I made this presentation in my 7th semester of B.Tech as per academic curriculum. Took help from several videos from youtube and studied some IBM publications. Cognitive Era is at the dawn. It does not make machines intelligent but instead it allows them to develop cognisance and learn by themselves as we humans do. I am fascinated and looking forward to contribute my existence in this great thought of almighty came into human mind. Guys! You could get a nice introduction from this presentation and explain it to others and even it could be used for your academic homework. Goodluck! GODSPEED!

1. Cognitive Computing
Introduction to IBM’s Watson
Rajkiya Engineering College, Azamgarh
Guided by:
Mr. Abhinandan Tripathi
HOD: Dept. of Information Technology
&
Mr. Shailendra Kumar Sonkar
Faculty: Dept. of Information Technology
Submitted by:
Amit Ranjan
Roll No.: 1473613005
Bachelor of Technology
Branch: Information Technology
3rd Year

2. 2
1. Introduction to Cognitive Computing
2. Evolution of Cognitive Computing
3. Introduction to IBM’s Watson
4. How does Watson Works
5. How Watson learns
6. Present Aspects
7. Future Possibilities
8. References
Contents

3. 1. Introduction to Cognitive Computing
3
1. Observe : We observe visible phenomena and bodies of evidence
2. Interpret: What we know on what we are seeing to generate hypothesis about what it means
3. Evaluate: Which hypothesis is right or wrong
4. Decide: Choosing the option that seems best and act accordingly
Human Cognitive abilities:
Observe Interpret Evaluate Decide
Fig. 1.1: Human Cognitive abilities

4. 1. Introduction to Cognitive Computing
4
• Cognitive computing refers to systems that learn at scale, reason with purpose and interact with humans naturally
• Rather than being explicitly programmed, they learn and reason from their interactions with us and from their
experiences with their environment
Pic. 1.1: IBM’s Cognitive Mind
(logo)

5. 2. Evolution of Cognitive Computing
5
▸Cognitive Systems are made possible by advances in a number of scientific fields over the past half-century, and are
different in important ways from the information systems that preceded them
1.The Tabulating Era (1900s — 1940s):
 The birth of computing consisted of single-purpose mechanical systems that
counted, using punched cards to input and store data, and to eventually instruct
the machine what to do
Pic.2.1 The Tabulating Era
(1900s — 1940s)

6. 2. Evolution of Cognitive Computing
6
The Programming Era (1950s — present):
 The shift from mechanical tabulators to electronic systems began during World War II, driven by military and scientific needs
 Originally built around vacuum tubes, they were given a huge boost by the
invention of the transistor and the microprocessor
 Everything we now know as a computing device
— from the mainframe to the personal computer, to the smartphone and
tablet — is a programmable computer
Pic. 2.2:The Programming Era
(1950s — present)

7. 2. Evolution of Cognitive Computing
7
1. The Cognitive Era (2011 — ):
 The true potential of the Cognitive Era will be realized by combining the data analytics and
statistical reasoning of machines with uniquely human qualities, such as self-directed goals,
common sense and ethical values
Pic. 2.3:The Cognitive Era
(2011 — )

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3. Watson
Pic. 3.1: Watson
 In February 2011, the world was introduced to Watson
 Watson’s ability to answer subtle, complex, pun-laden questions made clear that a new era
of computing was at hand

9. 3. Watson
9
 IBM’s cognitive computing system Watson defeated Ken Jennings and Brad Rutter at Jeopardy!
 Watson’s chess-playing predecessor, Deep Blue, defeated World Chess Champion Garry Kasparov in 1997
Pic.3.2: Watson playing jeopardy Pic. 3.3: Garry Kasparov with
deep blue

10. R&D
Demonstration
Commercialization
Cross-industry
Applications
IBM
Researh
Project
(2006 – )
Jeopardy!
Grand
Challenge
(Feb 2011)
Watson
for
Healthcare
(Aug 2011 –)
Watson
Ecosystem
(2014– )Watson
for Financial
Services
(Mar 2012 – )
Expansion
Fig. 3.1: Timeline of Watson’s Evolution
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11. 4. How does Watson Works
11
Understands
unstructured data
(80% of available
data )
• This includes
everything
from
literature,
articles,
research
reports, blogs,
posts and
tweets
Relies on Natural
language; which is
govern by rules of
grammar, context
and culture
• Breaks down a
sentence
syntactically,
relationally and
structurally
Discerning
meaning from the
semantics of the
written material
• Tries to possibly
extract logically
responses and
draw inferences
to potential
answers through
a broader way
of linguistic
models and
algorithms
Fig. 4.1: Process Chart showing working of Watson

12. 5. How Watson learns
 When Watson goes to works in a particular field it learns the language, the jargon and the motive thought of that
domain
 Ex: Cancer
12
Cancer
Hodgkin Dis
Adrenal Cancer
Breast Cancer
Osteosarcoma
Lymphoma
Ovarian Cancer
Neuroblastoma
Leukemia
Skin Cancer
Fig. 5.1: Different types of Cancer

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Each type may have different Symptoms and treatments
However, Those symptoms can also be associated to diseases other
than cancer
Treatment can have side effects and effect people differently depending
on many factors
Watson evaluates standards of care practices and thousands of pages of
literature that capture the best science in the field
Identifies the therapies that offer the best choices for the doctor to
consider in the treatment of the patient
Fig. 5.2: Watson’s approach for treatment

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1.Corpus Collection:
 With the guidance of human experts Watson collects the knowledge in order to have literacy in a particular domain---
called a corpus of knowledge
Corpus of Knowledge
 Collection of corpus starts with loading the relevant body of literature into Watson
2.Curating the Content:
 Building the Corpus also requires also requires some human intervention to go through the information and discard anything
that is out of date, poorly recorded or immaterial to the problem domain

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3.Ingestion:
 Next, data is preprocessed by Watson building indices, and other metadata that make working with that
content more efficient
 At this time Watson may also create a knowledge graph to assist in answering more precisely
4. Machine Learning:
 Now Watson has ingested the corpus, It needs to be trained by human experts to interpret the information
 To learn the best possible responses and acquire the ability to find patterns partners with experts to train it
in using a approach called machine learning
 An expert will upload the machine data in the form of Question/Answer pairs that serve as ground truth
 This does not give explicit answers for every question it will receive but rather teaches it the linguistic
patterns of meaning in the domain
 Once Watson trained on Q/A pattern it continues to learn through ongoing interactions
 Interactions between users and Watson are periodically reviewed by experts and fed back into the system
 Watson is ready to now ready to respond to questions about highly complex situation and quickly provide
a range of potential recommendation that are backed by evidence

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 Banks are analyzing customer requests and financial data to surface insights to help them make investment recommendations
 Companies in heavily regulated industries are querying the system to keep up with ever-changing legislation and standards of
compliance
 oncologists are testing ways in which cognitive systems can help interpret cancer patients’ clinical information and identify
individualized, evidence- based treatment options that leverage specialists’ experience and research
 Watson products and APIs can understand all forms of data to reveal business-critical insights, and bring the power of cognitive
computing to every organization
 With Watson APIs and solutions, businesses are already achieving outcomes – from improving customer engagement, to
scaling expertise, to driving innovation and growth
6. Present Aspects

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7.Future Possibilities
 Cognitive systems, in contrast, combine five core capabilities:
1. They create deeper human engagement
2. They scale and elevate expertise
3. They infuse products and services
with cognition
4. They enable cognitive processes
and operations
5. They enhance exploration and discovery
 Schaeffler and IBM Sign Watson IoT Partnership for New Industrial Era

18. “Technology creates possibilities and potential, but ultimately, the future we get will depend on the choices we
make. Technology is not destiny.
We shape our destiny
— Erik Brynjolfsson, MIT
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19. 8. References
[1]Kelly, John E. and Steve Hamm. Smart Machines: IBM’s Watson and the Era of Cognitive Computing.
New York. Columbia University Press, 2014
[2] Dr. John E. Kelly III Senior Vice President, IBM Research and Solutions Portfolio. Computing, cognition and
the future of knowing: How humans and machines are forging a new age of understanding
[3] Watson, Thomas Jr. IBM Archives[Online]
https://www03.ibm.com/ibm/history/exhibits/watsonjr/watsonjr_quoted.html
[4] IBM Watson: How it Works[online] https://www.youtube.com/watch?v=_Xcmh1LQB9I&t=11s
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THANKS!
Any questions?