Building WatsonAn overview of the DeepQA Project
David Ferrucci
Watson Principal Investigator and IBM Fellow
DeepQA Team @ IBM Research


A Grand Challenge Opportunity

Want to Play Chess or Just Chat?

Easy Questions?

Hard Questions?

The Jeopardy! Challenge

The Possibilities Multiply

Broad Domain

Inducing Frames

Evaluating Possibilities and Their Evidence

Keyword Evidence

Deeper Evidence

Not Just for Fun

Divide and Conquer

The Missing Link

What It Takes to compete against Top Human Jeopardy! Players

Early Experiments on Focused Content

A Few Guiding Principles

  • Specific Large Hand-Crafted Models Won’t Cut It
  • Intelligence from many diverse methods
  • Massive Parallelism is a Key Enabler

DeepQA: The Technology Behind WatsonMassively

WatsonMassively Parallel Probabilistic Evidence-Based Architecture



Goal-Oriented System-Level Metrics and Longer-Term Incentives

Extreme Collaboration

Diverse Skills ALL IN One Room

Disciplined Engineering and Evaluation

Grouping Features to produce Evidence Profiles

Evidence: Time, Popularity, Source, Classification etc.

Evidence: Puns

In-Category Learning

DeepQA: Incremental Progress in Answering Precision

NLP Components Technology Performance

Question Processing
Relation Extraction
Linguistic Frame Extraction
Passage Matching Ensemble
KAFE: Knowledge from Extracted Content

One Jeopardy! question can take 2 hours on a single 2.6Ghz Core

Run-Time Stack

Game Strategy

With Precision, Accurate Confidence and Speed, the rest was History

Potential Business Applications

Evidence Profiles from disparate data is a powerful idea

DeepQA in Continuous Evidence-Based Diagnostic Analysis

The Core Technical Team


Categories are not as simple as they seem

Toronto vs. Chicago

OpenSherlock Project »OpenSherlock Project
References »References
Building WatsonAn overview of the DeepQA Project
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