IBM Watson Innovation Day Boston, May 8 2014 Slides

Welcome to Watson Innovation

Day

© 2014 International Business Machines Corporation 4

Watson is one of IBM’ greatest innovations in its 100 year history, and now its only a click away.

Goals for today’s session:

• Ignite your imagination for how Watson can be put to work in your business changing the competitive landscape and redefining the art of the possible

• Help establish a proven and actionable business approach for you to bring Watson to market

• Demonstrate the process to build a Watson application and the tools and resources available to help you succeed.

• Describe IBM’s investment to help ensure your success in putting Watson to work, from design and development through go-to-market


Time Agenda

9:00am – 9:30amThe New Era of Computing: IBM Watson and the Watson Ecosystem

9:30am – 10:30amBehind the Scenes. The Process of Building a “Powered by Watson” Application

10:30am – 10:45am Break

10:45am – 11:15pmHow Watson is Changing the Game In Retail: Reflexis

11:15am – 11:45amHow Watson is Transforming Healthcare: Modernizing Medicine

11:45am – 12:00pm Wrap Up: Where Do I Go From Here?

12:00pm – 1:00pm Networking Lunch

1:00pm – 3:00pm “Work With Watson” Time

Agenda

What is Cognitive Computing?


On February 14, 2011

made history


Bringing Watson technology to market

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2880 CPUsSingle User

5+ days to retrainKnew Wikipedia

1 Machine1000s of users

<1 day to retrainLearned Medicine

Cloud DeliveryMillions of Users

Retraining in hoursBroad Industry Knowledge

Jeopardy

Cognitive Products

Cognitive Ecosystem


1900

Watson is ushering in a new era of computing

1950 2011

Tabulating Systems

Programmable Systems

Cognitive Systems


Understands natural language and human style communication

Adapts and learns from training, interaction, and outcomes

Generates and evaluates evidence-based hypothesis

Watson understands me.

Watson engages me.

Watson learns and improves over time.

Watson helps me discover.

Watson establishes trust.

Watson has endless capacity for insight.

Watson operates in a timely fashion.

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Cognitive computing is changing the game


IBM direct investments ($100M fund)

1. Acceleration of Watson Ecosystem2. Foster strategic alignment of brand

objectives3. Provide reference customer for new and

emerging market segments4. Access top talent and industry5. Seed market or market segment entry 6. Future acquisition potential7. Leverage broader IBM portfolio8. Provide financial return

Objective:

Investment OrientationBusiness AlignmentIndustry Focus: Healthcare, Retail, Travel, X-Industry, etc.

Market: B2B, B2B2CStage: Series A – C (typically)

Participation: Minority, venture led

T&C: Established by lead investors, no board seat

Investment orientationBusiness alignmentIndustry focus: Healthcare, Retail, Travel, X-Industry, etc.

Market: B2B, B2B2CStage: Series A – C (typically)

Participation: Minority, venture led

T&C: Established by lead investors, no board seat


Bringing Watson to market

Transforming industries and professions.

Advancing cognitive computing across the

enterprise.

Delivering the cognitive experience

to the masses.

What is the Watson Ecosystem?


Watson Ecosystem: A cognitive marketplace

Watson Developer Cloud delivers the tools,

methodologies, software developer kits and API(s) for

ISVs to build the next generation of cognitive

applications.

Watson Content Store brings together sources of free and fee data, including

general knowledge, industry-specific content,

and subject matter expertise.

Watson Talent Hub helps bridge ISVs’ resource gaps by

providing a marketplace for critical cognitive, big data, UI, and mobility

skills.

The IBM Watson Ecosystem brings the cognitive capabilities of Watson to the cloud, allowing third parties to harness Watson’s cognitive capabilities. The ecosystem is comprised of three key components:


Three ways Watson Ecosystem Program benefits partners

Watson cognitive capabilities can be a game changer by differentiating your offering in the marketplace.

The Program represents a unique opportunity to meet market demands and demonstrate leadership, innovation, and agility.

Watson cognitive capabilities can drive incremental revenue by attracting new users or growing current users.

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The Watson Content Store offers fuel for apps

A clearing house of unique and varying sources of data – general knowledge, industry specific content, and subject matter expertise – from a variety of sources.

51© 2014 International Business Machines Corporation

Content Providers

• New distribution channel• New customers & consumption model (license, subscription, transaction)

• Incremental revenue

Benefits

ISVs

• Fuel your application with thecontent needed for success

• Easily access multiple contentsources

• Test and validate content value

IBM Watson Content Store: Healthcare illustration

Clients

MedInsights Procedures

MMG Best Practices

Healthcare Platform

Watson Healthcare Cloud

MidWest Medical Group

Excel Physicians Practice

MedInsights powered by IBM Watson

Watson Platform

Medical Journals

Domain Content

Partner App

Client & Partner Content

General Content

Watson Content Store


With Watson’s Talent Hub, help is just a click away

Working with Watson

The Process of Building a “Powered by Watson” Application

18 © 2014 International Business Machines Corporation

Access Watson Developer Cloudusing Watson Experience Manager

Develop app “Powered by Watson”using APIs

Enrich Watsonwith content

Train Watson using tools and experts

Test appfunctional andnon-functional

Deploy application

The process for building your “Powered by Watson” app







Deploy application

The process for building your “Powered by Watson” app


Design and Develop “Powered by Watson” apps using the QA API

1. Design interaction and integration patterns with Watson and implement proof points as necessary

2. Establish the architecture with Watson and other components

3. Implement and model solution to scale as a product with customization

Key points






Deploy application


App Component

Other App Component(s)

Application powered by Watson using QAAPI

Pose Natural language question

Communicates with Watson using

QAAPI

Get response

Optionally, further apply Watson response

and/or other metadata

An example solution pattern used with Watson

• Design a solution with Watson as a key component

• Model the interaction patterns with Watson

• Create user experience mockups for the solution


Guidelines for interaction patterns with Watson

Use the following guidelines when evaluating the suitability of a specific solution:

• Tips for the “Ask” service • Answers must be found in the content resources ingested in

Watson • Answers must be explicit in the content; Watson cannot

synthesize answers• Answers must be discrete – Watson cannot combine information

from various documents or create an answer that is a deduction from passages it finds (future)

• Questions must not require Watson to make judgments

• Descriptive questions• Questions can be approximately one to three sentences long• Questions should require answers of a small paragraph (about

three sentences or less)


Watson works with different types of interactions

Question Type Description Example

Factoid( only supported question capability in

Jeopardy )

Simple fact regarding time, location, reference, quantity

Q: What fees are charged with XXX fund?

Descriptive Description about a topic Q: How are Roth and traditional IRAs different?

Yes /No Simple one response answers

Q: Are Roth IRA contributions tax deductible?

Procedural – How To How to question that returns list of steps

Q: How do I plan for college education?

Procedural – Troubleshooting Troubleshooting questions Q: Why did I have a fee

charged on my brokerage?

Definition Definition of industry terms Q: What is a 529 plan?

Training on each type of question enables Watson to provide a high quality experience for each user


Using the QAAPI with Watson

Integrate and Interact with Watson from Mobile or other Self Care Apps using a RESTful API

Response, confidence evidence and other response metadata can be manipulated, enriched and used part of a conversation; or to a component in the system downstream for further processing

Application Component

Configure parameters, including Basic Auth using the user id and password

for Watson Developer Cloud, POST question;

Receive question, obtain response JSON

Return JSON response and authentication token

Receive response from Watson

Send response to user or further processing


Integration with Watson – Sample JSON request / response

REQUEST

RESPONSEConfidence

Evidence

Answer #1

Code to integrate the Watson QAAPI


Code to get the answers from the Watson QAAPI


Code to render the Watson QAAPI


Access the Watson Developer Cloud using the Watson Experience Manager (WEM)

With Watson Experience Manager:

• Developers can use APIs to access Watson and test “Powered by Watson” apps

• Data Scientists can manage their content used to enrich Watson

• User experience developers can customize or create user interaction models with Watson

• Domain experts can train and test their “Powered by Watson” apps

WEM provides a role based set of tools for SME, Watson administrators, and Domain Experts


Administration Manage User Roles View Usage Reports

Configuration Configure, Style, & Theme out of the box UI Define confidence threshold

Watson Experience Manager – Configuration



1. Enrich Watson with relevant content to fuel the applications

2. Use Watson Experience Manager to upload, ingest, deploy content

3. Leverage the Watson Content Store to acquire public, subscribed or enterprise content

Key points






Deploy application


Proprietary Content

Acquire

Cleanse

Curate

Aggregate

Contract

Identify

Public Domain & Social

IBM Watson

Validate

Application Partners

Source Prepare

Ingest

Deploy

Select Content

Build Apps w/API’s

Leverage

App Users

Unstructured Data From Enterprise Apps

CRM eComm

Workforce HR

Product Catalog

Trouble Ticket

Domain Specific Content Providers

Email, Collaboration,

Open Data

ECM KMS

End Users

The content journey

Publish

Publish

Watson Content Store


Content guidelines in detail

IBM Watson requires a knowledge database (corpus) that contains information from which to formulate correct answers

Content ingested into IBM Watson means that content is processed by the system such that correct segments of data can be quickly retrieved

Content can come from a variety of sources and will have to be physically made available

Content requires a level of cleansing and curation for Watson to be effective

Proprietary Content

Acquire

Cleanse

Curate

Aggregate

Contract

Identify

Public Domain & Social

Validate

Unstructured Data From Enterprise Apps

CRM eComm

Workforce HR

Product Catalog

Trouble Ticket

Domain Specific Content Providers

Email, Collaboration,

Open Data

ECM KMS


Content ingestion – Supported contentTypes of Unstructured Data that can be Ingested in Watson

HTML Websites Domain Independent Content FAQ pages Forums Product Descriptions Product Catalog Export Product Reviews Social Network Extracts

Microsoft Word

Operational Runbook’s

Policies & Procedures

Contracts & Agreements

Terms & Conditions

PDF– Product Manuals– Financial Reports (sans graphs)– Analyst Research– User Guides– Troubleshooting Guide– Terms & Conditions– Setup & Configuration Guides– Magazines & Journals

Text

– Extracted Interaction Logs from

CRM, Trouble Ticket, Care, Media

Asset Management applications


HTML – Veterinary Critical Care Manual Example

Before content

requires more training


HTML – Veterinary Critical Care Manual Example

Guidelines Each

disease/condition has its own document

Document is broken down in the following manner:

AfterGood

content!


HTML – Medicare website

Avoid Sites that use

images instead of texts

Text information inside of an image

Content not directly usable


HTML – Product Catalog Example

Guidelines Consider one HTML

per product Consider the

structure of the HTML to be as follows:

Good Content!


PDF – Federal Benefits ebook Example

Guidelines Simple structure Straightforward format Plain text Consistent formatting

Good Content!


PDF – Market Analysis Example

Minimize Charts Complex Tables Graphs Multi column layout

with incorrect text ordering

Content not directly usable


Understand graphics (images, videos, sound …)

Ingest directly from a structured data source (Database, Datawarehouse)

There are architectural patterns and capabilities in Watson to be able to integrate with structured data sources

Nested tabular data

Call data records, sensor logs, meter data, etc.

What Watson cannot ingest yet ….


What Works?

Documents that are relevant to the use case under consideration

Understanding the validity of documents & frequency of changes

Well formed semantics – titles, sections, headings, sub-headings

What Does Not?

Access to glossary, abbreviations would be helpful and preferred

If HTML – removing headers, footers, sidebars improves responses

Corpus contain answers to the intended questions

Scanned Docs (OCR), Charts, Non-English, Password Protected, Noisy Chat Logs

Nested Tables; Image right document with no descriptions; Log & Sensor Data

Mismatch in the content ingested and the questions end users are asking

General guidance on content selection


Content crawling & curation – Items to consider

Content Acquisition

Crawling

Integration with ECM/KMS/DMS systems

Open Services for Lifecycle Collaboration

Content Curation

Cleansing, Preparation, Aggregation & Enrichment

Content Lifecycle Management

Stale content

Refreshing content

Content Metadata, Licenses & Attribution


Content crawling & curation – Example content

Based on this content one might be interested in understanding the following.

Various domain (medical health in this case) terms or concepts such as diseases, symptoms (headache, sore throat etc.), associated health conditions (asthma, diabetes etc.), vaccinations etc.

Concepts or terms expressed in different ways (flu Vs. influenza, running nose Vs. cold etc.)

Timing in terms of when the disease is more prevalent during a given year.

Statistics in terms of how many people were affected over the years.

Locations and other geo references made in the document with respect to the concepts or terms.

Co-references or relationships or associated side effects with other health conditions (Guillain–Barré Syndrome, chronic lung disease etc.), vaccination options etc.


Based on this content one might be interested in understanding the following.

Various domain (telecom in this case) terms or concepts such as equipment types (gateway, router, receiver), problems (connection issues, no audio etc.), associated conditions (correct cabling, receiver configuration, etc.), abbreviations etc.

Concepts or terms expressed in different ways (receiver Vs STB Vs DVR, router Vs gateway etc.)

Timing in terms of when a particular problem is more prevalent post service install & activation

Statistics in terms of how many people were affected over the years.

Locations and other geo references made in the document with respect to the concepts or terms.

Co-references or relationships or associated service problems with other conditions or issues (DVR Recording & Memory Capacity, Data Features & Connectivity etc.), upgrades, value added options etc.

Content crawling & curation – Example content


Watson Experience Manager – Corpus management

Content: Content Upload & Management – Not an ECM tool View Ingested Corpus Allows for on-demand corpus pre-processing & ingestion

Number of Docs Ingested as

Corpus

View Ingested Document &

CAS

Tag Each Document

Ingest into Corpus on-

demand

Upload & Delete

Documents


Train Watsonwith tools and experts

1. Watson is a cognitive system that is trained by experts and users and learns over time

2. Watson Experience Manager allows domain experts to provide training data like question and answer pairs

3. Watson is trained iteratively – follows a cycle of collecting realistic training data, running training experiments, testing, error analysis.

Key points






Deploy application


Training: Allow SME’s to enter & manage “Question & Answer” pairs Review & Approve Q&A Pairs Forms the basis for training data to help train Watson Goal is to build a representative set that enables Watson to understand the domain's

language characteristics

Drive towards a goal

Approve, Edit, Add Comments

Sample Q&A Pair Instance

Watson Experience Manager – Create Q&A pairs to help train Watson


Suite of tools for training and testing Watson Test, train, and improve the accuracy of the system SDK and a set of extensions points to develop tools to add to the

platform

Training Experiment,

Error Analysis

Key tools & capabilities – Watson common tooling platform


Test “Powered by Watson” apps (Functional and non-functional)

1. Watson Experience Manager offers ways to test the responses from Watson

2. Testing is an iterative process to improve responses; and test integration with Watson

3. In addition to functional tests, plan to perform stress tests based on user ramps, and other non functional tests.

Key points






Deploy application


Watson Experience Manager – Testing

Testing Test system by asking

questions

Additional Considerations

Confidence of the response

Evidence -where the

answer passage was

provided


Deploy “Powered by Watson” applications

1. Roll out the application using the production topology

2. Set up support teams and processes for handling user queries

3. Establish a set of metrics to be collected, with tools to support the process.

Key points






Deploy application


Deploying your “Powered by Watson” solution

• Rollout iteratively

• Create a rollout plan with the user base

• Size the system based on peak and scaled usage, failover and availability requirements and response times

• Establish SLAs and other metrics needed from the Watson Developer Cloud

• Determine any additional security provision needed

• Promote the powered by Watson application to the production zone in the Watson Developer Cloud


Summary - 3 key takeaways

123 Committed to partner success. New business unit,

HQ in NY, brings together research, development, service and go-to-market and features Innovation Hub with incubator, client solutions center and design lab

Consider the possible interaction patterns when designing your Watson app to create the optimal user experience (including factoids, descriptive, Yes/No, procedural, procedural troubleshooting and definitions).

The Watson Experience Manager (WEM), provides a platform to upload content, train Watson with question and answer pairs, and test the system by asking questions.

The process for building a Watson app involves an iterative process of integrating Watson capabilities using the QAAPI, uploading content, training Watson, and testing the application for the appropriate response.

Let’s Take a Break…

Coming Next…

Our Journey With Watson

Taking the Next Step with Watson

© 2014 International Business Machines Corporation

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How do I start my journey with IBM Watson?

1.What is the business value to the “Powered by Watson” application you intend to build?

2.Does the application draw upon the unique characteristics and capabilities of a cognitive offering?

3.Has the content that will fuel the application been identified and can it be secured/licensed for the intended use?

Have a question and answer interaction pattern, with questions posed in natural language

Seek answers and insights from a defined content repository comprised largely of unstructured data

Need transparency and supporting evidence for confidence weighted responses to questions and queries

The best use cases…


Phase 1: Engage

Join IBM Partner World at http://ibm.com/PartnerWorld

Analyze use case for Watson business and technical synergy

Submit Watson Ecosystem application and receive acceptance https://ibm.biz/watsonecosystemapply

Obtain access to the Watson Developer Cloud through the Watson Experience Manager

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Where can I go to learn more?

Apply:

https://ibm.biz/watsonecosystemapply

Share:

https://ibm.biz/watsondeveloper

Learn:

https://ibm.biz/watsonecosystem-youtube

https://ibm.biz/watsonecosystemapply

https://ibm.biz/watsondeveloper



IBM Watson Innovation Day Boston, May 8 2014 Slides

Presentations & Public Speaking

Transcript of IBM Watson Innovation Day Boston, May 8 2014 Slides