The document outlines IBM's Watson, a cognitive computing system developed to answer questions posed in natural language, famously showcased on the quiz show 'Jeopardy!'. It details Watson's hardware specifications, technology architecture, its development timeline, and capabilities in utilizing machine learning and data analysis. Additionally, it highlights Watson's applications across various fields, its limitations, and concludes with its competitive performance against human players.

1. DEPARTMENT OF INFORMATION TECHNOLOGY
CH. BRAHM PRAKASH GOVERNMENT ENGINEERING COLLEGE
IBM’S WATSON
SUBMITTED TO: SUBMITTED BY:
MS. RUCHI 1. JATIN BANSAL (02820703112)
MR. GULZAR AHMED 2. SHASHANK SHEKHAR(10320703112)

2. HARDWARE SPECIFICATIONS
| 90 x IBM Power 750 servers
| 2880 POWER7 cores
| POWER7 3.55 GHz chip
| 500 GB per sec on-chip bandwidth
| 10 Gb Ethernet network
| 16 Terabytes of memory
| 20 Terabytes of disk, clustered
| Can operate at 80 Teraflops
| 10 racks include servers, networking, shared disk system, cluster controllers

3. EQUIPPED TECHNOLOGIES
| IBM’s DeepQA software.
| Apache UIMA (Unstructured information management architecture) framework.
| Written in various languages including JAVA, C++, Prolog.
| Runs on SUSE LINUX Enterprise Server 11 Operating System.
| Includes Apache Hadoop Framework to provide distributive computing.

4. COGNITIVE COMPUTING
| Cognitive computing is the simulation of human thought processes in a computerized model.
| Cognitive computing involves self-learning systems that use data mining, pattern recognition and
natural language processing to mimic the way the human brain works. The goal of cognitive
computing is to create automated IT systems that are capable of solving problems without
requiring human assistance.
| Cognitive computing systems use machine learning algorithms. Such systems continually acquire
knowledge from the data fed into them by mining data for information.
| Cognitive computing is used in numerous artificial intelligence (AI) applications, including expert
systems, natural language programming, neural networks, robotics and virtual reality.
| The term cognitive computing is closely associated with IBM’s cognitive computer system, Watson.

5. WHAT IS WATSON ?
| Watson is a question answering computer system capable of
answering questions posed in natural language.
| Developed by a research team led by principal investigator David
Ferrucci.
| Watson was named after IBM's first CEO and industrialist Thomas J.
Watson.
| The computer system was specifically developed to answer questions
on the quiz show Jeopardy!

6. WATSON’S HISTORY
| In 1997, IBM had been on the hunt for a new challenge.
| In 2004, IBM Research manager Charles Lickel, saw Jeopardy (A Quiz game) as a possible challenge for
IBM.
| In 2005, IBM Research executive Paul Horn backed Lickel up to play Jeopardy! with an IBM system.
| In 2006 initial tests run by David Ferrucci, Watson was given 500 clues from past Jeopardy!
programs.
| In 2007, the IBM team was given three to five years and a staff of 15 people to solve the problems.
|In 2008, the developers had advanced Watson such that it could compete with Jeopardy! Champions.

7. | In 2010, Watson could beat human Jeopardy! contestants on a regular basis.
| On January 30, 2013, it was announced that Rensselaer Polytechnic Institute would receive a successor version of
Watson.
| On February 6, 2014, it was reported that IBM plans to invest $100 million in a 10-year initiative to use Watson.
| On June 3, 2014, three new Watson Ecosystem partners were chosen from more than 400 business concepts
submitted by teams spanning 18 industries from 43 countries.
| On July 9, 2014, Genesys Telecommunications Laboratories announced plans to integrate Watson to improve
their customer experience platform, citing the sheer volume of customer data to analyze is staggering.
| At present, we have Watson Engagement Advisor, Watson Explorer, Watson Discovery Advisor, Watson for Oncology,
Watson for Clinical Trial Matching, Watson Knowledge Studio.

8. WATSON’S WORKING
Fig. DeepQA Architecture: The Technology Behind Watson
Answer
Scoring
8
Models
Answer &
Confidence
Evidence
Sources
Models
Models
Models
Models
ModelsPrimary
Search
Candidate
Answer
Generation
Hypothesis
Generation
Hypothesis and Evidence
Scoring
Final Confidence
Merging & Ranking
Synthesis
Answer
Sources
Question
Decomposition
Evidence
Retrieval
Deep
Evidence
Scoring
Hypothesis
Generation
Hypothesis and Evidence Scoring
Learned Models
help combine and
weigh the Evidence
Question &
Topic
Analysis
Question

9. STEP 1 ANALYZING THE QUESTION
Category:
WORLD GEOGRAPHY
Clue:
In 1897 Swiss climber Matthias Zurbriggen became
the first to scale this Argentinean peak.
Step 1 Watson dissects the clue to understand what it
is asking for.
Watson tokenizes and parses the clue to identify the
relationships between important words and find the
focus of the clue, i.e. this Argentinean peak.

10. STEP 2 SEARCH
Step 2 Watson searches its content for text passages that relate to the clue.
Using important terms from the clue, Watson performs a search over millions of documents to find relevant passages.
Timeline of Climbing the Matterhorn
* August 25: H.R.H. the Duke of the Abruzzi made
the ascent with Mr. A. F. Mummery and Dr. Norman
Collie, and one porter, Pollinger, junior. According to
Mummery the weather was threatening, and, the Prince
climbing very well, they went exceedingly fast, so that
their time was probably the quickest possible. They left
the bivouac at the foot of the snow ridge at 3.40 a.m.,
and reached the summit at 9.50. A few days afterwards
the first descent of the ridge was accomplished by Miss
Bristow, with the guide Matthias Zurbriggen, of
Macugnaga.
The first known ascent of Aconcagua was during an
expedition was during an expedition led by Edward
Fitz Gerald in the summer of 1897. Swiss climber
Matthias Zurbriggen reached the summit alone on
January 14 via today's Normal Route. A few days later
Nicholas Lanti and Stuart Vines made the second
ascent. These were the highest ascents in the world at
that time. It's possible that the mountain had
previously been climbed by Pre-Columbian Incans.

11. STEP 3 HYPOTHESIS & CANDIDATE GENERATION
Step 3 Watson analyzes the text passages and generates possible “candidate answers”.
Watson extracts important entities – so called “candidate answers” – from the documents. The focus is on
coverage, which means that as much as possible is added (here, peaks, mountain ranges, people). At that
stage, these are just possible answers to Watson.

12. STEP 4 ANSWER SCORING
Step 4 Candidate answers are scored using a large number of answer scoring analytics.
In a massively parallel manner, Watson uses over 100 answer and deep evidence scoring algorithms to determine how
well a candidate answer matches what the clue is asking for.

13. STEP 5 SUMMARIZING ALL EVIDENCE
Step 5 Watson summarizes all evidence and determines its confidence in the answers.
The scores are grouped into meaningful groups, or evidence dimensions. A plot of these yields the evidence profile
for the candidate. Watson statistically combines the scores to produce a final confidence score.
Category: WORLD GEOGRAPHY
Clue: In 1897 Swiss climber
Matthias Zurbriggen became
the first to scale this
Argentinean peak.
What is
Aconcagua?

14. WATSON’S DRAWBACKS
| IBM Watson does not answer questions for which answers are unknown.
| IBM Watson is unable to apply most known algorithms to find answers,
e.g., solve a system of linear equations, figure out a logic puzzle, etc.
| Watson can automatically pick up algorithms from books like it picks
historical dates and relationships from newspaper archives.

15. CONCLUSION
| Deep Analytics – IBM Watson achieved champion-levels of Precision and Confidence over a huge variety
of expression.
|Speed – By optimizing Watson’s computation for Jeopardy! on 2,880 POWER7 processing cores we went
from 2 hours per question on a single CPU to an average of just 3 seconds – fast enough to compete
with the best.
|Results – in 55 real-time sparring against former Tournament of Champion Players last year, Watson put on a
very competitive performance, winning 71%. In the final Exhibition Match against Ken Jennings and
Brad Rutter, Watson won!

16. REFERENCES
| Quora
| Wikepedia
| IBM Watson
| IBM Watson: What is Watson?
| The DeepQA Research Team - IBM
| Youtube: IBM Watson: How it Works

17. Thank You !