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© 2012 International Business Machines Corporation
Watson – Beyond Jeopardy
University of Dayton – 3 April 2013
Follow us @IBMWatson
John M. Kundtz, Senior Principal Consultant
IBM Global Complex Opportunity Support
@JMKundtz
jkundtz@us.ibm.com
© 2012 International Business Machines Corporation2
Result of IBM Research “Grand Challenge”
On February 14, 2011, IBM Watson made history
© 2012 International Business Machines Corporation3
Agenda
What is IBM Watson and why is it important?
How is IBM putting Watson to work?
What can we expect in the future?
© 2012 International Business Machines Corporation4
Businesses are “dying of thirst in an ocean of data”
1 in 2
business leaders
don’t have access
to data they need
83%
of CIOs cited BI and
analytics as part of
their visionary plan
2.2X
more likely that top
performers use
business analytics
80%
of the world’s data
today is
unstructured
90%
of the world’s data
was created in the
last two years
1 Trillion
connected devices
generate 2.5
quintillion bytes
data / day
© 2012 International Business Machines Corporation5
Understands
natural language
and human
communication
Adapts and learns
from user
selections and
responses
Generates and
evaluates
evidence-based
hypothesis
…built on a massively parallel
architecture optimized for IBM POWER7
IBM Watson combines transformational technologies
1
2
3
© 2012 International Business Machines Corporation6
Big Data
Content
Analytics
IBM Technology Depth
Business
Analytics
Databases /
Data
Warehouses
2880 Processing Cores
16 Terabytes Memory
(RAM) – 20TB Disk
System Specifications
90 IBM P750
Servers
80 Teraflops (80
trillion operations
per second)
Workload Optimized
Systems
In the past 5 years IBM has spent over $14B in analytical
acquisitions and $6B in R&D annually
A look behind the scenes
© 2012 International Business Machines Corporation7
Brief History of IBM Watson
R&D
Demonstration
Commercialization
Cross-industry
Applications
IBM
Research
Project
(2006 – )
Jeopardy!
Grand
Challenge
(Feb 2011)
Watson
for
Healthcare
(Aug 2011 –)
Watson
Industry
Solutions
(2012 – )
Watson
for Financial
Services
(Mar 2012 – )
Expansion
© 2012 International Business Machines Corporation8
Moving beyond Jeopardy! is a non-trivial challenge
Watson at Play Watson at Work
1 User
Max. input was two sentences
5+ days to retrain
Evidence not present
Text-only input
Q&A model
Basic security
10s of thousands concurrent users
Pages of input (e.g. medical record)
Dynamic content ingestion
Supporting evidence integral
Text, tables and images as input
Both Q&A + Conversation model
High security (e.g. HIPAA)
© 2012 International Business Machines Corporation9
Informed decision making: search vs. Watson
Decision Maker
Search Engine
Finds Documents Containing Keywords
Delivers Documents Based on Popularity
Has Question
Distills to 2-3 Keywords
Reads Documents, Finds
Answers
Finds & Analyzes Evidence Watson
Understands Question
Produces Possible Answers & Evidence
Delivers Response, Evidence & Confidence
Analyzes Evidence, Computes Confidence
Asks NL Question
Considers Answer & Evidence
Decision Maker
© 2012 International Business Machines Corporation10
Where to put Watson to work
Watson Capabilities Best Fit for Watson
Natural language
understanding
Hypothesis generation
and confidence scoring
Iterative
Question/Answering
Broad domain of
unstructured data
Machine
learning
 Problems that require the
analysis of unstructured data
 Critical questions that require
decision support with
prioritized recommendations
and evidence
 High value in decision
support
 Leverage scale to maximize
machine learning and
improve outcomes over time
© 2012 International Business Machines Corporation11
“Medicine has become
too complex. Only about
20% of the knowledge
clinicians use today is
evidence-based.”
Steven Shapiro
Chief Medical & Scientific Officer
University Pittsburgh Medical Center
Why Watson for healthcare?
© 2012 International Business Machines Corporation12
Cancer is an insidious disease
Source: American Cancer Society, National Health Institute
X
1 in 4
individuals will die from
cancer
3X
rate cancer cost climbs
vs. std. health costs or
15-18% / yr.
20%
of cancer cases
receive the wrong
diagnosis initially with
some as high as 44%
$263.8B
overall costs of cancer
in the US in 2010
$$$$$$$$$$$$
$$$$$$$$$$$$
$$$$$$$$$$$$
$$$$$$$$$$$$✔
✔
✔
IBM
+ +
Working Together to Beat Cancer
© 2012 International Business Machines Corporation13
Watson enables three classes of cognitive services
Decide
• Ingest and analyze domain sources, info models
• Generate evidence based decisions with confidence
• Learn with new outcomes and actions
• e.g. - Next generation Apps  Probabilistic Apps
Ask
• Leverage vast amounts of data
• Ask questions for greater insights
• Natural language inquiries
• e.g. - Next generation Chat
Discover
• Find the rationale for given answers
• Prompt for inputs to yield improved responses
• Inspire considerations of new ideas
• e.g. - Next generation Search  Discovery
© 2012 International Business Machines Corporation14
Drug interactions
New treatment
options
Diagnose &
treat illness
Ask
Discover
Decide
Teach Practice Pay
Med student lookup
Patient
medication inquiry
Find and preempt
fraud
Patient outcomes
are analyzed
Find treatment
code anomalies
Pre-
authorization
Watson empowers the healthcare worker
In Pilot/Production
© 2012 International Business Machines Corporation15
Imagine if…
. . . new insights from medical
research find their way to patient
treatment programs in months
instead of years?
That’s exactly what a global
leader in cancer care is doing
today.
DISCOVER
“Watson will be an invaluable resource
for our physicians and will dramatically
enhance the quality and effectiveness
of medical care.”
-Dr Sam Nussbaum,
Chief Medical Officer, WellPoint
© 2012 International Business Machines Corporation16
Imagine if…
… call center agents could
find better answers to
customer questions 50%
faster.
That’s exactly what a major
provider of financial
management software did.
ASK
“Contact centers of the future will
improve precision and personalization,
transforming centers from a cost
orientation to a strategic assets.”
- Leading Telco Supplier
© 2012 International Business Machines Corporation17
Imagine if…
DECIDE
. . . the 1.5M people
diagnosed with cancer in the
US last year had a better
prognosis?
That’s exactly what a major
health plan provider is
working to accomplish.
“Watson can aggregate information
and give probabilities that will
enable (experts) to zero in on the
most likely diagnosis.”
-Dr. Steven Nissen,
Cleveland Clinic
© 2012 International Business Machines Corporation18
18
Symptoms
UTI
Diabetes
Influenza
Hypokalemia
Renal Failure
no abdominal pain
no back pain
no cough
no diarrhea
(Thyroid Autoimmune)
Esophagitis
pravastatin
Alendronate
levothyroxine
hydroxychloroquine
Diagnosis Models
frequent UTI
cutaneous lupus
hyperlipidemia
osteoporosis
hypothyroidism
Confidence
difficulty swallowing
dizziness
anorexia
fever
dry mouth
thirst
frequent urination
Family
History
Graves’ Disease
Oral cancer
Bladder cancer
Hemochromatosis
Purpura
Patient
HistoryMedicationsFindings
supine 120/80 mm HG
urine dipstick:
leukocyte esterase
urine culture: E. Coli
heart rate: 88 bpm
Symptoms
A 58-year-old woman complains of
dizziness, anorexia, dry mouth,
increased thirst, and frequent
urination. She had also had a fever.
She reported no pain in her abdomen,
back, and no cough, or diarrhea.
A 58-year-old woman presented to her
primary care physician after several days
of dizziness, anorexia, dry mouth,
increased thirst, and frequent urination.
She had also had a fever and reported that
food would “get stuck” when she was
swallowing. She reported no pain in her
abdomen, back, or flank and no cough,
shortness of breath, diarrhea, or dysuria
Family
History
Her family history included oral and
bladder cancer in her mother,
Graves' disease in two sisters,
hemochromatosis in one sister, and
idiopathic thrombocytopenic
purpura in one sister
Patient
History
Her history was notable for cutaneous
lupus, hyperlipidemia, osteoporosis,
frequent urinary tract infections, a left
oophorectomy for a benign cyst, and
primary hypothyroidism, diagnosed a
year earlier
Her medications were levothyroxine,
hydroxychloroquine, pravastatin, and
alendronate.
MedicationsFindings
A urine dipstick was positive for
leukocyte esterase and nitrites. The
patient was given a prescription for
ciprofloxacin for a urinary tract
infection. 3 days later, patient
reported weakness and dizziness.
Her supine blood pressure was
120/80 mm Hg, and pulse was 88.
• Extract Symptoms from record
• Use paraphrasings mined from text to handle
alternate phrasings and variants
• Perform broad search for possible diagnoses
• Score Confidence in each diagnosis based on
evidence so far
• Identify negative Symptoms
• Reason with mined relations to explain away
symptoms (thirst is consistent w/ UTI)
• Extract Family History
• Use Medical Taxonomies to generalize medical
conditions to the granularity used by the models
• Extract Patient History• Extract Medications
• Use database of drug side-effects
• Together, multiple diagnoses may best explain
symptoms
• Extract Findings: Confirms that UTI was present
Most Confident Diagnosis: DiabetesMost Confident Diagnosis: UTIMost Confident Diagnosis: EsophagitisMost Confident Diagnosis: Influenza
Putting the pieces together at point of impact can be life changing
© 2012 International Business Machines Corporation19
We have only just begun to build a
new era of computing powered by
cognitive systems
 Transforming how organizations think, act,
and operate
 Learning through interactions
 Delivering evidence based responses driving
better outcomes
© 2012 International Business Machines Corporation20
JOHN M. KUNDTZ – Data Center Optimization Executive
Mr. Kundtz has over two decades of experience as a Management Consultant and Business Development Executive
with a focus on complex Enterprise Solutions within multiple industries including finance, healthcare,
manufacturing, education, government, and not-for-profit. Recognized for innovative and creative problem
solving with a proven track record of business development and outstanding engagement delivery that meet
clients’ objectives.
John is currently a Senior Principal Consultant / Business Development Executive for IBM’s Global Complex
Opportunity Support (GCOS), John is responsible for developing and closing large complex solutions across the
globe. His, team of experienced Consultants, Architects, and Project Managers assist our clients with complex IT
Transformation and Data Center Optimization engagements. We lead the development and creation of the
methodologies and techniques required for successful IT Transformation and Data Center Optimization, including
delivery transformation activities and the best tools to develop the best solution at the lowest cost.
Before joining GCOS, John lead a team of data center sales specialists working with clients throughout the Eastern
United States, John and his team were responsible for helping clients identify requirements, assess current
capabilities, and review best options for their data centers. This included consulting and implementation services
to provide assessments and strategy input, updating and optimizing data center facilities, and consolidating and
relocating I/T equipment and overall IT and data centers infrastructure optimization resulting in a reduction in
costs and improved operations.
In 2010, John was honored by Northeast Ohio Inside Business Magazine as one of the region’s most influential
technology people.
As a past member of the Faculty of IBM’s Executive Consulting Institute as a Methodology Instructor, during his tenure
as an instructor, John worked in Japan, Ireland, and Belgium and as a result is well versed in cultural orientation
and cognitive styles required to conduct business in today’s global marketplace.
Mr. Kundtz has spoken and published on a variety of topics relating to Data Center Optimization, Smarter Data Center,
Analytics as well as Systems Management and Networking. He is well versed in the business and technical
issues impacting today’s organizations as they seek to leverage their IT assets for competitive advantage.
Follow John on Twitter @jmkundtz or connect on LinkedIn http://www.linkedin.com/in/jkundtz
© 2012 International Business Machines Corporation21

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Watson – Beyond Jeopardy

  • 1. © 2012 International Business Machines Corporation Watson – Beyond Jeopardy University of Dayton – 3 April 2013 Follow us @IBMWatson John M. Kundtz, Senior Principal Consultant IBM Global Complex Opportunity Support @JMKundtz jkundtz@us.ibm.com
  • 2. © 2012 International Business Machines Corporation2 Result of IBM Research “Grand Challenge” On February 14, 2011, IBM Watson made history
  • 3. © 2012 International Business Machines Corporation3 Agenda What is IBM Watson and why is it important? How is IBM putting Watson to work? What can we expect in the future?
  • 4. © 2012 International Business Machines Corporation4 Businesses are “dying of thirst in an ocean of data” 1 in 2 business leaders don’t have access to data they need 83% of CIOs cited BI and analytics as part of their visionary plan 2.2X more likely that top performers use business analytics 80% of the world’s data today is unstructured 90% of the world’s data was created in the last two years 1 Trillion connected devices generate 2.5 quintillion bytes data / day
  • 5. © 2012 International Business Machines Corporation5 Understands natural language and human communication Adapts and learns from user selections and responses Generates and evaluates evidence-based hypothesis …built on a massively parallel architecture optimized for IBM POWER7 IBM Watson combines transformational technologies 1 2 3
  • 6. © 2012 International Business Machines Corporation6 Big Data Content Analytics IBM Technology Depth Business Analytics Databases / Data Warehouses 2880 Processing Cores 16 Terabytes Memory (RAM) – 20TB Disk System Specifications 90 IBM P750 Servers 80 Teraflops (80 trillion operations per second) Workload Optimized Systems In the past 5 years IBM has spent over $14B in analytical acquisitions and $6B in R&D annually A look behind the scenes
  • 7. © 2012 International Business Machines Corporation7 Brief History of IBM Watson R&D Demonstration Commercialization Cross-industry Applications IBM Research Project (2006 – ) Jeopardy! Grand Challenge (Feb 2011) Watson for Healthcare (Aug 2011 –) Watson Industry Solutions (2012 – ) Watson for Financial Services (Mar 2012 – ) Expansion
  • 8. © 2012 International Business Machines Corporation8 Moving beyond Jeopardy! is a non-trivial challenge Watson at Play Watson at Work 1 User Max. input was two sentences 5+ days to retrain Evidence not present Text-only input Q&A model Basic security 10s of thousands concurrent users Pages of input (e.g. medical record) Dynamic content ingestion Supporting evidence integral Text, tables and images as input Both Q&A + Conversation model High security (e.g. HIPAA)
  • 9. © 2012 International Business Machines Corporation9 Informed decision making: search vs. Watson Decision Maker Search Engine Finds Documents Containing Keywords Delivers Documents Based on Popularity Has Question Distills to 2-3 Keywords Reads Documents, Finds Answers Finds & Analyzes Evidence Watson Understands Question Produces Possible Answers & Evidence Delivers Response, Evidence & Confidence Analyzes Evidence, Computes Confidence Asks NL Question Considers Answer & Evidence Decision Maker
  • 10. © 2012 International Business Machines Corporation10 Where to put Watson to work Watson Capabilities Best Fit for Watson Natural language understanding Hypothesis generation and confidence scoring Iterative Question/Answering Broad domain of unstructured data Machine learning  Problems that require the analysis of unstructured data  Critical questions that require decision support with prioritized recommendations and evidence  High value in decision support  Leverage scale to maximize machine learning and improve outcomes over time
  • 11. © 2012 International Business Machines Corporation11 “Medicine has become too complex. Only about 20% of the knowledge clinicians use today is evidence-based.” Steven Shapiro Chief Medical & Scientific Officer University Pittsburgh Medical Center Why Watson for healthcare?
  • 12. © 2012 International Business Machines Corporation12 Cancer is an insidious disease Source: American Cancer Society, National Health Institute X 1 in 4 individuals will die from cancer 3X rate cancer cost climbs vs. std. health costs or 15-18% / yr. 20% of cancer cases receive the wrong diagnosis initially with some as high as 44% $263.8B overall costs of cancer in the US in 2010 $$$$$$$$$$$$ $$$$$$$$$$$$ $$$$$$$$$$$$ $$$$$$$$$$$$✔ ✔ ✔ IBM + + Working Together to Beat Cancer
  • 13. © 2012 International Business Machines Corporation13 Watson enables three classes of cognitive services Decide • Ingest and analyze domain sources, info models • Generate evidence based decisions with confidence • Learn with new outcomes and actions • e.g. - Next generation Apps  Probabilistic Apps Ask • Leverage vast amounts of data • Ask questions for greater insights • Natural language inquiries • e.g. - Next generation Chat Discover • Find the rationale for given answers • Prompt for inputs to yield improved responses • Inspire considerations of new ideas • e.g. - Next generation Search  Discovery
  • 14. © 2012 International Business Machines Corporation14 Drug interactions New treatment options Diagnose & treat illness Ask Discover Decide Teach Practice Pay Med student lookup Patient medication inquiry Find and preempt fraud Patient outcomes are analyzed Find treatment code anomalies Pre- authorization Watson empowers the healthcare worker In Pilot/Production
  • 15. © 2012 International Business Machines Corporation15 Imagine if… . . . new insights from medical research find their way to patient treatment programs in months instead of years? That’s exactly what a global leader in cancer care is doing today. DISCOVER “Watson will be an invaluable resource for our physicians and will dramatically enhance the quality and effectiveness of medical care.” -Dr Sam Nussbaum, Chief Medical Officer, WellPoint
  • 16. © 2012 International Business Machines Corporation16 Imagine if… … call center agents could find better answers to customer questions 50% faster. That’s exactly what a major provider of financial management software did. ASK “Contact centers of the future will improve precision and personalization, transforming centers from a cost orientation to a strategic assets.” - Leading Telco Supplier
  • 17. © 2012 International Business Machines Corporation17 Imagine if… DECIDE . . . the 1.5M people diagnosed with cancer in the US last year had a better prognosis? That’s exactly what a major health plan provider is working to accomplish. “Watson can aggregate information and give probabilities that will enable (experts) to zero in on the most likely diagnosis.” -Dr. Steven Nissen, Cleveland Clinic
  • 18. © 2012 International Business Machines Corporation18 18 Symptoms UTI Diabetes Influenza Hypokalemia Renal Failure no abdominal pain no back pain no cough no diarrhea (Thyroid Autoimmune) Esophagitis pravastatin Alendronate levothyroxine hydroxychloroquine Diagnosis Models frequent UTI cutaneous lupus hyperlipidemia osteoporosis hypothyroidism Confidence difficulty swallowing dizziness anorexia fever dry mouth thirst frequent urination Family History Graves’ Disease Oral cancer Bladder cancer Hemochromatosis Purpura Patient HistoryMedicationsFindings supine 120/80 mm HG urine dipstick: leukocyte esterase urine culture: E. Coli heart rate: 88 bpm Symptoms A 58-year-old woman complains of dizziness, anorexia, dry mouth, increased thirst, and frequent urination. She had also had a fever. She reported no pain in her abdomen, back, and no cough, or diarrhea. A 58-year-old woman presented to her primary care physician after several days of dizziness, anorexia, dry mouth, increased thirst, and frequent urination. She had also had a fever and reported that food would “get stuck” when she was swallowing. She reported no pain in her abdomen, back, or flank and no cough, shortness of breath, diarrhea, or dysuria Family History Her family history included oral and bladder cancer in her mother, Graves' disease in two sisters, hemochromatosis in one sister, and idiopathic thrombocytopenic purpura in one sister Patient History Her history was notable for cutaneous lupus, hyperlipidemia, osteoporosis, frequent urinary tract infections, a left oophorectomy for a benign cyst, and primary hypothyroidism, diagnosed a year earlier Her medications were levothyroxine, hydroxychloroquine, pravastatin, and alendronate. MedicationsFindings A urine dipstick was positive for leukocyte esterase and nitrites. The patient was given a prescription for ciprofloxacin for a urinary tract infection. 3 days later, patient reported weakness and dizziness. Her supine blood pressure was 120/80 mm Hg, and pulse was 88. • Extract Symptoms from record • Use paraphrasings mined from text to handle alternate phrasings and variants • Perform broad search for possible diagnoses • Score Confidence in each diagnosis based on evidence so far • Identify negative Symptoms • Reason with mined relations to explain away symptoms (thirst is consistent w/ UTI) • Extract Family History • Use Medical Taxonomies to generalize medical conditions to the granularity used by the models • Extract Patient History• Extract Medications • Use database of drug side-effects • Together, multiple diagnoses may best explain symptoms • Extract Findings: Confirms that UTI was present Most Confident Diagnosis: DiabetesMost Confident Diagnosis: UTIMost Confident Diagnosis: EsophagitisMost Confident Diagnosis: Influenza Putting the pieces together at point of impact can be life changing
  • 19. © 2012 International Business Machines Corporation19 We have only just begun to build a new era of computing powered by cognitive systems  Transforming how organizations think, act, and operate  Learning through interactions  Delivering evidence based responses driving better outcomes
  • 20. © 2012 International Business Machines Corporation20 JOHN M. KUNDTZ – Data Center Optimization Executive Mr. Kundtz has over two decades of experience as a Management Consultant and Business Development Executive with a focus on complex Enterprise Solutions within multiple industries including finance, healthcare, manufacturing, education, government, and not-for-profit. Recognized for innovative and creative problem solving with a proven track record of business development and outstanding engagement delivery that meet clients’ objectives. John is currently a Senior Principal Consultant / Business Development Executive for IBM’s Global Complex Opportunity Support (GCOS), John is responsible for developing and closing large complex solutions across the globe. His, team of experienced Consultants, Architects, and Project Managers assist our clients with complex IT Transformation and Data Center Optimization engagements. We lead the development and creation of the methodologies and techniques required for successful IT Transformation and Data Center Optimization, including delivery transformation activities and the best tools to develop the best solution at the lowest cost. Before joining GCOS, John lead a team of data center sales specialists working with clients throughout the Eastern United States, John and his team were responsible for helping clients identify requirements, assess current capabilities, and review best options for their data centers. This included consulting and implementation services to provide assessments and strategy input, updating and optimizing data center facilities, and consolidating and relocating I/T equipment and overall IT and data centers infrastructure optimization resulting in a reduction in costs and improved operations. In 2010, John was honored by Northeast Ohio Inside Business Magazine as one of the region’s most influential technology people. As a past member of the Faculty of IBM’s Executive Consulting Institute as a Methodology Instructor, during his tenure as an instructor, John worked in Japan, Ireland, and Belgium and as a result is well versed in cultural orientation and cognitive styles required to conduct business in today’s global marketplace. Mr. Kundtz has spoken and published on a variety of topics relating to Data Center Optimization, Smarter Data Center, Analytics as well as Systems Management and Networking. He is well versed in the business and technical issues impacting today’s organizations as they seek to leverage their IT assets for competitive advantage. Follow John on Twitter @jmkundtz or connect on LinkedIn http://www.linkedin.com/in/jkundtz
  • 21. © 2012 International Business Machines Corporation21

Editor's Notes

  1. Main point: Data is growing at an astounding rate. It is growing so fast that we often lack the ability to use it to its full potential. The highly unstructured nature of this data makes the challenge that much more difficult. This is a real problem for business. It makes informed decisions more difficult to make. Business leaders need a way to find hidden patterns and isolate the valuable nuggets that they need to make business decisions.Further speaking points: Yet, the rewards for finding a way to harness the data into useful information are great; 54% of companies in this year’s study with MIT/Sloan are using analytics for competitive advantage… and that number has surged 57% in just the past 12 months. “Dying of thirst in an ocean of data”… It’s an apt analogy. Data is everywhere. 90% of it didn't exist just two years ago. The vast majority of it is totally useless for any given goal and therefore amounts to noise and a hindrance to finding the key useful information needed in a specific time and place. Additional information: See information and stats
  2. Main Point: At the core of what makes Watson different are three powerful technologies - natural language, hypothesis generation, and evidence based learning. But Watson is more than the sum of its individual parts. Watson is about bringing these capabilities together in a way that’s never been done before resulting in a fundamental change in the way businesses look at quickly solving problemsSolutions that learn with each iterationCapable of navigating human communicationDynamically evaluating hypothesis to questions askedResponses optimized based on relevant dataIngesting and analyzing Big DataDiscovering new patterns and insights in secondsFurther speaking points:. Looking at these one by one, understanding natural language and the way we speak breaks down the communication barrier that has stood in the way between people and their machines for so long. Hypothesis generation bypasses the historic deterministic way that computers function and recognizes that there are various probabilities of various outcomes rather than a single definitive ‘right’ response. And adaptation and learning helps Watson continuously improve in the same way that humans learn….it keeps track of which of its selections were selected by users and which responses got positive feedback thus improving future response generationAdditional information: The result is a machine that functions along side of us as an assistant rather than something we wrestle with to get an adequate outcome
  3. Main Idea: Watson is greater than the sum of its parts. However, it does have some familiar capabilities that have their roots in proven commercially available IBM offerings. And while the system specs on the left allowed Watson to process 200M pages of information in three seconds, this was a purpose-built configuration specific to the demands of answering a question in the same amount of time it takes to read it… not necessarily the same requirements of other applications. Further speaking points: Watson is the result of tremendous investment of time, resources, and ingenuity on the part of IBM. IBM spends over $6B in R&D annually. Watson was part of that investment and took five years of hard work to create. For Jeopardy, Watson held nearly twice the information contained in the US Library of Congress in instantly accessible RAM memory. On the software side, its information management capabilities combine to deliver deep content analysis and evidence based reasoning that connect widely disparate sources of information and make the kinds of connections that we as humans make. Except it never gets tired, never has an off day, and never forgets.Additional Information: Capabilities like content analytics, business analytics, big data, database and data warehouses are areas where IBM has led the market for years and which form the backbone of Watson’s strength.
  4. 75 new clinical trials start every day in the US alone .Source: Public Library of Science, oncologybiomarkers.com, NCCR$750B or 30 cents of every dollar spent on healthcare in the US is wasted .Source: Institute of Medicine
  5. Sources:http://www.managedcaremag.com/archives/1101/1101.cancerdrugs.htmlhttp://healthaffairs.org/blog/2011/07/28/u-s-health-spending-projected-to-grow-5-8-percent-annually/http://talkabouthealth.com/how-often-are-breast-cancer-cases-being-misdiagnosed-and-what-exactly-is-causing-these-misdiagnoses-to-occur
  6. Main point: Watson use cases can be broadly broken into three classes: Ask, Discover, and Decide. Users can ASK Watson direct questions in natural language the same way they ask friends or colleagues questions. This is in contrast to reducing an inquiry to a set of keywords and receiving a set of links to sources where their answers may (or may not) lie. People who saw Watson’s victory on the quiz show Jeopardy! will be familiar with this simplest use case. Think of this as next generation chat. Second, users can DISCOVER new insights with Watson. Examples of this could be use of Watson as a research assistant such as a biotech investigator looking for the best way to treat a disease in a specific cohort of patients. Finally, users might use Watson to help them DECIDE on the best course of action. This would be for situations where users are looking for confidence-based recommendations for their next action when they have many options to chose from such as what course of treatment to prescribe to a patient or what investment choice to make.
  7. Main point: Next let’s move to DISCOVER. Finding correlations, patterns, and relationships in a sea of data is difficult at best with today’s pervasive technology resources. That’s part of the reason it can take over ten years to bring medical research into practice for those who desperately need it. What if this could happen in months instead of years? That’s exactly what a leading cancer center is working toward today. Watson can be used to generate cohorts of patients with specific characteristics dynamically and draw upon a vast pool of medical information that doubles every five years to uncover specific (and often unexpected) findings for how to best treat them.
  8. Main point: Finally, let’s review Watson helping professionals DECIDE their next course of action. We’ve all been in situations where there is not a single ‘right’ answer but rather, a set of possible actions with various probabilities of favorable outcomes. For example, doctors face this many times daily when deciding a course of treatment for a patient. Looking more specifically at the 1.5M Americans diagnosed with cancer annually, what if they could be given a better prognosis? That’s exactly what IBM is working on with Watson to help Oncologists make more informed, evidence-based decisions with their patients. The potential benefits are overwhelming considering that over $263B was spent treating cancer in 2010 and costs have been rising at 3X the rate of the rest of healthcare. And with as much as 44% of initial cancer diagnoses being wrong, getting the right diagnosis and best treatment for the specific patient is a matter of tremendous importance. Sources:1 - $263.8B: overall costs of cancer in the U.S. in 2010Source: American Cancer Society, National Health Institute2- Cancer costs are rising about 15 to 18 percent annually -- 3x the rate of standard healthcare costs.Source: Managed Care, January 2011 and HealthAffairs Blog, July 20113- 20% of cancer cancers receive the wrong diagnosis, with some as high as 44%.Sources: Journal of Clinical Oncology, Talk about Health Blog, Sept 2011
  9. Main Point: What is in store for the future? IBM envisions a world in which cognitive capabilities are infused into more and more aspects of technology to help us live and work in better ways. But this is a long journey and we have only just begun stepping into this new era. Watson can help transform how organizations think, act, and operate as it learns through interaction and co-evolves with its users. With the unimaginable volume of information available in the world today, Watson’s evidence-based responses are improving business outcomes and changing people’s expectations for technology’s place in life. We’ve begun an exciting journey and we want to invite you to join us!
  10. Main point: Join the conversation and take the next step. Further speaking points:. Get involved and learn more about ways that Watson can help your business today. Learn more on the web. Join the conversation on twitter and facebook. See how Watson was created and is having a real impact on youtube. And above all, contact your IBM representative to your priorities and goals and how Watson can help play a part in meeting them.