Cognitive Computing: Trends to Watch in 2016

© 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Cognitive Computing
Increased activity from early adopters, startups, and vendors
IBM HorizonWatch 2016 Trend Report – External Version
Honor Sherlock, Senior Advisor, IBM Watson, Market Development
Bill Chamberlin, bluemine Product Manager, HorizonWatch
March 4, 2016

About This Trend Report
2 04March2016 HorizonWatch Trend Report: Cognitive Computing (External Version)
 Purpose: The slides provide an overview on the Cognitive Computing trend for IBM
clients and external stakeholders
 Content: Summary information about the Cognitive Computing trend is provided along
with many links to additional resources.
 How To Use This Report: This report is best read/studied and used as a learning
document. You may want to view the slides in slideshow mode so you can easily follow
the links
 Available on Slideshare: This presentation (and other HorizonWatch Trend Reports for
2015) will be available publically on Slideshare at
http://www.slideshare.net/horizonwatching
 Please Note: This report is based on internal IBM analysis and is not meant to be a
statement of direction by IBM nor is IBM committing to any particular technology or
solution.

Welcome to the Cognitive Era and the rise of Cognitive Business
IBM: Welcome to the Cognitive EraWe are entering a new era of computing called
cognitive computing. It signifies a fundamental
shift in how machines interact with us, other
machines and the environment. It will provide
much value, but it will be highly disruptive.
The Cognitive Era will result in entirely new
model of computing that includes a range of
technology innovations in analytics, natural
language processing and machine learning
“Over time, it will be possible to build cognitive
technologies into many of the IT solutions and
human-designed systems on earth, imbuing
them with a kind of “thinking” ability. These new
capabilities will enable people and organizations
to accomplish things they couldn’t before–
understanding more deeply how the world
works, predicting the consequences of actions,
and making better decisions.” IBM
IBM: The Rise of Cognitive Business

The Cognitive Era is not prediction of a future time period, it has
already begun
Frost & Sullivan: Future Applications of
Cognitive Intelligence
“The numbers in the new AI field are staggering:
more than 2,300 startups (a comprehensive list
can be found here) have been founded; venture
capitalists are investing billions of dollars.”
Forrester
“Smart machines are not future fantasy; they are
commercially available. According to Gartner’s
analysis of external sources, more than $10
billion have already been purchased through
more than 2,500 technology companies.” Gartner
“IDC expects the overall market to grow
significantly in the 2015–2019 forecast period, at
a CAGR of approaching 35%.” IDC

Cognitive Computing – Trend Overview
Drivers
 Advances in enabling technology areas
 Increasingly large complex datasets that can be the source of major
insights and hold the answers to critical questions
 Third computing platform – Cloud, Mobile, Big Data, Analytics, Social
 Data economy
Challenges
 Much more work on enabling technologies required
 Impact on business applications and processes not yet fully understood
 Education / Concerns about impact on jobs
 Window of Opportunity: Partnerships / Ecosystems
Implications
 This is a technology that learns. Accuracy will increase over time.
 First movers will have an advantage.
 Cognitive systems and services will be available via cloud delivered
services and therefore, cognitive capability will be delivered via any
mobile device
 It is technology directed at helping individuals, not departments. Thus
expect a mass market to develop around consumers.
 Business processes and whole industries will be transformed.
 Changes will be required in employee workforce, corporate culture, and
partner ecosystems.
 New IT architectures, systems design, data management/analytics and
workload optimized systems.
 Scenario planning needed to understand long term implications for mass
displacement of white collar knowledge workers.
“Artificial Intelligence could automate
close to 50% of jobs in the Western
world within the next two decades.”
Frost & Sullivan
“By 2018, 40 percent of outsourced
services will leverage smart machine
technologies, rendering the offshore
model obsolete for competitive
advantage.” Gartner
“By 2018 half of all consumers will
interact with services based on cognitive
computing on a regular basis.” IDC
IBM: The Future of Cognitive
Computing (video)

In 2016, cognitive platform providers will target the developer
community with an increasing volume of APIs to build scale.
 Cognitive platform providers target the developer
community. To jump-start cognitive computing
monetization, leading cognitive technology providers will
make their assets available to developers as APIs, with
the goal of seeding creation of “killer apps” that rely on
cognitive-enabled backbones.
– Cognitive development platforms: Developers will look for
cognitive computing vendors that can provide powerful and
simple development tools & platforms
– APIs: Developers want access to new APIs designed to help
accelerate innovation and the commercialization of cognitive
technologies.
 Integrating Cognitive systems with cloud, mobile, and
IoT systems. Look for development platforms and
offerings that integrate cognitive computing capabilities
with other offerings. IBM’s launch of an integrated
Watson IoT unit will prompt other competitors to
undertake similar initiatives in 2016, focusing on
launching solutions, tools and assets that capitalize on
the intersection of cognitive computing and other
disruptive technologies such as IoT, digital and cloud.
Source: MD&I HorizonWatch / TBR Inc.,
IBM DeveloperWorks Cognitive
Computing
“By 2018, over 50% of developer teams
will embed cognitive services in their apps
(vs. 1% today), providing U.S. enterprises
$60+ billion annual savings by 2020.” IDC
“By 2018, 20 percent of business content
will be authored by machines.” Gartner
“In order to manage and make sense of
the data that connected assets generate,
cognitive systems and machine learning
will play a fundamental role for the
evolution of IoT.” Forrester

In 2016, leading enterprises will aggressively build strategies to
adopt cognitive solutions
• Early use cases: Cognitive has the ability to break down
complex, disparate data environments and answer strategic
questions
• Professional Services. Enterprises will require consulting and
implementation support to develop cognitive road maps and
integrate complex data & analytics architectures. As a result,
services will compose the majority of spending through 2020.
• Third platform integration unlocks value: Cognitive
computing is optimized on a secure cloud-based and mobile-
enabled business platform, with an Internet of Things (IoT)
driven big data backbone for data capture, storage and
analysis.
• Data economy: Leading enterprises will focus on acquiring
and harvesting proprietary data feeds to train cognitive systems.
 Embedding cognitive technologies: Enterprises explore
embedding the technology into existing products, solutions and
services.
 Customer experience as a use case. Customers continue to
demand more personalized, contextually relevant experiences.
Organizations will evaluate cognitive computing as a way to
optimize the customer experience.
Indicators of 2016 Cognitive
Computing Adoption
1. Increasing cognitive computing
participation by technology vendors
2. Expanding volume of cognitive
computing case studies
3. Advances in cognitive development
tools and applications
4. Expansion of cognitive computing
API ecosystems
5. Emergence of cognitive
professionals and supporting
professional communities
TBR
“Smart machines deliver substantial
first-mover advantage and we
recommend early action.” Gartner

R&D advancements will continue in areas such as machine learning.
NLP, pattern recognition, reasoning and scheduling
 Advancements in machine learning feed off access to
IoT-generated data. As the IoT generates more real-time,
machine learning algorithms will use that data for planning,
forecasting and making critical business decisions.
 Natural language processing (NLP) sweet spot is
customer service. Enterprises use NLP-based solutions to
handle customer service inquiries without human interaction,
improving overall efficiencies and costs.
 Rich media & IoT analytics fuel pattern recognition
advancements. Combining historical and traditional data
with real time rich media & IoT unstructured data will reveal
new patterns in data that can inform future decision
processes.
 Knowledge representation and reasoning efforts focus
on supporting decision making. Look for efforts to build
large-scale knowledge databases that cognitive systems can
use to drive unbiased support for subject-matter experts.
 IoT data leads to smarter scheduling and planning. Real
time data from IoT sensors assists cognitive systems with the
job of advanced scheduling and planning applications.
Example: Leveraging weather data to help optimize
transportation and supply chain logistics.
“Through 2020, the smart machine era will
blossom with a proliferation of contextually
aware, intelligent personal assistants, smart
advisors (such as IBM Watson), advanced
global industrial systems and public
availability of early examples of autonomous
vehicles.” Gartner
IBM Research
“Technology companies and researchers
across the world have now set an ambitious
goal of developing Artificial Intelligence
solutions that are not just intelligent in terms
of decisions taken, but can also learn from
data - like humans do.” Frost & Sullivan

Cognitive computing offers predictive and personalized capabilities to
address business outcomes across core verticals
 Healthcare: The healthcare industry, driven by a push for
improved management, coordination and delivery of patient-
centric outcomes, offers continuous opportunities for cognitive
computing. Cognitive computing can analyze gigabytes of
medical information to formalize a specific treatment plan for
each patient.
 Banking and financial services: Cognitive computing allows
banking, financial services and insurance companies to analyze
gigabytes of data and recognize risks that were previously
ignored due to a lack of available analytics tools and platforms.
 Energy & Utilities: Cognitive computing solutions can support
multiple use cases in energy and utilities. For example,
cognitive computing can analyze information from sensor
networks, local weather stations, sky cameras and satellites to
more accurately predict weather patterns, enabling utilities to
more efficiently use their energy reserves.
 Manufacturing: Manufacturers will be able to adapt their
production cycles to more closely align to customers’ needs,
patterns and behaviors. By analyzing production changes
through cognitive computing, manufacturers can alter
production output and create a more homogeneous supply
chain.
“To improve efficiency and optimize
business outcomes, government agencies
are experimenting with smart machine
technologies, such as virtual assistants, to
deliver frontline services,.” Gartner
KMWorld: Cognitive Computing: Real-world
applications for an emerging technology
“Watson’s potential lies in its ability to
understand, reason and learn. Companies
will use this cognitive ability to build real
value when they can predict outcomes and
take actions to change them.” Gartner

Challenges: the relative nascence of cognitive computing demands
ROI proof points and careful selection of appropriate use cases
 Safeguards needed against data overreach and
abuse. Cognitive systems will rely heavily on data
derived from multiple systems and sources. As
such, it is important to ensure data is consolidated
and sourced in a consistent, secure manner.
 Where is the business value and ROI? Given its
nascence in the enterprise, limited case studies
exist for cognitive computing, creating potential
hurdles to large-scale investment.
 Lack of industry definitions and standards.
Similar to other emerging areas, the lack of
industry standards and definitions around cognitive
computing may create hesitation in adoption,
particularly in heavily regulated industries and the
public sector.
 Limitations of current technology. While there
are important reasons to move forward with
cognitive technology, firms must consider the
constraints of existing platforms relative to their
ultimate goals.
.
“Based on lessons learned from subject
matter experts (SMEs) who have led
early cognitive computing solution
implementations, we have identified three
keys to a successful implementation, as
well as four recommended steps for kick-
starting and accelerating your
organization’s cognitive journey.” IBM:
Your Cognitive Future
“By 2018, 45 percent of the fastest-growing
companies will have fewer employees than
instances of smart machines.” Gartner
“The smart machine era will be the most
disruptive in the history of IT.” Gartner

Activity in the cognitive computing vendor ecosystem is expected to
heat up in 2016
 Ecosystem activity builds: In 2016, the vendor
ecosystem become even more active. Startups
continue to enter the fray and existing players will
aggressively build cognitive expertise and assets
through selective hiring and targeted acquisitions.
 Targeting developers: To accelerate innovation and
monetize assets, platform players will increasingly
target development communities.
 New APIs and development platforms: Vendors
focus on accelerating innovation and the
commercialization of cognitive technologies.
 Acquisitions accelerate. Market players aim to
augment embedded cognitive capabilities as well as roll
out new cognitive-centric solutions by acquiring niche-
focused cognitive startups.
 Intersection of Cognitive Computing with IoT,
Cloud, and Digital. Vendors focus on launching
solutions, tools and assets that capitalize on the
intersection of cognitive computing and other disruptive
technologies such as IoT, digital and cloud.
IBM
“Unstructured and semistructured data
is fueling a renaissance in the handling
and analysis of information, resulting in
a new generation of tools and
capabilities that promise to offer
intelligent assistance, advice, and
recommendations to consumers and
knowledge workers around the world”
IDC

APPENDIX
Cognitive Computing Resources

Selected public-facing analyst websites and resources
 Forrester: Artificial Intelligence (blogs) and Cognitive
Computing (search)
 Frost & Sullivan: Artificial Intelligence (search)
 Artificial Intelligence -- Emerging Trends and Applications
(Technical Insights)
 Gartner: Smart Machines (search) and Machine
Learning
 IDC: Intelligent Systems (search) and Machine
Learning and Cognitive Computing
 MarketsandMarkets: Cognitive Computing
 Ovum: Cognitive Computing (search) and Artificial
Intelligence
“The main driver for global cognitive computing market is increasing trend of large and complex data-set.
This complex data is available in various form such images, video, and natural language. These data-sets
cannot be processed with help of existing big data analytics systems, hence business organizations are
turning their heads towards the cognitive computing.” MarketsandMarkets
“Smart machines are no
longer science-fiction; they are
here, being used by
businesses right now and only
growing in capabilities. The
disruption they will cause over
the next decade will leave no
industry untouched.” Gartner

Selected technology vendor & consultant websites
 Accenture: Artificial Intelligence coming of age
 Alibaba: DT PAI
 Amazon: Mechanical Turk
 Apple Siri
 Deloitte: Deloitte University Press
 Google: Google Now / Artificial Intelligence and Machine
Learning / Machine Intelligence / Natural Language
Processing / Human-Computer Interaction and Visualization
 IBM Research: Cognitive Computing
 IBM Watson
 Microsoft: Machine Learning / Artificial Intelligence /
Machine Learning, Natural Language Systems and
Applications / Deep Learning Technology Center / Top
Authors in Artificial Intelligence
 Oracle: Advanced Analytics
 SAS: Machine Learning
 Wipro: HOLMES
IBM Research: Cognitive Computing
“Cognitive technologies are
delivering measurable value to
enterprises across multiple
industries. Now is the time to
engage these technologies and to
frame how best your organization
will capture the value these
technologies are creating.” Deloitte

Selected media websites
 CIO.com Artificial Intelligence (search) / IBM Watson (search)
 ComputerWorld Artificial Intelligence (search) / IBM Watson (search)
 DataVersity Cognitive Computing
 eWeek Cognitive Computing (search) / Artificial Intelligence (search)
 Forbes Cognitive Computing (search) / Artificial Intelligence (search)
 GIGAOM Artificial Intelligence (search
 HBR.org Cognitive Computing (search) / Artificial Intelligence
(search)
 InformationWeek Cognitive Computing (search) / Artificial
Intelligence (search)
 InfoWorld Cognitive Computing (search) / Artificial Intelligence
(search):
 Wired Artificial Intelligence (search) / IBM Watson (search)
“Artificial intelligence suffered a long
winter, but a new name -- cognitive
computing -- and a flood of data,
innovation, and compute power now
has thousands smart applications
flourishing.” Infoworld: It's springtime at last
for cognitive computing
“The opportunities for cognitive
computing are compelling.
Organizations that move forward
with this innovative capability will
have the opportunity to push new
boundaries for growth and gain
advantage over their competition..”
Forbes: Four Steps To Get Started With
Cognitive Computing

Selected IBM websites
 Watson Internet of Things
 IBM Watson
 What is Watson?
 Watson Developer Cloud
 Watson Engagement Advisor
 Watson Explorer
 Watson Discovery Advisor
 Watson for Oncology
 Watson for Clinical Trial Matching
 Watson Knowledge Studio
 Watson Ecosystem
 Watson University
 Watson in Healthcare
 Watson Blog
 IBM Research: Cognitive Computing / DeepQA
White paper: Computing, cognition
and the future of knowing
• Watch: November 2015 Cognitive Colloquium at
Rensselaer Polytechnic Institute
• Watch: October 2015 Cognitive Colloquium at
University of California-San Francisco
IBM DeveloperWorks Cognitive Computing

Selected IBM social media resources
 Twitter: @ibmwatson (99.4k followers) Hashtags #ibmwatson
 Linkedin: Watson Advocates
 Facebook: IBM Watson (72k likes)
 YouTube: IBMWatsonSolutions
 Watson in Healthcare
 Watson Ecosystem Partners
 What is the Watson Ecosystem?
 What Does Watson Do?
 Pinterest: Watson
 Slideshare.net search for IBM Watson
 Blogs
 Watson Blog
 Building a Smarter Planet
 Dharmendra S Modha's Cognitive Computing Blog
Twitter: @ibmwatson
Blog: Watson Blog

Selected links to additional articles and resources
 About Tech: 5 Applications of Natural Language Processing Technology
 Accenture: Turning cognitive computing into business value and AI coming of age— disruption,
transformation straight ahead
 Bloomberg Business: Why 2015 Was a Breakthrough Year in Artificial Intelligence
 CognitiveScale: CS & Deloitte Join Forces to Drive Consumer Centric Healthcare
 Deloitte: Demystifying artificial intelligence and Transforming business with technology
 Enterra Solutions: Making Sense of Cognitive Computing
 InformationAge: Man and machine: Cognitive computing in the enterprise
 KnowledgeAnywhere: Cognitive Computing & Corporate Learning?
 KM World: Cognitive Computing: Real-world applications
 Microsoft Azure: Introduction to machine learning on Microsoft Azure and Announcing Cortana Analytics
Suite and New Partner Investments
 PR Newswire: Cognitive Computing - $13.7 Billion Globally, by 2020
 PC World: IBM, Deloitte bring big data to risk management
 TechEmergence: 3 Machine Learning Trends That Are Transforming Industries
 Thoughts On Cloud: APIs: Building blocks for creating a cognitive business strategy
 ZD Net: Facebook open sources AI tools, possibly turbo charges deep learning
18 04March2016 HorizonWatch Trend Report: Cognitive Computing (External Version) Prepared by: TBR, Inc

Some related definitions found on Wikipedia
 “A cognitive computer combines artificial intelligence and machine-learning algorithms, in an approach
which attempts to reproduce the behavior of the human brain.” Wikipedia
 “Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the
academic field of study which studies how to create computers and computer software that are capable of
intelligent behavior. .” Wikipedia
 “Machine learning explores the study and construction of algorithms that can learn from and make
predictions on data.” Wikipedia
 “In artificial intelligence, an intelligent agent (IA) is an autonomous entity which observes through
sensors and acts upon an environment using actuators (i.e. it is an agent) and directs its activity towards
achieving goals (i.e. it is rational).” Wikipedia
 “Human–computer interaction (HCI) researches the design and use of computer technology, focusing
particularly on the interfaces between people (users) and computers.” Wikipedia
 “Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics
concerned with the interactions between computers and human (natural) languages.” Wikipedia
 “Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-
level abstractions in data by using multiple processing layers with complex structures, or otherwise
composed of multiple non-linear transformations.” Wikipedia
 “Pattern recognition is a branch of machine learning that focuses on the recognition of patterns and
regularities in data, although it is in some cases considered to be nearly synonymous with machine
learning.” Wikipedia

More Insights on Technology Trends are Available
20
Other slide decks in this IBM HorizonWatch 2016 Trend Report series have been
posted to Slideshare
You are also invited to check out the following IBM websites and resources
– IBM Academy of Technology
– IBM Center for Applied Insights
– IBM Institute for Business Value
– IBM Research and Research News and 5 in 5
– IBM’s THINK blog
04March2016 HorizonWatch Trend Report: Cognitive Computing (External Version)

Cognitive Computing: Trends to Watch in 2016

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