IBM 100 – A Computer Called Watson

Theodor STANESCUtheodor.stanescu@ro.ibm.com Strategy and Architecture Services ManagerIBM ROMANIA

http://www.youtube.com/watch?v=mjdRgBAY278

Time

Co

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ute

r In

tell

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Learning Systems

Smart Systems EraSmart Systems Era

Counting Machine(Circa 1820)

ENIAC(Circa 1945)

Deep Blue (1997)

Watson (2010)

Antikythera Astronomical

Computer (ca 87 BC)

Abacus(Circa 3500 BC)

Napier’s Rods(Circa 1600)

System/360 (1964)

Tabulating EraTabulating Era

Computing EraComputing Era

We are Entering a New Era

We Have Entered a New Wave of Innovation

1770 1875 19201830 1970

Inn

ova

tio

n

Smarter Products

& Services

The Industrial Revolution

Age of Steam

and Railways

Age of Steel,

Electricityand Heavy Engineering

Age of Oil, Carsand Mass Production

Ageof IT andTelecom

Source: “Next Generation Green: Tomorrow’s Innovation Green Business Leaders”, Business Week, Feb 4, 2008

2nd Wave 5th Wave 6th Wave1st Wave 3rd Wave 4th Wave

2010

Our World is Getting Smarter

Our world is becoming

INSTRUMENTED

Our world is becoming

INTERCONNECTED

Virtually all things, processes and waysof working are becoming

INTELLIGENT

Informationfrom Everywhere

RadicalFlexibility

Extreme Scalability

• Cloud computing

• Virtualization at every level

• Automated administration

• Easy-to-use analytics

• “Big data” analytics

• Real-time stream processing

• Efficient parallelism

• Workload-optimized

• Data and content

• Apps, web and sensors

• At rest and in motion

• Integrated and federated

Macro Trends are Changing the IT Landscape

Healthcare

Oil and Gas

Energy & Utilities

Transportation

Telecommunications

Retail

Banking

Government

Electronics

Smarter Industry

Electronic Medical Records

Smart Sensoring

Smart Meters

Service Innovation

RFID Tagging

Core Banking

Digital Surveillance

Track and Trace

Asset Instrumentation

Instrument to Manage

Collaborative Care

Oilfield Modeling

Intelligent Utility Network

Congestion Management

New Services

Smarter Commerce

Market Expansion

Crime Prediction and Prevention

Supply Chain Optimization

Optimize to Transform

Health Information Exchange

Integrated Oilfield Management

Integrated Asset Management

Carrier-grade Platform

Integrated Demand/Supply Sys

Single View of the Customer

Crime Information Warehouse

Product Design Collaboration

Integrated Fare Management

Integrate to Innovate

Smarter Planet – How Clients Engage

What Is Watson?The Next Grand Challenge

Over the last century, IBM has reached numerous scientific breakthroughs through its commitment to research and its tradition of Grand Challenges. These Grand Challenges work to push science in ways that weren’t thought possible before.

Jeopardy! The IBM Challenge poses a specific question with very real business implications: Can a system be designed that applies advanced data management and analytics to natural language in order to uncover a single, reliable insight — in a fraction of a second?

“We look at areas where there's an enormous gap in current capability and use that as a challenge. We call them Grand Challenges.”

Dr. John E. Kelly IIISenior Vice President and Director of IBM Research

What Is Watson?

Watson is unique in that it

attends to heterogeneous sources

postulates multiple possible answers

considers evidence across multiple dimensions

and learns.

What Is Watson?

Watson does not

understand

nor does it think.

Statistics

Development Team 25 people

Project Duration 4 years

Software 1,000,000+ SLOC

700K Java, 300K C++,

plus other bits

~ 130 components

Hardware 90 IBM Power 750 servers

2880 Power7 cores @ 80+ TFLOPS

20 TB memory

10 Gbps network

Play and comment for the audience the movie

IBM Watson – IBM Next Grand Challenge

http://www.youtube.com/watch?v=VjHMYuGkzlU

5 minutes

• PIQUANT (Practical Intelligent Question Answering Technology) @ IBM.

• OpenEphyra @ CMU.

• UIMA (Unstructured Information Management Architecture) @ IBM -> Apache.

Related Systems

http://www.ephyra.info/

http://uima.apache.org/

http://www.research.ibm.com/UIMA/Project_QA.htm

Architecture: In Their Own Words

. . .

Hypothesis

Scoring

Models

Confidence- WeightedDifferential Diagnosis

Case/Question/Topic Data

Evidence Sources

Models

Models

Models

Models

ModelsPrimarySearch

CandidateAnswer

Generation

HypothesisGeneration

Hypothesis and Evidence Scoring

Final Merging and Confidence &

RankingSynthesis

Answer Sources

Question /Case

Analysis

Fact, Finding and Question

Decomposition

EvidenceRetrieval

Deep Evidence Scoring

HypothesisGeneration

Hypothesis and Evidence Scoring

Learned Modelshelp combine and

weigh the Evidence

Sources

• Wikipedia/Wikiquote/Wiktionary/Wikibooks (The Free Encyclopedia) @ http://wikipedia.org

• YAGO2 (A Spatially and Temporally Enhanced Knowledge Base from Wikipedia) @ http://www.mpi-inf.mpg.de/yago-naga

• Dbpedia (Extracting Structured Information from Wikipedia) @ http://dbpedia.org

• WordNet (A Lexical Database for English) @ http://wordnet.princeton.edu

• Web expansion of many primary sources.

• Various licensed encyclopedias, dictionaries, books of quotations, and wire news.

Deployment View: Watson

• 90 IBM Power 750 servers.

• 4 Power7 processors/server.

• 8 cores/processor.

• 10 TB memory/server.

• SUSE Linux Enterprise OS.

• SONAS storage @ 20 TB.

• Juniper switch @ 10 Gbps.

• 2 x 20-air conditioning units.

Deployment View: Actuator

• Players receive a clue simultaneously (humans visually/Watson electronically).

Human reaction time to a light stimulus is approximately 190 ms; Watson’s actuator reaction time is approximately 5-10 ms, giving it at best 180 ms to compute).

• Players can buzz in only after an enable light.

• Humans can anticipate; Watson cannot.

Deployment View: Avatar

• Developed by Joahua Davis and Branden Hall of Automata Studios.

• Designed using Adobe Illustrator CS5 and scripted with Adobe Flash Professional CS5 using the HYPE visual framework.

• Deployed using Adobe Flash Player 10.1.

http://www.hypeframework.org/blog/content/ibm-watson-and-the-jeopardy-challenge/

Deployment View: Voice

• Must handle a large, open-ended vocabulary with many difficult words.

• Text to speech synthesis constructed from the phonemes extracted from 10 hours of the voice of Jeff Woodman.

• Rules-based linguistic analysis front end.

• Prosody and acoustic model back-end.

http://www.anythinggoesradio.com/Interviews/JeffWoodman_02_14_11.MP3

Deployment View: Watson

Play the movie:

IBM Watson: A System Designed for Answers

http://www.youtube.com/watch?v=cU-AhmQ363I

3 minutes

Organization: Principal Investigator

David Ferrucci

Organization: Algorithms

Organization: Systems

Organization: Strategy

Organization: Speech

Organization: Annotations

Organization: Labs

Organization: Universities

Organization: Universities

Organization: Project Management

Organization: Applications

Tools

• Eclipse.

• Subversion -> RTC.

• Watson Error Analysis Tool (WEAT).

• Feature Analysis Tool (FAT).

• BlueJ Automatic Distributed Execution Environment tools (BAIDE)

• Data repository tools.

Process

• Agile development.

• War room setting.

• Weekly integration.

• End to end testing.

• ~ 6,000 experiments

• 10 gigabits of test data/week.

% Answered

Watson’s Future: New Domains

• Clinical decision support/physician’s assistant.

• Business analytics.

• Customer service.

• Legal research.

References: On The Web

http://www.ibm.com/innovation/us/watson/

http://www.ted.com/webcast/archive/event/ibmwatson

http://www.pbs.org/wgbh/nova/tech/smartest-machine-on-earth.html

http://www.youtube.com/watch?v=FC3IryWr4c8

http://www.youtube.com/watch?v=3G2H3DZ8rNc&feature=relmfu

Play the movie

IBM – A century of progresshttp://www.youtube.com/watch?v=gLlJDUPg-kY

About 2 minutes

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