Videos

See AI2's full collection of videos on our YouTube channel.
Viewing 241-250 of 250 videos
  • Large-Scale Paraphrasing for Natural Language Generation Thumbnail

    Large-Scale Paraphrasing for Natural Language Generation

    October 1, 2014  |  Chris Callison-Burch
    I 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 Thumbnail

    Modeling Biological Processes for Reading Comprehension

    August 5, 2014  |  Jonathan Berant
    Machine 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 Thumbnail

    Extracting Knowledge from Text with Tractable Markov Logic and Symmetry-Based Semantic Parsing

    July 25, 2014  |  Pedro Domingos
    Building 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) Thumbnail

    Paul Allen Discusses AI2 and the Future of AI (Discussion of AI2 begins at 17:30)

    June 4, 2014  |  Paul Allen
    Paul 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 Thumbnail

    Crowdsourcing Insights into Problem Structure for Scientific Discovery

    May 13, 2014  |  Bart Selman
    In 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 Thumbnail

    Learning and Inference for Natural Language Understanding

    March 31, 2014  |  Dan Roth
    Machine 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 Thumbnail

    The Aha! Moment: From Data to Insight

    February 26, 2014  |  Dafna Shahaf
    The 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 Thumbnail

    Statistical Text Analysis for Social Science: Learning to Extract International Relations from the News

    February 26, 2014  |  Brendan O'Connor
    What 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 Thumbnail

    Smart Machines, and What They Can Still Learn From People

    January 23, 2014  |  Gary Marcus
    For 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…
  • AI: A Return to Meaning Thumbnail

    AI: A Return to Meaning

    November 5, 2013  |  David Ferrucci
    Artificial Intelligence started with small data and rich semantic theories. The goal was to build systems that could reason over logical models of how the world worked; systems that could answer questions and provide intuitive, cognitively accessible explanations for their results. There was a tremendous focus on…