Cognitive future part 1

Your cognitive future
How next-gen computing changes the way we live and work IBM Institute for Business Value
Part I: The evolution of cognitive

IBM Watson
Watson is a cognitive system that enables a new
partnership between people and computers that
enhances and scales human expertise. For more
information about IBM’s Watson, visit ibm.com/watson
IBM Strategy & Analytics
The IBM Strategy and Analytics practice integrates
management consulting expertise with the science of
analytics to enable leading organizations to succeed.
For more information about IBM Strategy & Analytics
offerings from IBM, visit ibm.com/services/us/gbs/
strategy
Executive Report
Watson and Strategy & Analytics

Executive summary
For decades, science fiction visionaries have shared their renditions of intelligent machines
and computers that could learn and function as humans. Intelligent machines have since
moved beyond the lore of science fiction; today, they are a reality thanks to breakthroughs in
cognitive computing. Cognitive computing is here – and this innovative capability is becoming
ubiquitous in our everyday lives and fundamentally changing how we perform our jobs,
engage and interact with others, learn and make decisions. Pioneering organizations across
industries and around the world are already leveraging its capabilities to realize significant
business value and help solve some of society’s greatest challenges.
We are entering a new era of computing. Following the programmable and tabulating systems
eras, cognitive computing represents a huge leap forward. This new era brings with it
fundamental differences in how systems are built and interact with humans.
In the programmable systems era, humans do most of the directing. Traditional
programmable systems are fed data and their results are based on processing that is pre-
programmed by humans. The cognitive era on the other hand is about thinking itself – how we
gather information, access it and make decisions. Cognitive-based systems build knowledge
and learn, understand natural language, and reason and interact more naturally with human
beings than traditional programmable systems. The term “reasoning” refers to how cognitive
systems demonstrate insights that are very similar to those of humans.
Why cognitive should be on
your radar
Organizations have just begun to scratch the surface
of cognitive computing capabilities. From improving
customer engagement to enhancing research
capabilities that identify new life-saving medical
treatments, the potential value is boundless. Through
our research, we uncover multiple innovative
opportunities across industries, creating chances for
early adopters to achieve a substantial first-mover
advantage. WinterGreen Research estimates the
global healthcare decision support market alone will
increase to more than $200 billion by 2019 as a result
of new cognitive computing technologies.1
COG · NI · TIVE / käg-nə-tiv
(adjective): of, relating to or involving conscious mental activities
(such as thinking, understanding, learning and remembering)
1

Cognitive systems are able to put content into context, providing confidence-weighted
responses, with supporting evidence. They are also able to quickly find the proverbial needle
in a haystack, identifying new patterns and insights. Over time, cognitive systems will simulate
even more closely how the brain actually works.2
In doing so, they could help us solve the
world’s most complex problems by penetrating the complexity of big data and exploiting the
power of natural language processing and machine learning.
While tremendous advancements have been made over the past 50 years, cognitive
computing is virtually in its infancy in terms of how this exciting technology could potentially
evolve. Adopting and integrating cognitive solutions into an organization is a journey and not a
destination. Therefore, organizations need to set realistic expectations and develop long-term
plans with incremental milestones to benefit from the technology’s future progression. Based
on experience with clients and extensive research, we have identified multiple opportunities
across industries for innovative application of cognitive computing today, as well as examined
how the technology might evolve in the future.
In this, the first in a series of reports based on the IBM Your cognitive future research study, we
explore three capability areas for cognitive computing. We also discuss how future
opportunities will be influenced by the evolution of cognitive computing capabilities, such as
advancements in machine learning techniques, and how adoption will be impacted by
multiple forces, from societal views to policies and skills. In the second report, we will explore
lessons learned from pioneering early adopters and provide insights on how you can prepare
to take advantage of cognitive computing solutions.
Threeareas of cognitive capability are directly
related to the ways people think and work.
Six forces will determine adoption and
advancement rates for cognitive computing.
Five key dimensions will impact the robustness
of future cognitive capabilities.
So what does cognitive computing do?
Cognitive computing…
• Accelerates, enhances and scales human
expertise
• Captures the expertise of top performers
– and accelerates the development of
expertise in others
• Enhances the cognitive process of
professionals to help improve decision making
in the moment
• Scales expertise by quickly elevating the
quality and consistency of decision making
across an organization.
2 Our cognitive future

The three capability areas for cognitive
We see three broad areas of capability for cognitive systems. Opening new doors for
innovations, these capability areas directly relate to the ways people think and work and
demonstrate increasing levels of cognitive capability. Significant progress has been made
across each of these capability areas, and opportunities for future evolutions of capability
look promising, as they continue to gain momentum in a number of industries.3
It is important
to note that these capabilities are not mutually exclusive. A specific business solution may in
fact leverage one or more of these capability areas.
“The current capabilities of cognitive
computing are just the beginning of
what can be.”
Dr. Manuela Veloso, Professor of Computer Science,
Carnegie Mellon University
Decision
Discovery
Source: IBM Institute for Business Value analysis.
Figure 1
There are three emerging capability areas for cognitive computing
Engagement
Cognitive computing capabilities
3

Engagement – These systems fundamentally change the way humans and systems
interact and significantly extend the capabilities of humans by leveraging their ability
to provide expert assistance and to understand. These systems provide expert
assistance by developing deep domain insights and bringing this information to
people in a timely, natural and usable way. Here, cognitive systems play the role of an
assistant – albeit one who is tireless, can consume vast amounts of structured and
unstructured information, can reconcile ambiguous and even self-contradictory data,
and can learn. In this partnership, the two – human and machine – are more effective
than either one alone.
Much like the human brain, these systems begin to build models of themselves and
the world around them. This world consists of the system itself, the knowledge
ingested from information corpora and the users of the system. The models include
the contextual relationships between various entities in a system’s world that enable it
to form hypotheses and arguments. As a result, these systems are able to engage in
deep dialogue with humans. Significant and proven capabilities have been built
around this capability area.In the future, increasingly more domain-specific question
and answer (QA) systems are expected to emerge. Many of them are likely to be
pre-trained with domain knowledge for quick adoption in different business-specific
applications. Additionally, future cognitive systems will advance to have free form
dialogue and reasoning capabilities.4
(See Case study: Leveraging cognitive
computing to assist military members in transitioning to civilian life.)

Case study
Leveraging cognitive computing to assist military members in transitioning to
civilian life
USAA, a financial services company, provides banking and insurance services to 10.4 million
past and present members of the U.S. Armed Forces and their immediate family members,
including veterans making the often difficult transition from military to civilian life. Like any
career change, moving from a military to a civilian career presents challenges to members
and their families. The process can be complex and intimidating as many do not know which
questions to ask and concepts to consider in making the transition. To better service these
customers, USAA has implemented an innovative cognitive computing solution leveraging
IBM’s Watson.
This solution allows transitioning military members to visit usaa.com or use a mobile browser
to ask questions specific to leaving the military, such as “Can I be in the reserve and collect
veterans compensation benefits?” or “How do I make the most of the Post-9/11 GI Bill?”
Starting with 2,000 questions, a team spent more than six months training and educating the
system. In addition, the solution analyzed and understands more than 3,000 specialized
military transition documents. The system’s natural language processing allows it to
understand real questions asked in diverse ways and provide expert advice directly to
customers. As a result, USAA is able to provide customers comprehensive answers to
complex questions in a non-judgmental environmental.5
5

Decision – These systems have decision-making capabilities. Decisions made by cognitive
systems are evidence-based and continually evolve based on new information, outcomes and
actions. Decisions made by these systems are also bias free; however, certain standards are
required for humans to fully trust their decisions. Currently, cognitive computing systems
perform more as advisors by suggesting a set of options to human users, who ultimately
make the final decisions. (See Case study: Cognitive computing solution helps support
decision making for improved patient care.) Confidence in a cognitive system’s ability to make
decisions autonomously depends on the ability to query and have traceability to audit why a
particular decision was made, as well as improved confidence scores of a system’s
responses. A confidence score is the quantitative value produced by a system representing
the merit of a decision after evaluating multiple options.6
Discovery – Discovery is the epitome of cognitive capability. These systems can discover
insights that perhaps could not be discovered by even the most brilliant human beings.
Discovery involves finding insights and connections and understanding the vast amounts of
information available around the world. With ever-increasing volumes of data, there is a clear
need for systems that help exploit information more effectively than humans could on their
own.7
While still in the early stages, some discovery capabilities have already emerged, and
the value propositions for future applications are compelling. Advances in this capability area
have been made in specific domains, such as medical research, where robust corpora of
information exist.8
(See Case study: Cognitive computing solution supports new discoveries
and insights in medical research.)

Case study
Cognitive computing solution helps support decision making for improved patient care
WellPoint, Inc., one of the largest health benefits companies in the United States, delivers a
number of health benefit solutions through its networks nationwide. Utilization management
nurses spend 40 to 60 percent of their time aggregating information that is faxed or mailed to
them to decide whether requests for procedures should be approved or denied based on
evidence-based medicine and WellPoint medical policies. For complex decisions, patients
can often wait weeks for the clinical review to occur, and a lack of available evidence or the
ability to process in a timely fashion can delay treatment or lead to errors. Also, it is extremely
challenging for medical professionals to keep up with the rapid advancements in medical
knowledge.
To address these challenges, WellPoint implemented a cognitive computing solution powered
by IBM’s Watson that provides decision support for the pre-authorization process. The
solution bases recommendations on its ability to interpret meaning and analyze queries in the
context of complex medical data and human and natural language, including doctors’ notes,
patient records, medical annotations and clinical feedback. As the solution learns, it becomes
increasingly more accurate. Even if nurses have to do additional research on a request,
Watson’s ability to aggregate the information and present it to them in a readable, structured
format saves a lot of time. Providing decision support capabilities and reducing paperwork
allows clinicians to spend more time with patients.9
7

Case study
Cognitive computing solution supports new discoveries and insights in
medical research
Baylor College of Medicine, a leading health sciences university, is constantly looking for
innovative approaches to advance and accelerate medical research. The time needed for
research professionals to test hypotheses and formulate conclusions currently ranges from
days to years. A typical researcher reads about 23 scientific papers per month, making it
humanly impossible to keep up with the ever-growing body of scientific material available.
Biologists and data scientists at Baylor have leveraged a cognitive computing system
powered by IBM’s Watson in their Baylor Knowledge Integration Toolkit (KnIT) to accelerate
research, unlock patterns and make discoveries with greater precision.
The system is trained to “think” like a human research expert by unlocking insights, visualizing
possibilities and validating theories at much greater speeds. Leveraging this solution,
researchers identified proteins that modify p53, an important protein related to many cancers,
which can eventually lead to better efficacy of drugs and other treatments in just a matter of
weeks. The solution analyzed 70,000 scientific articles on p53 to predict proteins that turn on
or off p53’s activity – a feat that would have taken researchers years to accomplish without
cognitive capabilities. As a result, cancer researchers have a variety of new directions in which
to target their research.10

The future evolution of cognitive
The future of cognitive computing – both how it advances as a technology and the rates of
adoption in the public and private sectors – will be greatly affected by external forces, as well
as technology evolutionary paths and trends.
Six major forces
Six forces will influence the future of cognitive computing and affect the rate of adoption in
both the public and private sectors.
Technology
• Advanced, intelligent devices will enable a greater
understanding of entity context and contribute to
the robustness of available information corpora.
• Greater scalability needs will drive new
architectures and paradigms.
Society
• Tremendousdemandformoreintelligentmachines
andaccessthroughmobiledevicescanfacilitate
familiarityandcomfortwithtechnology.
• Fears of privacy breaches and machines taking
human jobs could be a deterrent.
Information
• Variety and scalability capabilities of
future systems will advance rapidly to
cope with information exhaust.
• Information explosion could advance
evolution and adoption rates.
Perception
• Perceptions and expectations must
be well managed.
• Unrealistic perceptions of risk and
expectations could lead to a third
“AI Winter.”
Skills
• Cognitive computing demands unique skills,
such as natural language processing and
machine learning.
• Greater availability of key skills will be critical in
the evolution and adoption of the capability.
Policy
• Wider adoption will require modifying policies
(e.g., data sharing) and creating new policies
(e.g., decision traceability).
• Fear, uncertainty and doubt may be addressed
by new policies (e.g., data security and privacy).
Cognitive
computing
evolution
Figure 2
Six forces are impacting the evolution of cognitive computing
“The degree of data sharing will likely
impact the adoption of cognitive
computing solutions; however, the
technical side is fascinating. Policies
can clearly impact technology but the
hope is that the capability will still
move forward.”
Dr. Manuela Veloso, Professor of Computer Science,
Carnegie Mellon University
9

Society – At the societal level, there will be two opposing forces at work. One will push toward
the technology, as the demand for more and more intelligent machines increases over time,
and the desire to access them through personal mobile devices grows as well. This increased
access and exposure to cognitive capabilities through mobile devices has the potential to
increase both familiarity and comfort with the technology. However, there will still be an
opposing force looking to slow adoption as broader understanding and enablement of
cognitive computing occurs.
Technology – There is already a strong belief among subject-matter experts that current
computer architectures and programming paradigms must advance to take cognitive
computing to the next level. Technology advances, including natural language processing,
neuromorphic computers, unsupervised machine learning algorithms (i.e., deep learning) and
virtual reality devices, may help in this evolution. Advances in intelligent devices (e.g., mobile
devices and the Internet of Things [IoT]) will enable greater understanding of entity (e.g., people
and assets) context, which can contribute greatly to the robustness of available information
corpora available to cognitive systems.
Perception – The value proposition of cognitive computing is compelling, and many
pioneering organizations are already realizing economic value. However, perceptions need to
be well managed and grounded in reality. Otherwise, the disparity between vastly different
views combined with misinformation could lead to another “AI Winter,” which refers to a period
of reduced funding and interest in artificial intelligence research.11
Educating the market about
the realities and potential value of cognitive computing is crucial to successful perception
management.
“The traceability of the machine
recommendations (i.e., why a
recommendation was made) will be
important in fostering confidence
and trust.”
Dr. Francesca Rossi, Professor of Computer Science,
University of Padova and Harvard University

Information – IDC projects that the digital universe will reach 40 zettabytes (ZB) by 2020. To
put this number into perspective, consider that 40 ZB is equal to 57 times the amount of all
the grains of sand on all the beaches on earth.12
This information explosion – driven in part by
the rapid growth of mobile devices and social media – has accelerated the growth and
application of cognitive computing. It is now nearly humanly impossible across vocations to
keep pace with the growing volume and velocity of information available today. As the
explosion reaches increasing orders of magnitude, cognitive computing will likely be forced
to evolve more rapidly. The variety and scalability of capabilities for future cognitive systems
will have to advance rapidly to cope with this information exhaust.
Policy – Wider adoption of cognitive computing across domains will likely require that
policies advance (e.g., data sharing, data security and privacy). Additionally, there may be
requirements for entirely new policies in response to advancements in cognitive capabilities.
For example, in the case of machine autonomous decision making (i.e., “decision” capability
area), policies addressing the traceability of the decision-making process may need to be
added. Additionally, in response to fear, uncertainty and doubt, authorities around the world
should review policies to help ensure they both responsibly progress the capability of
cognitive computing and protect citizens.
Skills – A key challenge for the advancement of cognitive computing will be the availability of
skilled humans. Advancing cognitive computing capabilities and implementing cognitive
systems require unique skill sets, such as those of machine learning experts and natural
language processing scientists. These skills are currently in high demand and limited supply.
“There are concerns over another
‘AI winter.’ Education programs will
be key to grow cognitive systems
capability, and IBM is doing a
significant amount of work in this
area.”
Dr. Jim Spohrer, Director Global University Programs,
IBM Research
11

Five key dimensions
How the three capabilities of cognitive computing evolve will depend on five important
dimensions. The evolution path and rate of advancement across these dimensions will impact
the robustness of future capability.
Figure 3
There are five evolutionary dimensions of cognitive computing
How personalized
and interactive is it?
Evolving
dimensions
How can capability
scale to meet
demand?
How ubiquitous is the
capability?
What is the degree of
autonomy in learning?
What are the various
types of inputs it can
sense and interpret?
Personalized
interaction
Learning
Sensing
Ubiquity
Scalability

Personalized interaction – Current cognitive systems are predominantly passive in nature
and require that human beings initiate action to generate an output or response. Often this
interaction is through text typed on a computer, mobile app or web portal. Future cognitive
systems will increasingly enable enhanced natural interaction with users including voice and
visualization. Future systems will become increasingly more interactive and engaging.
Significant advancements have already been made to better understand users and deliver
responses fit for the user’s specific locative and temporal context.
Learning – Current cognitive systems are predominantly trained systems (supervised
learning). These systems rely upon humans with domain-specific subject matter expertise to
train them. This process can be more labor intensive and time consuming. Future cognitive
systems will adopt greater unsupervised learning, which will require much less human
interaction in the system training process. The research community is actively looking to make
breakthroughs in this area.
Sensing – Current cognitive systems primarily work with natural language text and require
natural language processing capability for a particular language. Natural language processing
capabilities for English and Western European languages are more advanced today. Future
generations of cognitive systems will accommodate a variety of media beyond text (e.g., audio,
image, video). Continued advancements in this dimension will be dependent on various
disciplines of computer science (e.g., speech and image processing, pattern recognition).
“We’re just at the beginning of this
cognitive computing era.”13
Dr. John Kelly, IBM Senior Vice President and Director of IBM
Research
13

Ubiquity – Cognitive systems are increasingly being deployed to be widely available and
accessible over web portals, mobile apps and cloud. In the future, as the adoption of
cognitive-based systems increases, they will eventually spread to become ubiquitous. This
future could include a marketplace with millions of cognitive agents or avatars, driven in part
by the explosive adoption of mobile devices, the IoT and the upsurge of machine-to-machine
interaction. Tomorrow’s cognitive computing fabric will be interwoven into technology (such
as social media), thereby touching our daily lives.
Scalability – Cognitive systems need to continue to increase in scalability to support wide
applicability. In 2011, the version of IBM’s Watson system that beat the reigning champion on
the U.S. television game show Jeopardy! required 90 IBM Power 750 servers. By January
2014, Watson was 24 times faster, had a 2,400 percent improvement in performance and was
90 percent smaller.14
In the future, cognitive systems may be offered as a fabric. IBM has
already made its Watson technology available as a development platform in the cloud, which
is spurring innovation and fueling a new ecosystem of entrepreneurial software application
providers.15
WayBlazer, a travel inspiration, recommendation and planning platform that
provides consumers with more personalized, relevant and valuable information, is one
example of a partner realizing value in this ecosystem model. WayBlazer uses a standards-
based cognitive cloud powered by IBM Watson technology to recommend targeted travel
insights and commerce offers that are tailored and customized for each consumer’s
experience.16

Ready or not? Ask yourself these questions
• What opportunities exist to create more engaging and personalized experiences for your
constituents?
• What data aren’t you leveraging that – if converted to knowledge – would allow you to
meet key objectives and business requirements?
• What is the cost to your organization associated with making non-evidence-based
decisions or not having the full array of possible options to consider when actions are
taken?
• What benefit would you gain in being able to detect hidden patterns locked away in your
data? How would this accelerate research, product development, customer services
and the like?
• What is your organizational expertise skill gap? What would change if you could equip
every employee to be as effective as the leading expert in that position or field?
Cognitive computing has the potential to provide significant business and economic value to
organizations across industries. Stay tuned for the next in the series of reports from the IBM
Your cognitive future study, where we will explore lessons learned from pioneering early
adopters and provide recommended steps for your organization to gain first mover advantage
and begin creating new opportunities.
For more information
To learn more about this IBM Institute for Business
Value study, please contact us at iibv@us.ibm.com.
Follow @IBMIBV on Twitter, and for a full catalog of our
research or to subscribe to our monthly newsletter,
visit: ibm.com/iibv
Access IBM Institute for Business Value executive
reports on your tablet by downloading the free “IBM
IBV” app for iPad or Android from your app store.
The right partner for a changing world
At IBM, we collaborate with our clients, bringing
together business insight, advanced research and
technology to give them a distinct advantage in
today’s rapidly changing environment.
IBM Institute for Business Value
The IBM Institute for Business Value, part of IBM Global
Business Services, develops fact-based strategic
insights for senior business executives around critical
public and private sector issues.
15

Study approach and methodology
In the summer of 2014, the IBM Institute for Business Value initiated a study focused on
addressing three questions related to cognitive computing:
1. What is the current state of cognitive computing and how is it expected to evolve?
2. What lessons can be learned from pioneering organizations that have implemented
cognitive computing solutions across various industries?
3. What are the key strategy and planning considerations and what steps can leaders take to
make cognitive computing a reality in their organization?
To address these questions, we conducted interviews with dozens of global subject matter
experts (SMEs) in various areas related to the emerging field of cognitive computing. SMEs
included members of industry with experience in implementing real-world cognitive
computing solutions across multiple domains (e.g., program executives and technical leaders
of cognitive computing system implementations) and members of industry and academia
focused on cognitive computing research and development across multiple research areas
(e.g., professors of computer science at leading universities, members of the Association for
the Advancement of Artificial Intelligence [AAAI]). Interviews focused on gaining insights on
the future of cognitive computing and the forces likely to impact the direction of this
technology, as well as harvesting lessons learned from real-world systems being
implemented by pioneering organizations.

About the study executive leaders
Jay Bellissimo is the General Manager of Watson Transformations in IBM’s Watson Group.
Jay is responsible for helping drive the next era of computing – cognitive computing –
by creating markets, transforming industries and helping clients explore new business models
to take advantage of the many benefits of cognitive computing. He can be reached at
joseph.bellissimo@us.ibm.com.
Shanker Ramamurthy is the Global Managing Partner of Business Analytics and Strategy
within IBM Global Business Services. Shanker is responsible across all industries globally for
the consulting services that include Digital Operations; Finance, Risk and Fraud; Big Data
Analytics; Talent and change; and the IBM Institute for Business Value. He can be reached at
sramamur@us.ibm.com.
About the authors
Dr. Sandipan Sarkar is an Executive Architect in the IBM Global Business Services Global
Government Center of Competency and is responsible for designing and implementing
complex and innovative technology solutions for organizations around the world. Sandipan
holds a PhD in natural language processing from Jadavpur University. He can be reached at
sandipan.sarkar@in.ibm.com.
Dave Zaharchuk is the Global Government Industry Leader for the IBM Institute for Business
Value. Dave is responsible for directing thought leadership research on a variety of issues and
topics. He can be reached at david.zaharchuk@us.ibm.com.
17

Contributors
Dr. Lisa Amini, Ian Baker, Dr. Guruduth Banavar, Grady Booch, Dr. Chris Codella, Steve Cowley,
Dr. Will Dubyak, Juliane Gallina, John Gordon, Bill Hume, Brian Keith, Peter Korsten, Ravesh
Lala, Gina Loften, Phil Poenisch, Dr. Francesca Rossi, Dr. Manuela Veloso and Eric Will.
Acknowledgments
We would also like to thank Brian Bissell, Dr. Eric Brown, Dr. Murray Campbell, Patricia Carrolo,
John Hogan, Dr. Daniel Kahneman, Shibani Kansara, Nitin Kapoor, Eric Lesser, Ryan Musch,
Mary Ann Ryan, Prasanna Satpathy, Akash Sehgal, David Sink and Dr. Jim Spohrer.

Notes and sources
1 “Healthcare Decision Support and IBM Watson: – Markets Reach $239 Billion By 2019.”
WinterGreen Research, Inc. Press Release. March 19, 2013. http://wintergreenresearch.
com/reports/Healthcare%20Decision%20Support%202013%20press%20release.pdf
2 “IBM Global Technology Outlook 2014.” IBM Research. 2014.
3 Ibid.
4 Ibid.
5 “USAA members can quiz this celebrity computer soon (Who is Watson?).” USAA News.
July 23, 2014. https://communities.usaa.com/t5/USAA-News/USAA-members-can-
quiz-this-celebrity-computer-soon-Who-is-Watson/ba-p/37556?SearchRanking=
1SearchLinkPhrase=watson; “USAA and IBM Join Forces to Serve Military Members.”
IBM Press Release. July 23, 2014. http://www-03.ibm.com/press/us/en/
pressrelease/44431.wss
6 “IBM Global Technology Outlook 2014.” IBM Research. 2014.
7 Ibid.
8 Ibid.
9 Terry, Ken. “IBM Watson Helps Doctors Fight Cancer.” Informationweek.com. February 8,
2013. http://www.informationweek.com/healthcare/clinical-information-systems/
ibm-watson-helps-doctors-fight-cancer/d/d-id/1108594?page_number=1
19

10 Picton, Glenna. “Study shows promise in automated reasoning, hypothesis generation
over complete medical literature.” Baylor College of Medicine News. August 25, 2014.
https://www.bcm.edu/news/research/automated-reasoning-hypothesis-generation
11 AI Newsletter. January 2005. http://www.ainewsletter.com/newsletters/aix_0501.htm#w
12 “New Digital Universe Study Reveals Big Data Gap: Less Than 1% of World’s Data is
Analyzed; Less Than 20% is Protected.” EMC Press Release. EMC website. December 11,
2012. http://www.emc.com/about/news/press/2012/20121211-01.htm
13 Greenemeier, Larry. “Will IBM’s Watson Usher in a New Era of Cognitive Computing?”
Scientific American. November 13, 2013, accessed August 6, 2014. http://www.
scientificamerican.com/article/will-ibms-watson-usher-in-cognitive-computing/
14 “IBM Watson Group Unveils Cloud-Delivered Watson Services to Transform Industrial
RD, Visualize Big Data Insights and Fuel Analytics Exploration.” IBM Press Release.
January 9, 2014. http://www-03.ibm.com/press/us/en/pressrelease/42869.wss
15 “IBM Watson’s Next Venture: Fueling New Era of Cognitive Apps Built in the Cloud by
Developers.” IBM Press Release. November 14, 2013. http://www-03.ibm.com/press/us/
en/pressrelease/42451.wss
16 “Digital Travel Pioneer Terry Jones Launches WayBlazer, Powered by IBM Watson.”
IBM Press Release. October 7, 2014. https://www-03.ibm.com/press/us/en/
pressrelease/45024.wss

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