Colloquium
Siddharth Patwardhan
IBM T. J. Watson Research Center
Friday, February 3, 2012
1230 WEB
Refreshments 3:20 p.m.
Lecture 3:40 p.m.
Host: Ellen Riloff
Title: Building Watson: An Overview of DeepQA and the Jeopardy! Challenge
Siddharth Patwardhan
IBM T. J. Watson Research Center
Friday, February 3, 2012
1230 WEB
Refreshments 3:20 p.m.
Lecture 3:40 p.m.
Host: Ellen Riloff
Title: Building Watson: An Overview of DeepQA and the Jeopardy! Challenge
Abstract
"Over the past four years a team of IBM Research scientists set out to accomplish a grand challenge: build a computing system that rivals a human's ability to answer questions posed in natural language with speed, accuracy and confidence, while analyzing subtle meaning and other complexities in which humans excel and computers traditionally do not. The DeepQA project at IBM is designed to tackle this challenge, with the aim being to explore how advancing and integrating Natural Language Processing (NLP), Information Retrieval (IR), Machine Learning (ML), Knowledge Representation and Reasoning (KR&R) and massively parallel computation can greatly advance open-domain automatic Question Answering. In this talk, I will give an overview of the DeepQA technology and describe how it was used to build Watson, the computer system that won the Jeopardy! Challenge in February 2011. Watson has has the ability to process and analyze vast amounts of unstructured data. As a consequence, it has the potential to transform entire industries and the way people interact with computers. Its applications are many -- ranging from business intelligence to healthcare to finance to customer support, among others. I will discuss some of these in my presentation, and provide a glimpse into Watson's future."
"Over the past four years a team of IBM Research scientists set out to accomplish a grand challenge: build a computing system that rivals a human's ability to answer questions posed in natural language with speed, accuracy and confidence, while analyzing subtle meaning and other complexities in which humans excel and computers traditionally do not. The DeepQA project at IBM is designed to tackle this challenge, with the aim being to explore how advancing and integrating Natural Language Processing (NLP), Information Retrieval (IR), Machine Learning (ML), Knowledge Representation and Reasoning (KR&R) and massively parallel computation can greatly advance open-domain automatic Question Answering. In this talk, I will give an overview of the DeepQA technology and describe how it was used to build Watson, the computer system that won the Jeopardy! Challenge in February 2011. Watson has has the ability to process and analyze vast amounts of unstructured data. As a consequence, it has the potential to transform entire industries and the way people interact with computers. Its applications are many -- ranging from business intelligence to healthcare to finance to customer support, among others. I will discuss some of these in my presentation, and provide a glimpse into Watson's future."