Computer Science ColloquiumIm Rahmen des Informatik-Kolloquiums, das von den Instituten des Fachbereichs Informatik, der Österreichischen Gesellschaft für Informatik (ÖGI), der Arbeitsgemeinschaft für Datenverarbeitung (ADV) sowie der Österreichischen Computergesellschaft (OCG) abgehalten wird, spricht
IBM T.J. Watson Research Ctr. & IBM Watson Health, Yorktown Heights, NY USAüber das Thema:
IBM Watson: Building a Question-Answering system to Beat Humans on TVZeit: Mon 30.5.2016, 15:45, 90 Minuten
Ort: HS 18
ZusammenfassungIn February of 2011, IBM's computer system called Watson participated in the US game show Jeopardy! on national television against two former champions - and won. Jeopardy! is a questionanswering challenge, which, despite including elements of speed and betting, is at its core about finding answers to questions and having a good confidence estimate about those answers. Question-answering (QA) is a sub-field of Artificial Intelligence, and Watson is acknowledged to represent the current state-of-the-art. Watson is able to answer some obscure general-knowledge questions that average people have difficulty with, so in that very limited and technical sense is super-human. On the other hand it makes regular mistakes, usually in regard to questions about common sense or common human experience (of which it has none). This talk will examine what went into Watson, to what extent it actually understands the domain it operates in, and where the technology is headed.
VortragenderJohn Prager has been working in technical fields related directly or indirectly to Question Answering for most of his professional career. Most recently, while at the IBM T.J. Watson Research Center he has been part of the Watson project, a system that played (and won) the Jeopardy! TV quizshow game. He has been involved in both the algorithms area, concentrating on question analysis and wordplay, and strategy. He is still involved with Watson, as it is being adapted to clinical decision support in the health-care domain. Previously, he led IBM?s successful entries in the TREC-QA tasks, an annual evaluation at NIST. Prior to that, he worked in various areas of Search, including Language Identification, Web Search and Categorization. While at the former IBM Cambridge Scientific Center (Cambridge, Mass), John was the project leader of the REASON (Realtime Explanation And SuggestiON) project; REASON would provide users help by taking naturallanguage questions and processing them with an inference engine tied to a large repository of facts and rules about network-wide resources. John has degrees in Mathematics and Computer Science from the University of Cambridge (Cambridge, UK) and in Artificial Intelligence from the University of Massachusetts; his publications include conference and journal papers, fifteen patents, and a book on Turing.
Einladender: Dr. Peter Knees, Institut für Computational Perception
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