistic Solutions Copyright 2018 Accenture All rights reserved. 4

5 SOLUTION KEY CHARACTERISTICS Operating on volumes beyond pilot/prototype ROI proven on production volumes Volume Proven ROI Engineered for reliable operation and quality Reliable Repeatable Evolutionary Repeatable methodology for other similar solutions Enables evolution to increasing automation 5

6 BUILDING 1/5 BUSINESS-VALUE FOCUSED APPROACH #1 Strong Industry and Technology partnership to experiment and evolve the solution Conversion of business problem to the right AI problem Right use of the AI outputs in downstream processes Ongoing ROI measurement Business Value-focused Maintain a problem-first approach, find the simplest solution Leverage human-computer interactions to simplify Copyright 2018 Accenture All rights reserved. 6

7 PROCESS AUTOMATION - QUOTE AMENDMENT (HIGH LEVEL FLOW) Create Alternative quotes Sales Rep Navigates to Deal Info tab on Opportunity with Quote Seller confirms Seller feeds in the Service Level Advisor Advisor asks if the seller wants to create an alternative quotes with increased Service Level e.g. - Would you like to create alternative quotes with increased service level? Advisor identifies the opportunity related to the account and also recognizes the quotes which have identical SLs and may need same SL upgrade Create alternate quotes for all these and change SL? No Ye s Advisor creates alternate quotes for all the quotes under consideration For making changes to an individual quote advisor redirects seller to [SSQ Link] Advisor recommends the Service Level to be added or lists all the Service Levels to choose from Advisor recommends the next (logical) increased level of service based on current SL Advisor adds the new Service Level to all the quotes and confirms the creation of alternate quotes Advisor moves to the next change, if applicable Systems AI Engine SFDC SAP Quotes are on SFDC opportunity, viewable to the seller through the UI. Changes are made in the Service Level field. Copyright 2018 Accenture All rights reserved. 7

8 INDUSTRY AND TECHNOLOGY PARTNERSHIP THROUGHOUT DEVELOPMENT LIFECYCLE Ongoing monitoring & evaluation Business Requirement to AI Problem Defn. Model Deployment AI Development Lifecyle Data Collection Production Data Pipeline Model Development Copyright 2018 Accenture All rights reserved. 8

9 BUILDING 2/5 DIVERSE ECOSYSTEM FOR AI DEVELOPMENT Diverse skills employed for development #2 Partnerships with academia to deliver thought leadership and innovative solutions Community approach to team development Relationships with key technology partners and start-ups Diverse Ecosystem Copyright 2018 Accenture All rights reserved. 10

10 DIVERSE & EVOLVING ROLES FOR AI DEVELOPMENT DEDICATED SHARED AI/ML Scientist AI/ML Engineer Ai Architect Develops model design; conducts various experiments to determine best model: creates final best model Implements code and services to process data and generate desired outputs from final model in production system Builds overall framework for AI deployment, designs the architecture for AI production setup DEDICATED & SHARED Data Engineer Business Analyst Visualization Designer/Engineer AI Delivery Leads Designs and builds the data pipelines for data processing and ingestion to the AI system Contributes in converting business problem to relevant AI problem; user acceptance testing Designs and implements the new user interfaces and visualization mediums needed for AI systems Sustain AI assets and platforms; recruit AI talent; create training programs for upskilling for AI skills Copyright 2018 Accenture All rights reserved. 11

11 AI Ecosystem and partnerships AI technology radars Global alliances Accenture Investment Total # of practitioners University / Research partnerships Global Labs $600 million - including 185+ Related Patents and Applications Stanford MIT DFKI Turing institute UK Liquid Tech Labs Studio Sophia Dublin AI COE IDC Innovation Tech Labs Palo Centre Alto Copyright 2018 Accenture All rights reserved. 12

12 BUILDING 3/5 USE TECH-AGNOSTIC FRAMEWORKS #3 Develop integrated solutions that leverage best-of-breed products Create processes to continuously evaluate new technology and software solutions Technologyagnostic Copyright 2018 Accenture All rights reserved. 13

13 Technology-agnostic Architecture Framework for AI Sources Social Media Visualization Services Enterprise Systems Enterprise Systems Enterprise Smart Metering & Outage Resolution Fraud Detection Service Predictive Network Operations Service Health Advisor Re-admission Service Business Services Product Sale Prediction Service Cross Industry Services Orchestration Services AI Training System Doc Types Free Text XML XML </> Channels Natural Language Processing ACIP Feedback Service Answer Service Speech Recognition Data Transformation Data Services Custom Services OCR AI Interface Services Image Processing Data Masking Data Insights Persistence Services Data Lake Technical Services /Fax/Voice Mail AI Services AI Platforms (Azure, IBM Watson, ) AI Libraries (Python, R ) AI Platforms/Libraries Copyright 2018 Accenture All rights reserved. 14

14 CASE STUDY COMBINATION OF MULTIPLE TECHNOLOGIES Business Context The Client (an APAC Broadcasting Network) has requirement to identify new telecom poles as part of an acquisition process The project team has 18 resources are working to identify the poles manually. This incurs heavy cost and is also time consuming. Each pole is located in Google Maps manually and the type of pole (Utility Pole or Telecom Pole) is visually identified Sample Images Telecom Pole Utility Pole Solution The images are downloaded using Google Street API Automated image identification using Pattern Matching with Google s Tensor Flow Machine Learning Framework The Inception Model of Tensor Flow is based on Convolutional Neural Networks Final layers of inception model are re-trained with pole images to classify poles based on patterns Benefits Automatic identification of different types of poles (despite differences in backgrounds, angles, resolutions, distances) Over 35% automation of image classification problem for pole types (and significantly lower manual intervention) Copyright 2018 Accenture All rights reserved. 15

15 BUILDING 4/5 THINK INDUSTRIAL SOLUTION (NOT PROTOTYPE!) #4 Industrialized Development Data and technology platforms built to scale Flexible and Robust Data pipeline is crucial Industrialized services and cloud capabilities optimized for AI delivery Repeatable and sustainable development processes Copyright 2018 Accenture All rights reserved. 16

16 REPEATABLE DEVELOPMENT METHODOLOGY Program Management Solutioning Project Management Project Execution Release 1..n AI Value Targeting Confirm AI Pilot Pilot Deployment Pilot Operation Confirm Sprint Management Deploy Release Service Delivery Initiation Change Enablement Service Introduction

17 Fraud Detection Solution at Scale Courtesy: FICO Fraud Manager Copyright 2018 Accenture All rights reserved. 18

18 BUILDING 5/5 STRATEGIC CHANGE MANAGEMENT INCLUDED #5 Evolve the level of automation through incremental steps Design approach that puts humans at the center of the solution Incorporate change management plans in the development plan Involve the end users in design and measurement Strategic Change Management Copyright 2018 Accenture All rights reserved. 19

19 AUTOMATION JOURNEY Nonoptional Automation Take Responsibility and Don't Let Me or Anyone Else Mess It Up Overrideable Automation Take Responsibility Until I Tell You Otherwise Opt-In Automation Do This Task for Me Advisory Guidance Help Me as I Go Give Me a Suggestion Specific Information Give Me the Facts General Information Courtesy: Gartner Copyright 2018 Accenture All rights reserved. 20

20 AUTOMATION THRESHOLD TO OPTIMIZE BUSINESS VALUE Automation Threshold Source: Internet Copyright 2018 Accenture All rights reserved. 21

21 BUILDING RECAP #1 #2 #3 #4 #5 Business Value-focused Diverse Ecosystem Technologyagnostic Industrialized Development Strategic Change Management Volume Proven ROI Reliable Repeatable Evolution -ary SCALE Copyright 2018 Accenture All rights reserved. 22

22 QUESTIONS Contact me at Copyright 2018 Accenture All rights reserved. 23

23 Thank You