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<pre>
                         Keynote:
    Project Alexandria – In Pursuit of Commonsense AI

                                                    Scott Yih
                                    Allen Institute for Artificial Intelligence
                                              scottyih@allenai.org




Abstract
Enabling machines with commonsense, the knowledge that virtually every person has, is an important quest
towards artificial general intelligence. In this talk, I’m going to introduce the new initiative on commonsense AI,
Project Alexandria, at Allen Institute for Artificial Intelligence (AI2). I will first describe briefly the vision of this
project and review some of the past research efforts on commonsense knowledge representation and reasoning,
explaining why it is a difficult problem. In order to encourage the community to make progress on commonsense
AI, our focus in the first year of Project Alexandria is to create a large-scale benchmark dataset. I will talk
about our latest work on producing natural commonsense questions by pairing crowd workers to play games,
and share some of the lessons we learned.

Bio
Scott Wen-tau Yih a Principal Research Scientist at Allen Institute for Artificial Intelligence (AI2). His research
interests include natural language processing, machine learning and information retrieval. Yih received his
Ph.D. in computer science at the University of Illinois at Urbana-Champaign. His work on joint inference using
integer linear programming (ILP) has been widely adopted in the NLP community for numerous structured
prediction problems. Prior to joining AI2, Yih has spent 12 years at Microsoft Research, working on a variety of
projects including email spam filtering, keyword extraction and search & ad relevance. His recent work focuses on
continuous representations and neural network models, with applications in knowledge base embedding, semantic
parsing and question answering. Yih received the best paper award from CoNLL-2011, an outstanding paper
award from ACL-2015 and has served as area co-chairs (HLT-NAACL-12, ACL-14, EMNLP-16,17,18), program
co-chairs (CEAS-09, CoNLL-14) and action/associated editors (TACL, JAIR) in recent years. He is also a co-
presenter for several tutorials on topics including Semantic Role Labeling (NAACL-HLT-06, AAAI-07), Deep
Learning for NLP (SLT-14, NAACL-HLT-15, IJCAI-16), NLP for Precision Medicine (ACL-17, AAAI-18).




Copyright © by the paper’s authors. Copying permitted for private and academic purposes.
In: Joint Proceedings of the First International Workshop on Professional Search (ProfS2018); the Second Workshop on Knowledge
Graphs and Semantics for Text Retrieval, Analysis, and Understanding (KG4IR); and the International Workshop on Data Search
(DATA:SEARCH’18). Co-located with SIGIR 2018, Ann Arbor, Michigan, USA – 12 July 2018, published at http://ceur-ws.org




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