Artificial Intelligence: Natural Language Processing
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This document provides an overview of natural language processing (NLP) through a presentation. It defines NLP and its subfields. NLP allows computers to analyze, understand, and generate human language. The presentation discusses how NLP is used in commercial applications and emerging technologies. It outlines Rogers' characteristics of innovation diffusion and shows where NLP currently sits on the technology S-curve. The summary is that AI and NLP will transform many industries through applications involving user interfaces, actions, analytics, and machine-human interactions.
Artificial Intelligence: Natural Language Processing
- 1. NATURAL LANGUAGE PROCESSING Emerging Technology Presentation Presentation by: Frank Cunha III, AIA (January 2018)
- 2. 1. Introduction 2. Disruptive Innovation Theory 3. Innovation Attributes 4. Technology S-Curve 5. Technology Diffusion 6. Summary 7. Questions Overview
- 3. 1. What is A.I.? 2. What is N.L.P.? Introduction
- 4. What is NLP? Definition: Computers use (analyze, understand, generate) natural language • A subfield of Artificial Intelligence AI • An interdisciplinary subject Major areas of research and development • Text Processing • Speech Processing Why NLP? • Huge amounts of data • Applications for processing large amounts of texts require NLP expertise
- 5. NLP in the Commercial World
- 6. More about NLP? NLP NLG NLU Natural Language Processing is computers reading language Natural Language Generation is computers writing language. Natural Language Understanding is computers understanding language. e.g. Siri & Amazon Alexa.
- 7. What is Disruptive Innovation? • Simpler • Affordable • Lower margins • First commercialized in emerging or insignificant markets
- 8. Artificial Intelligence (AI) Everywhere Gartner Hype Cycle for Emerging Technologies, 2017
- 9. Rogers’ Characteristics of Innovation “In general, innovations that are perceived as having relative advantages, being more compatible, less complex, observable, and trialable will diffuse more rapidly than other.” – The Open University
- 10. Examples: Siri, Amazon Alexa Checklist: 1. Is it cheaper to make and buy? Does it provide something previously not possible? Does it offer more features? 2. Is the innovation compatible with the experiences, values and needs of its potential buyers? 3. Is it easier to use, or is reliable and safe? 4. Is it easier for potential buyers to see the innovation being used? 5. Is it to be able to try innovations before buying?
- 11. Technology S-Curves 1. Phases of Technology Cycle 2. Fluid to Dominant
- 12. Maturity Maturity Growth Disruption Embryonic Embryonic Growth Performance Time Technology S-Curves
- 13. Where is NLP Right Now?
- 14. Fluid to Dominant 30% There is no defined business case 27% Not clear what AI can be used for 23% Don’t have the required skills 20% Need to invest in modernizing data management platform first
- 15. Technology Diffusion 1. Who is the Market 2. Roger’s Diffusion Model 3. Crossing the Chasm
- 16. Who is the Market? Autonomous Vehicles Healthcare Social Media & News Banking, Security Learning & Education People & Culture
- 18. Natural Language Processing Autonomous Vehicles Healthcare Social Media & News Banking & Security Learning & Education People & Culture Voice Recognition; Voice Commands Deep Learning & Data Mining; Access Client Information Machine-Human Interactions Data mining, Better first response time How we access information How we transcribe information & communicate and interact with one another Impact by Market Sector
- 19. Crossing the Chasm 1. Must take root in one of the other major emerging technologies to prove itself viable 2. Innovations in one area will cascade out across multiple industries and spread Natural Language Processing
- 20. Summary • AI will transform the way will live • AI is part of all/most other Emerging Technologies • NLP will enable AI to Mesh: Maximizing and optimizing the dynamic connections of people, processes, applications, technologies and devices • Collaboration of things (IoT) • Applications: • User interface • Actions • Business Analytics • Industries: • Healthcare, Education, Banking, Security, Autonomous Devices/Machines, etc.
- 21. Questions
- 22. Sources 1 Hype Cycle for Artificial Intelligence, 2017 2 Wikipedia (NLP) 3 What is the Role of Natural Language Processing in Healthcare? 4 What is the Role of Natural Language Processing in Healthcare? 5 How Has Natural Language Processing Technology Changed Healthcare? 6 Computer-assisted coding and natural language processing 7 Humans and systems: Creating natural interfaces to augment human ability 8 3 Reasons Why AI Will Boost US Productivity by 35% by 2035 9 Why Artificial Intelligence is the Future of Growth”-- 10 Global Economic Impacts Associated with Artificial Intelligence 11 Natural Language Processing Projects & Startups To Watch In 2018 03/31/2017|In Technology Industry Trends 12 Applications of Natural Language Processing that you Should Consider for your Business in 2018 by Valeryia 13 Health IT experts discuss how they're using NLP in healthcare 14 https://www.forbes.com/sites/gilpress/2017/01/23/top-10-hot-artificial-intelligence-ai-technologies/#7647c4c11928 15 Deep Learning for NLP, advancements and trends in 2017 16 https://www.attivio.com/company/about-attivio 17 https://automatedinsights.com/alexa 18 https://www.cambridgesemantics.com/category/webinars/ 19 http://www.digitalreasoning.com/visionary-approach/more-human 20 https://lucidworks.com/vision/ 21 https://narrativescience.com/Resources/Resource-Library/Blog 22 https://www.sas.com/en_us/search.html?q=NLP 23 Top 10 Hot Artificial Intelligence (AI) Technologies 24 The 5 Customer Segments of Technology Adoption 25 Overview of Artificial Intelligence and Natural Language Processing 26 Natural Language Processing Market Trends 27 Natural Language Processing Market to Reach $22.3 Billion by 2025 28 https://www.accenture.com/t20160814T215515Z__w__/gb-en/_acnmedia/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Technology_11/Accenture-Turning- Artificial-Intelligence-into-Business-Value.pdf#zoom=50 29 http://www.claytonchristensen.com/key-concepts/ 30 https://www2.deloitte.com/insights/us/en/focus/cognitive-technologies/what-is-cognitive-technology.html