Videos
See AI2's full collection of videos on our YouTube channel.Viewing 251-260 of 261 videos
Deep Natural Language Semantics by Combining Logical and Distributional Methods using Probabilistic Logic
November 4, 2014 | Raymond MooneyTraditional logical approaches to semantics and newer distributional or vector space approaches have complementary strengths and weaknesses.We have developed methods that integrate logical and distributional models by using a CCG-based parser to produce a detailed logical form for each sentence, and combining the…
Large-Scale Paraphrasing for Natural Language Generation
October 1, 2014 | Chris Callison-BurchI will present my method for learning paraphrases - pairs of English expressions with equivalent meaning - from bilingual parallel corpora, which are more commonly used to train statistical machine translation systems. My method equates pairs of English phrases like --thrown into jail, imprisoned-- when they…
Modeling Biological Processes for Reading Comprehension
August 5, 2014 | Jonathan BerantMachine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. In this talk, I will focus on a new reading comprehension task that requires complex reasoning over a single document. The input is a paragraph describing a…
Extracting Knowledge from Text with Tractable Markov Logic and Symmetry-Based Semantic Parsing
July 25, 2014 | Pedro DomingosBuilding very large commonsense knowledge bases and reasoning with them is a long-standing dream of AI. Today that knowledge is available in text; all we have to do is extract it. Text, however, is extremely messy, noisy, ambiguous, incomplete, and variable. A formal representation of it needs to be both…
Paul Allen Discusses AI2 and the Future of AI (Discussion of AI2 begins at 17:30)
June 4, 2014 | Paul AllenPaul Allen discusses his vision for the future of AI and AI2 in this fireside chat moderated by Gary Marcus of New York University at the 10th Anniversary Symposium - Allen Institute for Brain Science. AI2-related discussion begins at 17:30.
Crowdsourcing Insights into Problem Structure for Scientific Discovery
May 13, 2014 | Bart SelmanIn recent years, there has been tremendous progress in solving large-scale reasoning and optimization problems. Central to this progress has been the ability to automatically uncover hidden problem structure. Nevertheless, for the very hardest computational tasks, human ingenuity still appears indispensable. We…
Learning and Inference for Natural Language Understanding
March 31, 2014 | Dan RothMachine Learning and Inference methods have become ubiquitous and have had a broad impact on a range of scientific advances and technologies and on our ability to make sense of large amounts of data. Research in Natural Language Processing has both benefited from and contributed to advancements in these methods…
The Aha! Moment: From Data to Insight
February 26, 2014 | Dafna ShahafThe amount of data in the world is increasing at incredible rates. Large-scale data has potential to transform almost every aspect of our world, from science to business; for this potential to be realized, we must turn data into insight. In this talk, I will describe two of my efforts to address this problem…
Statistical Text Analysis for Social Science: Learning to Extract International Relations from the News
February 26, 2014 | Brendan O'ConnorWhat can text analysis tell us about society? Corpora of news, books, and social media encode human beliefs and culture. But it is impossible for a researcher to read all of today's rapidly growing text archives. My research develops statistical text analysis methods that measure social phenomena from textual…
Smart Machines, and What They Can Still Learn From People
January 23, 2014 | Gary MarcusFor nearly half a century, artificial intelligence always seemed as if it just beyond reach, rarely more, and rarely less, than two decades away. Between Watson, Deep Blue, and Siri, there can be little doubt that progress in AI has been immense, yet "strong AI" in some ways still seems elusive. In this talk, I…