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.

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

17. Rogers Diffusion Model

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