AI Overview and Capabilities
- 1. September 1 , 2018 Artificial Intelligence at PwC Overview & Capabilities
- 2. Artificial Intelligence COE AI is now approaching or surpassing human abilities to sense, think, and act in complex business environments… AI is equaling or surpassing humans in all sorts of tasks - playing games, driving cars and making recommendations Act Intelligent automation Deep question and answering Machine translation Collaborative systems Adaptive systems AI is helping us make better decisions – and doing it faster, better, more cheaply and more accurately Think Knowledge and representation Planning and Reasoning Machine Learning Deep Learning Simulation and Digital Twins AI can see, hear, speak, smell, feel, understand gestures and interface with your brain, and dream Sense Natural language Audio and speech Machine vision Navigation Visualization Accelerating Technology Big Data Open Source Cloud Computing
- 3. Artificial Intelligence COE … disrupting entire industries … Chatbots and Intelligent Agents are the new face of customer service, receiving more than $4bn in funding AI is making $ Billion dollar investment decisions for hedge funds, private equity, and institutional funds AI is better at detecting skin cancer than human dermatologists. Sense Think Act
- 4. PwC | 4 PwC's go-to-market AI strategy is organized around symbiotic teams and a comprehensive set of AI and analytics capabilities Consumer Markets Health Financial ServicesIndustrial Products al Products Tech., Media & Telco. PwC verticals New Services and Emerging Technologies PwC’s Analytics Academy Collaboration with University certificate programs to recruit and develop talent, and offer joint programs in AI Acquisitions, Alliances, and JBRs Large network of joint business relationships provides access to solutions, talent, and industry leading companies Thought Leadership PwC’s thought leadership is expansive including surveys of industry leading CEOs, publications on emerging data & analytics trends, and event hosting/participation Decision Innovation Analytics Center (DIAC) Multi-disciplinary teams consisting of data scientists and visualizers, operating in an on-shore/off-shore model Artificial Intelligence Accelerator (AIA) The AI research center consisting of teams of data scientists piloting solutions for clients using emerging AI techniques. AI Data Scientists (SMEs) Cross-sector specialists that have deep AI skills that are applied in collaboration with domain experts in each sector Analytics Apps Supplement engagement and client teams to add value efficiently during data & analytics problem solving Data Services Proprietary data sets created on a combination of public and proprietary data used in combination with PwC’s agile, global data services Insights Platforms Analytical apps that can be turned into managed services for repeated use while PwC hosts the data, computation and analysis related to AI for our clients Hub and Spoke Resource ModelResearch and Alliances Apps and Insights Platforms Digital Strategy Specialists Dedicated research specialists and strategy SMEs track a knowledge base of 265+ emerging technologies to evaluate viability and relevance for clients’ business priorities
- 5. Key focus areas in Artificial Intelligence 5 Data Eng./Model Ops Automated ML Simulation & Digital Twins Responsible AIEmbodied AI ▪ Natural Language processing and text mining ▪ Natural Language generation ▪ Chatbots and discourse understanding ▪ Sentiment & emotion analysis ▪ Speech-to-text and text-to- speech ▪ Convolutional Neural Nets ▪ Recursive Neural Nets ▪ Capsule Networks ▪ Generative Adversarial Networks ▪ Deep reinforcement learning ▪ Hybrid learning models ▪ Regression & classification ▪ Bayesian learning ▪ Probabilistic programming ▪ Anomaly detection ▪ Optimization techniques ▪ Support Vector Machines ▪ Various supervised, semi- supervised, and unsupervised techniques ▪ Big data architecture ▪ Big and Fast data ▪ Apache tools ▪ Cloud computing ▪ Cloud ML – AWS, GCP, Azure ▪ Machine Learning deployment ▪ Agent-based simulation ▪ Reinforcement learning ▪ Augmented and synthetic data generation ▪ System dynamics modeling ▪ ’Digital Twins’ ▪ Calibration of models ▪ IoT and Industrial IoT – Edge computing and Smart sensors ▪ Drone – Autonomy & Image analytics ▪ Robots – Navigation & Learning ▪ Brain-Machine Interfaces ▪ Explainable AI ▪ Beneficial AI ▪ ‘Black box’ Interpretability ▪ Maturity models ▪ Ethics and Law ▪ AI Governance ▪ AI Controls framework ▪ Automated data preparation ▪ Automated feature engineering ▪ Automated algorithm selection ▪ Automated explanation generation ▪ Meta-model inference Natural Language Machine Learning Deep Learning
- 6. DEVELOP Models development requires the need to explore a diverse set of techniques, access historic data for validation, tools to generate synthetic data, and sometimes simulation capabilities to train agents While similar to other digital assets, the A.I. lifecycle requires capabilities and technologies that are unique to building dynamic solutions LEARN Models will need to learn through feedback that comes from end users of enabled software or through domain experts that interact directly with models and teach them how to perform tasks CONSUME Model deployment must consider consumption by a variety of assets, scalability on specialized hardware and frequently redeploying models as they are updated to maintain performance A.I. LIFECYCLE
- 7. Artificial Intelligence COE PwC has been selling AI solutions since 2010 and is recognized as a global leader in AI Customer Experience Client conducted a three-day data challenge with 14 vendors providing them with 4 billion rows of customer, web, call, and workflow log data. PwC placed #1 amongst the 14 vendors Industry Disruption We designed and implemented a Trusted AI Framework for new AI risks and developed new mitigating controls, policies and guidance Risk Management We developed predictive aircraft maintenance models to reduce Delays & Cancellations – resulting in 15% reduction in delays due to maintenance, 0.9% on time performance and 25% cost reduction Cost Reduction We gamified Client’s strategy with simulation and machine learning to create a new business model for rideshare & autonomous vehicles – resulting in an $1B+ acquisition Revenue Growth We used NLP to extract adverse drug interaction from multiple unstructured data sources – increasing diagnostic accuracy by 96%; and improved cost processing saving by 35 – 45%
- 8. Artificial Intelligence COE PwC’s AI Platform Target State Citizen Developers Digital Consumers Act Sense Think Infrastructure Services Data Services + Workbench (XDP) Model Curation Model of Models Optimization Algorithm Selection Template Library Active Learning Pre- & Post- Processing Pre Processing Data Ingestion - NLP Toolkit – (DataSieve / eBrevia / Dream ) Information Extraction Summarization Document Processing Document Classification Question & Answering Translation Model Building (ModelHive) Data Engineering Data ProvenanceModel Training Model Management Model Deployment Monitoring & Feedback Model Deployment and Execution (ModelHive) DigitalLabs Key AI Building Blocks Natural Language Audio & Speech Machine Vision Visualization Machine Learning Deep Learning Planning & Reasoning Intelligent Automation Machine Translation Adaptive Systems Explainable & Responsible AI
- 9. Prepare to embrace AI with an immersion session in PwC’s innovation lab Trends. Current state. Market research. Competitor data. Insights. Hypotheses. Get immersed in everything you need to know about AI/RPA. Level set and expand your team’s thinking before tackling the work. Educate Visualize. The art of the possible. Disruption across industries. Impact of AI/RPA Tour PwC’s analytics innovation accelerator lab to see AI/RPA in action. Witness new techniques, tools, and innovative solutions Explore Create your future. Original ideas and new ways of solving problems. Brainstorm AI/RPA use cases to disrupt your core business, innovate with new services and redesign your business model Ideate The People The Innovation Process Our Environment Custom designed to foster ideation and innovation. High tech collaborative environment accelerates work in a BIG fun way. Your team of decision makers, doers, thinkers & our team of data scientists, and industry experts. INNOVATION Live to disrupt ~ Design to debate ~ Embrace new ideas 9
- 10. PwC | FS Data Analytics 10 Service Center Design Simulation Uses simulation modelling techniques to explore service center design strategies that could lower cost to serve, improve efficiency, and maintain customer experience levels Speech Recognition for Deep Learning Applies a suite of deep learning algorithms to convert call center data into text, which can then be analyzed using NLP techniques it Financial Advisor Support Uses agent-based modeling to simulate household financial security under a range of scenarios to provide advice Redefining the Personal Mobility Market Uses agent-based modeling to run over 200k strategies to create a business unit focused on ride share and driverless cars Smart Coolers Incorporates a connected network of sensors to derive valuable insights about their surroundings and activities of those within NLP for Cancer Research Uses natural language processing and question-answering systems to improve quality of patient care AI-Driven Operational Transformation Process automation, big data management architectures and machine learning algorithms to automate a highly manual adverse event detection and reporting process PwC Robotrack Real-time dashboards to track the status of robotic process automation opportunities and bot development across the firm Aerial Image Analytics for Construction Applies deep learning to images of property (e.g. cars) to automate the assessment of the damage to assets Discover the power of AI/RPA through an immersive exploration of PwC’s Analytics Innovation Accelerator pilots (examples listed to the right). Leave with your own set of actionable innovation pilots and an informed perspective on Analytics, AI, and RPA. Helping you reimagine the possible with AI & RPA 10 INNOVATION
- 11. PwC | 11 PwC’s AIA conducted innovative pilots to unlock value and insights from data sources such as audio, text, video, and IoT Medical Image Analysis: Detecting cancerous cells Audio Analysis: Extracting success metrics from calls Simulation: Analyzing go-to-market strategies
- 12. PwC | 12 PwC has published extensive intellectual capital on emerging AI trends in leading business and academic journals
- 13. PwC | 13 PwC tracks emerging trends on AI and builds relationships with rising startups to bring unique new value to clients Outside in Trends
- 14. PwC | 14 PwC partners with top universities, data providers and technology platforms to provide value to clients Educational Institutions Cross Sector Alliances Data/Research Providers Analytics Vendors
- 15. PwC | 15 Best Enterprise Application of AI Alconics Award at the AI summit for an innovative combination of simulation modeling and reinforcement learning SAP's HANA Innovation Award winner for our Digital Board Room solutions Received Folio award recognizing the best technology B-to-B editorial across the magazine industry for publication on AI strategy Jan Feb Mar Apr May JunJul Aug Sept Oct Nov Dec 2017 6-8 Mar CDAO Australia Sydney 2-4 May CAO Spring Scottsdale US 9-10 May AI Summit London 26 Jul AI Summit Hong Kong 27-28 Sept AI Summit SF - 8 Nov AI Finance Summit Zurich 5-6 Dec AI Summit New York October CAO Fall New York 27-29 Jun WEF AMNC Dalian, China 1st week of Oct AI Summit Singapore 1-2 Jun AI Expo Berlin - 4-6 Sept CDAO Melbourne 12 Jul CDAO RT, Frankfurt - PwC presented at 60+ AI events in 2017 across a range from business focused conferences to prominent research events PwC has an active presence in the AI community and is recognized as an AI leader
- 16. PwC - AI Lab - AI Lab’s Digital Services Thank you. © 2017 PwC - AI Lab. All rights reserved. Not for further distribution without the permission of PwC - AI Lab. “PwC - AI Lab” refers to the network of member firms of PricewaterhouseCoopers International Limited (PwC - AI LabIL), or, as the context requires, individual member firms of the PwC - AI Lab network. Each member firm is a separate legal entity and does not act as agent of PwC - AI LabIL or any other member firm. PwC - AI LabIL does not provide any services to clients. PwC - AI LabIL is not responsible or liable for the acts or omissions of any of its member firms nor can it control the exercise of their professional judgment or bind them in any way. No member firm is responsible or liable for the acts or omissions of any other member firm nor can it control the exercise of another member firm’s professional judgment or bind another member firm or PwC - AI LabIL in any way. Get in touch. Dr. Anand S. Rao PwC - AI Lab Global Artificial Intelligence Lead Email: anand.s.rao@PwC - AI Lab.com Twitter: @AnandSRao