watson and the new era of cognitive systems - ipp.pt - ruicoentro.pdf · watson and the new era of...

Rui Coentro

University Relations Manager

Center for Advanced Studies (CAS) Manager

Global Technology Services Delivery Manager

Watson and the new era

of cognitive systems

© 2013 IBM Corporation

Multi-Layer Neural Network

2

“bat”

Each simple building block is a connection of neurons which produces a

higher-order, more complex representation of the input

Neurons in one layer are connected to neurons in the next layer


For regression problems, sum-of-squared error is used

For classification problems, cross-entropy is used

Define Objective Function

3

Error

ref=y

© 2013 IBM Corporation 4

In vision, each layer of the neural

network is mimicking how

humans process images

Why Deep Networks Are Important

In speech, layers are learning speaker

adaptation and discrimination, no need for

separate modules for each processing

stage as we previously did


Deep Neural Network Applications

Pre-training, hardware improvements and parameter reduction

encourage deeper networks

Deep Neural Networks (DNNs) have been successfully applied

across a variety of pattern recognition tasks

–Acoustic Modeling for Speech Recognition

–Language Modeling for Speech Recognition

–Image Recognition

–Natural Language Processing

–Information Retrieval

–Multimodal Processing

–Regression Problems

5

© 2014 International Business Machines Corporation 6

Experts build expertise through cognition

Observe

Interpret

&

Evaluate

Decide Cognition


The volume, variety and

velocity of data is creating

an unprecedented opportunity.

2.5B gigabytes of new data are generated every day, 4/5ths of which is unstructured.

8


Watson is creating a new partnership between people

and computers that enhances, scales and accelerates human

expertise.


IBM can put Watson to work for you

Exploration Visually depict and

analyze data for

clear advice

Decision Help users make

more informed

evidence-based

decisions

Discovery Help people create

new insights by

synthesizing

information

Engagement Helps organizations

build stronger

relationships with

constituents


Meaningful insights are only gained when data

reveals a universe of relationships

Genes

Chemical

Compounds

Diseases

Patients Animal Models

FDA Orange

Book/Moieties

Cells Patents Drugs

Plant

Biology

®™

How it works video – 8 min. (https://www.youtube.com/watch?v=_Xcmh1LQB9I)


Watson is the culmination of several cognitive

technologies


Visualizes with Supporting Evidence

Learns Through Expert Training

Understands Scientific Entities & Relationships

Integrates All Types of Big Data Ingest

Learn

Test

Experience

Watson enables insights by connecting and analyzing hundreds of

internal and external data sources in minutes rather than weeks


Learn

Test

Experience

Ingest

16M+ patents from

US, Europe, WIPO

23M+ abstracts

100+ journals

50+ books

11,000+ drug labels

20,000+ genes

12M+ chemical

structures Watson Corpus

Over 1TB of data

Over 40m

documents

Over 100m entities

and relationships

Internal Data

In vitro tests

In vivo studies

Compounds

Toxicology reports

Clinical trial data

Lab notes

Other

Available External Data

Chemical database

Public genomics

Medical textbooks

Medline

Other journals

FDA drugs/labels

Patents

Not just a search engine, Watson understands and

interprets the language of science


Learn

Test

Experience

Ingest

Diagram

Formula

Names

(149)

Chemical ID

Valium, Dizapam Alboral,

Aliseum,AlupramAmiprol, Asiolin,

Ansiolisina Apaurin, Apoepam, etc.

CAS# 439-14-5

C16H13CIN2O Rich dictionaries

enable Watson

to link all entity

representations

H C3

O

CI N

N

More than mere text mining, Watson can identify

relationships


Learn

Test

Experience

Ingest

Symptom

s

Arthritis

pain

Chronic

pain Fever Headache

Drug class

Antiplatelet

NSAID

Analgesic

Adverse

Effects

GI pain

Gastritis

GI bleeding

Nausea

Indications Reduce MI Reduce

stroke

Reduce

fever Reduce

pain

Anti-

Inflammatory

Aspirin Illustrative Example

Ontologies: The relationship between any entity and other scientific domains

Annotators allow Watson to read and extract appropriate

information


Learn

Test

Experience

Ingest

…doxorubicin results in extracellular signal-regulated kinase (ERK)2 activation,

which in turn phosphorylates p53 on a previously uncharacterized site, Thr55…

Extracts Preposition Recognizes preposition location on Thr55

Extracts Entities ERK2 = Protein, P53 = Protein, Thr55 = Amino Acid

Extracts Verb Maps to domain of Post Translational Modification

Recognizes subject / object relationships



ERK2

phosphorylates

p53

on

Thr55

Machine learning enables Watson to teach itself over time


Learn

Test

Experience

Ingest

Aspirin

GI Pain

Valium

Depression

Annotator

Logic

Watson Applies

Annotators to Text

Watson Creates

Knowledge Graph

• Aspirin is an antiplatelet indicated to

reduce the risk of myocardial

infarction

• Known side effects include

Gastrointestinal (GI) pain, GI upset,

ulcers, GI bleeding, and nausea

• Valium or Diazepam is a

benzodiazepine derivative, indicated

for the treatment of anxiety, muscle

spasms

• Valium may cause depression,

suicidal ideation, hyperactivity,

agitation, aggression, hostility…

• Drug = entity

• Side effect = entity

association cause

• Cause = relating verb

• Rule = 1 drug to 1

side effect

Machine learning also enables Watson to learn from

experts


Learn

Test

Experience

Ingest

Aspirin

GI Pain

Valium

Depression

Watson Creates

Knowledge Graph

Drugs can

have more

than one

side effect

Expert

Intervention

Watson Applies Annotators &

Refines Knowledge Graph

Aspirin

GI Pain

GI Upset

Nausea

Ulcers

GI Bleed

Depression

Valium

Agitation

Aggression

Hostility

Hyperactivity

Beyond mere algorithms, Watson evaluates supporting

evidence


Learn

Test

Experience

Ingest • Quantity

• Proximity

• Relationship

• Domain Truths/

Business Rules

What genes

contribute to

developing

colon cancer?

Search

Corpus

Extract

Evidence Score & Weigh Question

• Side Effects

• Lab Notes

• Genes

• Publications

• Drugs

• Animal Models

• Clinical Trial

Data

The Result: Watson enables breakthrough insights after analyzing

thousands of articles and other corpus data in minutes


Learn

Test

Experience

Ingest

Gene Network

csnk1dros1 pdlim7

prkcg

aurka

nrgn

cdc20ugcg

hist1h1c

ca2

dach1

prb3

ccnb11

ppm1d

tp53inp1

mms

tpt1csnk2a1

mapk1

plk1

csnk1g2

ppp2r4

cdk7

gfm1

mapk14

mdm2hipk4

arl2

mapkapk2

cdk1

dyrk2

mapk8

chek1

tceal1

h2afx

brca1

jun

card16

atm

atr

stat3

cdk5

plk3

cdk9

mapk10chek2

ep300mapk9

nuak1mgst1

pdik1lptch1

tgm2

cdc25c

ccne1dnm1l

krt20kat2b

bbc3

stk11

nr1h2

cdk2

chmp1a

aldh1l1

slco6a1

e2f1

prrt2 csnk1a1tmprss11d

ephb2bard1

ptk2b

agt

cdkn2a

ccn2a

ptgs2

hdac6vhl

tbppin1

sgsm3

dyrk1aprkdc

des

dusp26

tp53

csnk1dros1 pdlim7

prkcg

aurka

nrgn

cdc20ugcg

hist1h1c

ca2

dach1

prb3

ccnb11

ppm1d

tp53inp1

mms

tpt1csnk2a1

mapk1

plk1

csnk1g2

ppp2r4

cdk7

gfm1

mapk14

mdm2hipk4

arl2

mapkapk2

cdk1

dyrk2

mapk8

chek1

tceal1

h2afx

brca1

jun

card16

atm

atr

stat3

cdk5

plk3

cdk9

mapk10chek2

ep300mapk9

nuak1mgst1

pdik1lptch1

tgm2

cdc25c

ccne1dnm1l

krt20kat2b

bbc3

stk11

nr1h2

cdk2

chmp1a

aldh1l1

slco6a1

e2f1

prrt2 csnk1a1tmprss11d

ephb2bard1

ptk2b

agt

cdkn2a

ccn2a

ptgs2

hdac6vhl

tbppin1

sgsm3

dyrk1aprkdc

des

dusp26

tp53

60534927591476718347480Proto-Oncogene Proteins

141062882603331334542169757Phosphorylation

19045070423056756308401Cell Cycle

75224756202167488821588076Cell Line

4106135439013003642528911125571728Humans

8943133032023216123305620060Apoptosis

137131016023957713092515820178Mice

27206382254401022216311004235507Animals

439241028910736465036465Tumor Suppressor Protein p53

2230471239721062969612327Aged

3942162138117609900130313252Mutation

268225416411321262984714728Middle Aged

623391893366485163922215559Signal Transduction

750

0

0

0

chek1

1745

255

0

198

cdk2MeSH Name Total pik3ca p53 braf chek2 epha2

Adult 12112 763 10291 928 144 47

Phosphatidylinositol 3-Kinases 11066 10726 0 271 0 0

Immunohistochemistry 10127 710 8930 309 38 57

Protein-Serine-Threonine Kinases 7413 2076 2600 162 1287 0

60534927591476718347480Proto-Oncogene Proteins

141062882603331334542169757Phosphorylation

19045070423056756308401Cell Cycle

75224756202167488821588076Cell Line

4106135439013003642528911125571728Humans

8943133032023216123305620060Apoptosis

137131016023957713092515820178Mice

27206382254401022216311004235507Animals

439241028910736465036465Tumor Suppressor Protein p53

2230471239721062969612327Aged

3942162138117609900130313252Mutation

268225416411321262984714728Middle Aged

623391893366485163922215559Signal Transduction

750

0

0

0

chek1

1745

255

0

198

cdk2MeSH Name Total pik3ca p53 braf chek2 epha2

Adult 12112 763 10291 928 144 47

Phosphatidylinositol 3-Kinases 11066 10726 0 271 0 0

Immunohistochemistry 10127 710 8930 309 38 57

Protein-Serine-Threonine Kinases 7413 2076 2600 162 1287 0

High

Affinity

Moderate

Affinity

Some

Affinity

no

Affinity

• Select entities from two different ontologies (i.e.

disease/gene)

• Visualize co-occurrence

• Use statistics to spot the intersections

• Drill down to see the evidence

• Select two or more genes of interest

• See network of relationships

• Show strength, nature & proximity of the relationship

• Colored vectors indicate the nature of the interaction

• Hover over connections to see the evidence

Co-occurrence Table


Watson Discovery Advisor - Video


Watson Discovery Advisor: Accelerating breakthrough insights across life science functions

• What new ways could we target this

disease pathway?

Let’s look at all the genes identified in

every disease that are activated by this

protein

Lead & Drug Discovery

• How can we quickly identify if this

compound has a toxicity issue?

Signals from internal toxicology reports

and published studies suggest this

compound may cause serious AEs

Safety & Toxicity

Assessment

• Are there reasons for the early safety

signals that we can quickly identify?

AE reports suggest that our drug is often

being taken with dairy foods when this

side effect is being reported

Pharmacovigilance

• Does this drug have an effect on the

pathway of another disease?

There are several diseases where the

same receptors that this compound

binds to exist

Drug Repurposing

• What populations are likely to benefit

most from this intervention?

Looking at all known studies of similar

compounds, this is how this treatment

might perform in these populations

Comparative Effectiveness /

Clinical Trial Design

• What do early studies of competitors

reveal about their efficacy and safety?

Animal models revealed early

effectiveness and faster onset,

differentiating from current products

Competitive Intelligence

Watson Explorer component view

Security

Management and application development

Query

Routing

Mobile Collaboration Application

Builder

Solution

Gallery

Content

Miner

Studio

Connectivity

… CMS Email DBMS External CRM Wikis Support Social SCM File

systems

Public Cloud Hadoop

Indexing, search and analytics

Indexing Search

Content

analytics Text analytics

= available ith

Advanced Edition

Watson Explorer Applications Search • Analyze • Interpret

Watson Developer

Cloud Cognitive and information

analysis services

Question & Answer

Relationship Extraction

Concept Expansion

Personality Insights

Language Translation

Tradeoff Analytics

Message Resonance

AlchemyAPI

AlchemyVision

… more …

Private Cloud 23


Advisors

Developers Cloud

Specialties

Models

Content

Tooling

Assemble

Train

Deploy

Admin

Data Services Ingest Extract Annotate Curate

Design

Engagement Discovery

Decision Policy

Cross Industry Editions

Oncology Wealth Mgmt.

Intelligence Cooking

Target Industry Editions Powered by Watson Offerings

App Store

Healthcare

Financial Svc.

Travel . . .

Call Center

User Profiling

Research . . . Core Offerings Watson Analytics Watson Explorer

Industry Aligned Market Aligned

Visualize

Cognitive Services (APIs)

The same services are used by business partners, customers, and IBM Developers.

Reusable services form the basis for all Watson

cognitive solutions

Watson Platform built on Bluemix • Build your application using callable Watson Service

APIs

- Question Answering

- Language Identification

- Speech to text / Text to speech

- Visual Recognition

- Machine Translation

- Personality Insights

- Message Resonance

- Relationship Extraction

- Concept Expansion

- Concept Insights

- Tradeoff Analytics

- Visualization Rendering (library)

• Built on Bluemix (http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/services-catalog.html)

• Can be combined with the 100s of other available services on Bluemix

• Pre-ingested content for health and travel © 2014 International Business Machines Corporation

#ibmskills | ibm.biz/aiforcloud

Ecosystem Development

Announcing the IBM Academic Initiative for Cloud

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Start today with three simple steps


Smarter Cities: Capitalizing on new insights, creating system-wide efficiencies, collaborating in new ways

ISEP – October 2015


Vibrant cities are realizing their full potential by integrating across functions, capitalizing on new insights, creating system-wide efficiencies and collaborating in new ways

29


Energy Government Healthcare Public Safety

Prioritized Industries

Transportation Water

Solutions

Smarter City Operations

Consulting and Services

And our Smarter Cities solution portfolio is expansive

Infrastructure Planning and Management People

Intelligent Operations Center

Law enforcement, public safety, intelligence, counter fraud

Emergency management

Building management

Campus management

Transportation management

Water management

Utility network management

Asset management

Social program management

Smarter care

Health management

Educational outcomes

30

Business Partner Solutions

IBM Intelligent Operations for Water (IOW) and IBM’s Intelligent Water Portfolio

1.Water

Sourcing

2.Water

Treatment

3.Water

Storage &

Distribution

4.Waste/Storm

water

Collect &

Discharge

Recycled/Treated

• Monitor source levels (above & below ground • Optimize source “blending” • Resource Mapping • Land use analysis • Water intake flow monitor • Raw Water quality • Flood / levee Mgmnt • Contamination monitoring • Ecosystem services value

• Monitor concentration of chemicals • Water quality • Audit-ready reporting • Asset performance • Resource scheduling

• Asset condition monitoring • Work Mgmnt optimization • Predictive asset management (including failure prediction) • Cust. / Usage segments • Leak detection • Pump & Pressure Optimization • Water Quality • Theft & tampering • Meter outage / failure • Demand mgmnt / conservation • Budget, Price analyses

• Sewer discharge / overflow • Flood monitoring & modeling • Treated Water quality • Wastewater potential (chemical & energy recovery, new water)

5.Treated

Wastewater -

Other Use

• Usage optimization • Blend optimization • Run-off monitoring

HIGH-LEVEL TOP SEGMENT NEEDS

Analytics & Optimization +What-if End to End Water Lifecycle View Multi-stakeholder Collaboration Asset Management Planning, Regulatory Compliance & Audit Environmental impact

KPIs, Reports, Graphs, GIS capabilities Energy Consumption & Carbon Footprint Impact of Weather events Link to other domains (Grid, Buildings) Water value accounting Water Risk Management

TOP CROSS-SEGMENT NEEDS

Natu

ral E

co

syste

m

1 2 3 4

5

Na

tura

l E

co

syste

m

The Water market is complex and comprises 5 broad segments. This release

addresses key specific needs across segments Use Cases that may be

delivered using IOW 1.5

capabilities


Engaging Citizens

Operational Visibility

Water and wastewater agencies are focusing on several key imperatives to manage water and ensure sustainability

Optimize water and wastewater operations

Proactive operational stance versus a reactive one

Ensure accurate data on water is accessible

Revitalize water delivery infrastructure; extend asset life

Drive service quality, conservation in water-stressed areas

Capture contextual knowledge as codified business rules

Collaborate across silos

Encourage citizen participation in monitoring & reporting

Document operational expertise via work flows

Sustainable Operations

Ageing infrastructure

Quality of Services

Grey Tsunami


Water efficiency management business value

Enables water operators to reduce water loss, minimize network disruptions, make more informed decisions, drive holistic leak management

Water Efficiency Management: Non-Revenue Water

Save money - lower repair costs, extended asset life & reduced energy bills Lower business risk with preventative maintenance Become more proactive - change operational stance Improve quality of service to end users

Pressure Management

Pipe Failure Prediction

Non Revenue Water

Asset Management

Energy Reduction


1) Pressure Management. Explicitly manage to achieve network pressure targets with possibly conflicting goals. LOWER COSTS, RECAPTURE REVENUE

2) Pipe Failure Prediction. Focus on system reliability, preventive maintenance effectiveness. LOWER COSTS AND OPERATIONAL RISK

3) Asset Management + Operational Information. Proactively / Effectively manage incidents and repairs. LOWER REPAIR / MAINTENANCE EXPENSE

4) Situational Awareness. Leverage data holistically to create insights, improve water management. LOWER NETWORK RISK, IMPROVE EFFICIENCY

Water efficiency management solutions for water operators

Enables water operators to reduce water loss, minimize network disruptions, make more informed decisions, drive holistic leak management


Water efficiency management - pressure management

Data visualization

– Consolidates data from a variety of sources, e.g. SCADA, billing records…

– Provides continual visibility and understanding of pressure status

Monitoring, insight

– Generates real-time anomaly alerts

– Provides detailed trend information

Decision making

– Accepts input via intuitive user interface: desired targets at pressure critical points

– Provides recommendations for detailed equipment operational settings

Optimize network pressure – Lower energy costs, Decrease leak and burst incidence and extend life of assets


Water efficiency management - pipe failure prediction

Data visualization

– Pipe network, failure risk hotspots, risk factors distribution

Pattern analysis, modeling

– Analyzes seasonal patterns, spatial pattern, factor correlation, feature selection

– Advanced data mining (e.g. decision tree, regression, neural network)

Prediction and planning

– Failure prediction: which pipe sections are most at risk of failure

– Generate preventative maintenance plan

Identify riskiest pipes and drive preventative maintenance plans to reduce leaks and bursts. Lowers cost of expensive disruptions and improves Quality of service


Water efficiency management – asset management and operational insight

Visualization and correlation

– Synchronize asset details from an enterprise asset management

– Combine with operational information (e.g. pressure, flow, temperature)

Analysis and estimation

– Estimate cost of repair based on data

(e.g. material, age, diameter, location)

EAM integration

– Create work order in EAM system

– View status and details, GIS map view

Enhance situational awareness of operations and infrastructure by integrating and visualizing asset and work order information


Water efficiency management – situational awareness

Visibility

– Visualize near real time data, status and performance of water systems

• SCADA systems, sensors, meters, video, etc.

– Visualize real-time / near real-time data

feeds from external data sources

• GIS / geographic information system

• EAM / enterprise asset management • ERP / enterprise resource planning, etc.

Situational awareness – View relationships, patterns, correlations

– Leverage key performance indicators, business rules, standard operating procedures

– Bridge gap between physical world of control systems and realm of business decisions

Leverage data holistically to find hidden patterns, correlations - create insights to improve water management: improve decision making, enhance efficiency and reduce risk

Non-revenue water

Water conservation

Water sustainability

Wastewater management

Urban flood management

….and beyond …


Water Maturity continuum chart

40

Integrated view of Operations & Infrastructure •Situational Intelligence for better management

•Basic correlation & Reporting

•Demand trend & Patterns Forecasts

•Workflows, KPIs

Advanced analytics Leak / Theft Detection

Dynamic Pressure Optimization Weather prediction and modeling

SCADA and basic sensor systems • Basic IT applications and SCADA Security

• Ph, turbidity, chemical sensors etc.

EAM, CRM, ERP & GIS • Asset and Workforce Management

•Customer Management systems

•Financial management

•Workforce Management

Tim

e

Customer Value


Complementary solutions

Enterprise Asset Management: Integration with an Enterprise Management System provides a “closed loop” to identify, mitigate and quickly address any disruptive events – by linking predictive analytics, pressure optimization and asset management.

Video Analytics – Infrastructure Physical Security: Video is another data feed for increased situation awareness with ability to search for events and analyze patterns. It can help secure high value assets in critical operations, widely dispersed assets – by providing alerts in real time.


Use Case 1

42


Smarter Water Landing Page: ibm.com/smarterplanet/water

GIO on Water: ibm.com/ibm/gio/water

Desert Mountain video - http://www.youtube.com/watch?v=LepjT1j9wcA

City of South Bend video – http://www.youtube.com/watch?v=ZvA8q6cU2jw

watson and the new era of cognitive systems - ipp.pt - ruicoentro.pdf · watson and the new era of...

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