IBM Watson-How it works

#IBMEDGE © 2012 IBM Corporation
sBD07
IBM Watson: How it Works
and What it Means for Society
Beyond Winning Jeopardy!
Tony Pearson
IBM Master Inventor and Senior
Managing Consultant

In 2011, the IBM Watson computer was
able to beat the top-earning human
winners on the trivia game-show
“Jeopardy!” Presenter Tony Pearson,
author of "How to Build Your Own
Watson Jr. in Your Basement," will
explain how the IBM Watson system
was put together, how it works, and
what examples of text mining and big
data analytics means for society as we
apply technology to meet
tomorrow's challenges.

Sessions -- Tony Pearson
• Monday
– 1:00pm Storing Archive Data for Compliance Challenges
– 4:15pm IBM Watson: What it Means for Society
• Tuesday
– 4:15pm Using Social Media: Birds of a Feather (BOF)
• Wednesday
– 9:00am Data Footprint Reduction: IBM Storage options
– 2:30pm IBM's Storage Strategy in the Smarter Computing era
– 4:15pm IBM SONAS and the Cloud Storage Taxonomy
• Thursday
– 9:00am IBM Watson: What it Means for Society
– 10:30am Tivoli Storage Productivity Center Overview
– 5:30pm IBM Edge “Free for All” hosted by Scott Drummond
3

An estimated 2 billion people are now on the Web
… and a trillion connected objects – cars, appliances,
cameras, roadways, pipelines
Data is getting more social
…20M articles on Wikipedia
…30B pieces of Facebook content are shared monthly
…There are 156M public blogs
Data volume is expanding at an incredible rate
…Data will grow 800% in the next five years
…Unstructured data growing faster than structured
Today’s Information Challenge
4

1 in 2
Business leaders don’t
have access to data
they need
83%
CIO’s cited BI and analytics
as part of their visionary
plan
54%
Companies use
analytics for
competitive advantage
80%
of the world’s
data today is
unstructured
90%
of the world’s data
was created in the
last two years
20%
amount of available
data traditional
systems leverages
Source: GigaOM, Software Group, IBM Institute for Business Value"
Dying of Thirst in an Ocean of Data
5

Can we design a computing
system that rivals a human’s
ability to retrieve, analyze and
interpret vast amounts of
information?
What if an enterprise had all the
answers it needs to succeed?
6

The Jeopardy! Challenge:
A compelling and notable way to drive and measure the technology of
automatic Question Answering along 5 Key Dimensions
$600
In cell division, mitosis
splits the nucleus &
cytokinesis splits this
liquid cushioning the
nucleus
$200
If you're standing, it's the
direction you should look to
check out the wainscoting.
$2000
This actor, Audrey’s husband
from 1954 to 1968, directed
her as Rima the bird girl in
‘Green Mansions’
$1000
The first person mentioned
by name in ‘The Man in the
Iron Mask’ is this hero of a
previous book by the same
author.
1. Broad Domain
2. Complex Language
3. High Precision
4. Accurate Confidence
5. High Speed
7

The Plan: Compete against Humans
to Demonstrate Technology
8

Do you Remember IBM Deep Blue?
•Chess
– A finite, mathematically well-defined search space
– Limited number of moves and states
– All the symbols are completely grounded in the
mathematical rules of the game
•Human Language
– Words by themselves convey different meanings
– Only grounded in human cognition
– Words navigate, align and communicate an infinite
space of intended meaning
– Computers can not ground words to human
experiences to derive meaning
9

Where was
Einstein
born?
Source: Spreadsheet, Database, etc. Source: Jack Welch and the GE Way, Robert Slater
Source: Spreadsheet, Database, etc. Source: http://www.schaeffenacker-ulm.de/en/otto.html
Structured Data Unstructured Data
Welch ran
this?
“One day, from among his city
views of Ulm, Otto chose a
water color to send to Albert
Einstein as a remembrance of
Einstein´s birthplace”
“If leadership is an art then
surely Jack Welch has proved
himself a master painter during
his tenure at GE”
Physicist Birth Place
A. Einstein Ulm
N. Bohr Copenhagen
M. Curie Warsaw
Source: IBM Research
Person Organization
L. Gerstner IBM
J. Welch GE
W. Gates Microsoft
Why is it so hard for computers to
understand humans?
10

Decision Maker
Search Engine
Finds Documents containing Keywords
Delivers Documents based on Popularity
Has Question
Distills to 2-3 Keywords
Reads Documents, Finds Matches
Finds & Analyzes Evidence
Informed Decision Making:
Search vs. Expert Q&A
Expert
Understands Question
Produces Possible Answers & Evidence
Delivers Response, Evidence & Confidence
Analyzes Evidence, Computes Confidence
Asks NL Question
Considers Answer & Evidence
Decision Maker
11
11

Computers in SciFi Movies…
Lots of Lights and Cardboard!
IBM Watson….Lots of Work!
12

Question
100s Possible
Answers
1000’s of
Pieces of Evidence
Multiple
Interpretations
100,000’s scores from many simultaneous
Text Analysis Algorithms100s sources
. . .
Hypothesis
Generation
Hypothesis and
Evidence Scoring
Final Confidence
Merging &
Ranking
Synthesis
Question &
Topic
Analysis
Question
Decomposition
Hypothesis
Generation
Hypothesis and Evidence
Scoring
Answer &
Confidence
Unstructured Information
Management Architecture (UIMA)
To date, UIMA is the only industry standard for content analytics.
Developed by IBM, it is now an OASIS standard, with source code
for reference implementation kept by Apache Software Foundation.
13

Winning Human
Performance
Winning Human
Performance
Computers, circa 2006Computers, circa 2006
Grand Champion
Human
Performance
Grand Champion
Human
Performance
Each dot represents an actual historical human Jeopardy! game
Answering Precision, circa 2006
14

Baseline 12/06
v0.1 12/07
v0.3 08/08
v0.5 05/09
v0.6 10/09
v0.8 11/10
v0.4 12/08
v0.2 05/08
IBM Watson
Playing in the Winners Cloud
V0.7 04/10
DeepQA: Progress in Answering
Precision
15

• Deep Analytics – Combining many analytics in a
novel architecture, we achieved very high levels of
Precision and Confidence over a huge variety of
content.
• 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.
• Results – in 55 real-time sparring games against
former Tournament of Champion Players in 2010,
Watson put on a very competitive performance in all
games -- placing 1st in 71% of the them!
Precision / Confidence & Speed
16

IBM Watson vs. Wolfram Alpha
Source: http://www.quora.com/IBM-Watson/Whats-the-system-architecture-of-the-IBM-Watson

Watson’s
QA Engine
2,880
IBM POWER7
Compute
Cores
15 TB of
Memory
Strategy
Text-to-Speech
Jeopardy!
Game
Control
System
Human Player
2
Clue GridClue Grid
Clues, Scores & Other Game Data
Insulated and
Self-Contained
Answers &
Confidences
Human Player
1
Clue &
Category
Decisions to
Buzz and Bet
Analysis of natural
language content
equivalent to 1 Million
Books
Real-Time Game Configuration
Watson’s
Game
Controller
18

Watson’s
QA Engine
2,880
IBM POWER7
Compute
Cores
15 TB of
DRAM memory
Strategy
Text-to-Speech Answers &
Confidences
Clue &
Category
Decisions to
Buzz and Bet
IBM Watson Components
Avatar -
Apple Mac
notebook
Voice synthesis,
strategies for betting,
buzzing in, clue
selection &
exchanging info with
Jeopardy Computers
Windows 7
Lenovo desktop
10 Frames of
Hardware:
• 88 Compute nodes
• 2 Storage nodes
• 4 SAS disk shelves
• 10GbE Network
• 80 TeraFLOPS
Software:
• SLES 11 Linux
• Clustered NFS
• GPFS file system
• Hadoop, UIMA-AS
• 700 KLOC Java
• 300 KLOC C++
IBM Power750
servers (POWER7)
Watson’s
Game
Controller
19

Storage in IBM Watson
• Sources
– Encyclopedias
– Dictionaries
– Books and Web pages
– Quotations
– Wire News
– Knowledge Bases
– Lexical Database of English
• Test and Training Data
– J! Archive
2 IBM Power750 servers
• Clustered NFS
• IBM GPFS file system
4 IBM EXP 12S disk shelves
• 48 x 450GB SAS drives
• 10.4 TB of RAID-1 space
• 1 TB of unstructured data
16 TB of DRAM memory

Watson Wins!
Largest Jeopardy! in 5 years
34.5M Jeopardy! Viewers
1.3B+ Impressions
Over 10,000 Media Stories
11,000 attend watch events
2.5M+ Videos Views
12,582 Twitter tweets
25,763 Facebook Fans
On February 14-16, 2011, IBM Watson changed history, introducing a
system that rivaled a human’s ability to answer questions posed in
natural language with speed, accuracy and confidence.
21

Reflections on IBM Watson

How to Build your Own Watson Jr.
In your Basement (eight steps)
1. Acquire Hardware
2. Establish Networking
3. Install Linux and Middleware
4. Download information sources
Server 1:
Presentation
Server
This will be your
avatar interface to
ask questions and
display answers
Server 2:
Business Logic
Server
This will be your
compute node for
analytics
Server 3:
File / Database
Server
This will be your
information source
repository
23

How to Build your Own Watson Jr.
In your Basement (eight steps)
5. Query Panel – Parsing the Question
6. Implement Hadoop, UIMA with Java, C++ and XML
• This is the part we call in the industry
a “Small Matter of Programming” (SMOP)
7. UIMA-AS Parallel Processing
8. Testing and Training
Element # of Cores Response
Single core 1 2 hours
3 Quad-Core servers 12 10 minutes
1 Frame (Watson) 288 30 seconds
IBM Watson 2880 3 seconds
24

One Year Later –
IBM Watson by the numbers
15
5
386
77
Million viewers watched the rerun of
IBM Watson’s triumph on Jeopardy!
Universities are collaborating
with IBM on Watson and
Analytics
Thousand downloads of “How to
build your own Watson Jr. in
your basement”
Members of U.S. Congress
that have competed against
Watson
25

…built on a massively parallel
probabilistic evidence-based
architecture
Understands
Natural
Language
of human
speech
Adapts and
Learns from
user selections
and responses
Generates and
evaluates
hypothesis for
better outcomes
IBM Watson brings together a set of
transformational technologies to
drive optimized outcomes
26

27 8/2/2011
Watson was built for Jeopardy!
Can be enhanced for future applications
Watson's current capabilities were
constrained for Jeopardy! requirements...
• English only
• A single questioner per system
instance
• 3-second response time
• Static content
• Unstructured text
• Requires training data – history
of questions and answers
...but future Watson enhancements are
possible with further development...
• Multiple, varied users
• More dynamic content updates
• More/varied training data
• Varied response times
• Additional languages
Early 2011 Future
27

IBM PureSystems
IBM Watson
10 Frames
IBM PureFlex
4 Frames
28
60% Reduced Floor Space!

IBM Watson has the capabilities to address grand
business and societal challenges
Contact Center
Healthcare Financial Services
Government
Diagnostic/treatment
assistance, evidenced-
based insights,
collaborative medicine
Investment and
retirement planning,
institutional trading and
decision support
Call center and tech support
services, enterprise
knowledge management,
consumer insight
Public safety, improved
information sharing,
security
Transforming how Business Thinks,
Acts, and Operates
29

Medical information
is doubling every 5
years, much of
which is
unstructured
81% of physicians
report spending 5
hours or less per
month reading
medical journals
Source: International Journal of Circumpolar Health, DoctorDirectory.com, Institute for Medicine"
Healthcare Industry is beset with
complex information challenges
Medicine has become too complex (and only) about 20 percent of the knowledge clinicians use
today is evidence-based.”
--- Steven Shapiro, Chief Medical and Scientific Officer, UPMC
30

Interprets and understands
natural language questions
Analyzes large volumes
of unstructured data
Quantifies degrees of
confidence in potential
answers
Supports iterative
dialogue to refine results
Adapts and learns to
improve results over time
Why is Watson Technology
ideal for Healthcare?
31
Source: IBM Research, MI, SCIP, BCG analysis
What condition has red eye, pain,
inflammation, blurred vision, floating
spots and sensitivity to light?
What condition has red eye, pain,
inflammation, blurred vision, floating
spots and sensitivity to light?
Physician Notes, Medical Journals,
Pathology results, Clinical Trials,
Wikipedia, etc
Physician Notes, Medical Journals,
Pathology results, Clinical Trials,
Wikipedia, etc
Family History, Physical Exam,
Current Medications,
etc.
Family History, Physical Exam,
Current Medications,
etc.
New Clinical Recommendations.
New Drugs. Approved use of Drugs,
etc.
New Clinical Recommendations.
New Drugs. Approved use of Drugs,
etc.
Uveitis 91%
Iritis 48%
Keratitis 29%
Uveitis 91%
Iritis 48%
Keratitis 29%

32
• Private data
• Custom algorithms
• Custom applications
Customized Watson
Solution Appliance
IBM Watson for Healthcare
Watson for Healthcare Service
...Patient
Workup
Customized
Solution
Differential
Diagnosis
Second
Opinion
......
Public
domain
Public
domainPublishersPublishers Healthcare
Providers
Healthcare
Providers
......
Watson-enabled Solutions from major
healthcare solution providers
Benefits
Providers
Benefits
Providers
Evidence
Data Training
Data
Annotators
and
Algorithms
Relationship
Data
Watson Engine and Scoring and
Confidence Models
...
Medical Professionals and Patients
• Improve quality of care
• Reduce errors
• Engage patients
• Improve audit trails
• Improve efficiency
• Better utilize skills
• Right content,
right time
• Best-practices to
point of care
• Capture value
• Advance
Evidenced-based
Care
• Foster a
healthcare
analytics
ecosystem
• Capture value

Watson @ WellPoint
• WellPoint & IBM agreement
• WellPoint will develop and launch Waston-based solution
–Help improve patient care
–Provide delivery of up-to-date, evidence-based healthcare
• IBM will develop the base Watson healthcare technology
• Targeted implementation:
– Physician Helper: Will be a consultant with the ability to analyze
various inputs to help humans make a decision
– Load Watson with medical data to analyze and identify conditions
• Ranging from heart disease to cancer to diabetes.
• Medical histories, test results, possible drug interactions and treatment
options will be evaluated too.
– Working with select physician groups in clinical spots
33

Seton Healthcare
• First client to utilize IBM Content and Predictive Analytics for
Healthcare
– Combines IBM's Watson technology with industry solutions offering
• Extract relevant clinical information from vast amounts of patient data
– Better analyze the past
– Understand the present
– Predict future outcomes
• Seton to focus on
– Determine root causes of hospital re-admissions
– Ways to decrease preventable multiple hospital visits
• Facts…
– One in five patients suffer from preventable re-admissions
– Represents $17.4 billion of the current $102.6 billion Medicare budget *
– Beginning in 2012, hospitals are penalized for high re-admission rates with
reductions in Medicare discharge payments
* According to the New England Journal of Medicine
34

• First of a kind solution for healthcare and available to help
healthcare organizations with transformation opportunities
– Integrates structured and unstructured data
– Applies predictive root cause analysis, natural language processing
(like IBM Watson), and built-in medical terminology support
– Identifies trends, patterns and deviations revealing clinical and
operational insights. It is a first of a kind solution for healthcare and
available to help healthcare organizations with transformation
opportunities.
• Pairs Content Analytics and SPSS Modeler Professional
with solution and healthcare industry specific medical
terminology support and services
– Synergistic solution to IBM Watson
– Healthcare solution that pairs natural language processing with
predictive root cause analysis.
IBM Content and Predictive
Analytics for Healthcare:
35

Reuters publishes the
equivalent of 9000 pages of
financial news every day1
Five new research
documents come out of Wall
Street every minute1
Asset managers receive up
to 1,000 e-mails daily1
Sources: 1 - www.financial-domain.info/integrating-qualitative-and-quantitative-information/
2- IBM Client experience with ForEx traders
3 – Derived from NYSE data
Financial services firms are
beset with complex information
challenges
36

Institutional Investment Advisor
Retail Financial Advisor
Risk Management officer
Utilize more information, more
effectively and efficiently, to support
investment and credit decisions
Provide investment advice directly
to retail investors and/or support
advisors for high net worth clients
Leverage superior capabilities
for fraud detection and/or
Compliance support
Financial Services– Role based
use case examples
37

Citigroup
• Announced plans to explore how Watson fits into the
realm of digital banking
• Citigroup will examine…
– Watson's ability to “Help analyze customer needs”
– Process vast amounts of up-to-the-minute financial, economic,
product and client data,
– Provide rapid, personalized banking solutions.
– Watson's Deep-content analytics, Natural language processing
and Evidence-based learning with how the company interacts
with customers to advance digital banking
• Watson's financial assistance will be provided as a
“Cloud-based service"
38

Need to rethink what it will take to
get ahead tomorrow
Traditional IT
• Structured data (local)
• Deterministic Applications
• Search Oriented
• Query Results
• Machine Language
Emerging IT
• Structured & unstructured (global)
• Probabilistic Applications
• Discovery Oriented
• Big Data Insights
• Natural Language
39

Summary
• IBM Watson is...
– A reasoning system that processes questions and answers in
Natural Language, across structured and unstructured data
sources, using Deep Analytics that learns for optimal results
• IBM Watson is not…
– An advanced search engine, database retrieval system, our
new computer overlord, or the beginning of Skynet
• IBM Watson works by...
– Analyzing the question, generating hypotheses, evaluating
evidence and presenting results scored by confidence level
• Which means that…
– Society now has a new tool to help tackle some of the biggest
information challenges in healthcare, financial services, etc.

#IBMEDGE
Intel, the Intel logo, Xeon and Xeon Inside are trademarks or registered
trademarks of Intel Corporation in the U.S. and /or other countries.
Thank You!
Session: sBD07
Presenter: Tony Pearson

www.ibmwatson.com
www.facebook.com/ibmwatson
www.twitter.com/ibmwatson
(Tweet hashtag #ibmwatson )
www.youtube.com/ibm
Learn more at:
See Watson in action at an IBM Lab, Briefing
Center or Analytics Solution Center

About the Speaker
Mr. Tony Pearson
Master Inventor,
Senior Managing Consultant
IBM System Storage
Tony Pearson is a Master Inventor and Senior managing consultant for the IBM System Storage™ product line. Tony joined
IBM Corporation in 1986 in Tucson, Arizona, USA, and has lived there ever since. In his current role, Tony presents briefings on
storage topics covering the entire System Storage product line, Tivoli storage software products, and topics related to Cloud
Computing. He interacts with clients, speaks at conferences and events, and leads client workshops to help clients with
strategic planning for IBM’s integrated set of storage management software, hardware, and virtualization products.
Tony writes the “Inside System Storage” blog, which is read by hundreds of clients, IBM sales reps and IBM Business Partners
every week. This blog was rated one of the top 10 blogs for the IT storage industry by “Networking World” magazine, and #1
most read IBM blog on IBM’s developerWorks. The blog has been published in series of books, Inside System Storage: Volume
I through IV.
Over the past years, Tony has worked in development, marketing and customer care positions for various storage hardware and
software products. Tony has a Bachelor of Science degree in Software Engineering, and a Master of Science degree in
Electrical Engineering, both from the University of Arizona. Tony holds 19 IBM patents for inventions on storage hardware and
software products.
9000 S. Rita Road
Bldg 9070 Mail 9070
Tucson, AZ 85744
+1 520-799-4309 (Office)
tpearson@us.ibm.com
Tony Pearson
Master Inventor,
Senior Managing
Consultant
IBM System Storage™

Additional Resources
44
Email:
tpearson@us.ibm.com
Twitter:
http://twitter.com/az99Øtony
Blog:
http://ibm.co/brAeZØ
Books:
http://www.lulu.com/spotlight/99Ø_tony
IBM Expert Network:
http://www.slideshare.net/az99Øtony
44

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Information is provided "AS IS" without warranty of any kind.
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Information concerning non-IBM products was obtained from a supplier of these products, published announcement material, or other publicly available sources and does not
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