Chief Executive Officer
Dr. Oren Etzioni is Chief Executive Officer at AI2. He is Professor Emeritus, University of Washington as of October 2020 and a Venture Partner at the Madrona Venture Group since 2000. His awards include Seattle’s Geek of the Year (2013), and he has founded or co-founded several companies, including Farecast (acquired by Microsoft). He has written over 100 technical papers, as well as commentary on AI for The New York Times, Wired, and Nature. He helped to pioneer meta-search, online comparison shopping, machine reading, and Open Information Extraction.
- December 6, 2018 | Oren EtzioniDr. Oren Etzioni, Chief Executive Officer of the Allen Institute for AI and professor of computer science at the University of Washington, addresses one of the Holy Grails of AI: acquiring, representing and utilizing common-sense knowledge, during a distinguished lecture series held at the Office of Naval Research.
- February 13, 2018 | Oren EtzioniOren Etzioni, CEO of the Allen Institute for AI, gave the keynote address at the winter meeting of the Government-University-Industry Research Roundtable (GUIRR) on "Artificial Intelligence and Machine Learning to Accelerate Translational Research".
- October 4, 2017 | Oren EtzioniDoes Artificial Intelligence (AI) research result in threats to society, or will it yield beneficial technology? The talk will address these issues by describing the projects and perspective at the Allen Institute for AI (AI2) in Seattle. AI2's mission is "AI for the Common Good," as exemplified by Semantic Scholar, a search engine that utilizes AI to overcome information overload in scientific search.
- July 25, 2017 | Oren EtzioniThis video discusses the paper: Moving Beyond the Turing Test with the Allen AI Science Challenge. The field of Artificial Intelligence has made great strides forward recently, for example AlphaGo's recent victory against the world champion Lee Sedol in the game of Go, leading to great optimism about the field. But are we really moving towards smarter machines, or are these successes restricted to certain classes of problems, leaving other challenges untouched? In 2016, the Allen Institute for AI (AI2) ran the Allen AI Science Challenge, a competition to test machines on an ostensibly difficult task, namely answering 8th Grade science questions. Our motivations were to encourage the field to set its sights broader and higher by exploring a problem that appears to require modeling, reasoning, language understanding, and commonsense knowledge, to probe the state of the art on this task, and sow the seeds for possible future breakthroughs. The challenge received a strong response, with 780 teams from all over the world participating. What were the results? This article describes the competition and the interesting outcomes of the challenge.
- June 13, 2017 | Oren EtzioniAs computer automations is upon us and many jobs will change or be replaced by AIs, AI optimist Oren Etzioni, CEO, Allen Institute for AI, describes the social impacts we must consider as he paints a possible euphonic future state in which jobs will be more creative and fulfilling. About XPRIZE: XPRIZE is an educational (501c3) nonprofit organization whose mission is to bring about radical breakthroughs for the benefit of humanity, thereby inspiring the formation of new industries and the revitalization of markets that are currently stuck due to existing failures or a commonly held belief that a solution is not possible. XPRIZE addresses the world's Grand Challenges by creating and managing large-scale, high-profile, incentivized prize competitions that stimulate investment in research and development worth far more than the prize itself. It motivates and inspires brilliant innovators from all disciplines to leverage their intellectual and financial capital.
- January 5, 2017 | Oren Etzioni"I think what's missing in the AI conversation is a dose of realism. We have on the one extreme people like Kurzweil, who are fantastically optimistic but don't really have data to back up their wildly optimistic predictions. On the other hand, we have people who are very afraid, like Nick Bostrom, who's a philosopher from Oxford, or Elon Musk, who needs no introduction, and say AI is like summoning the demon, which is really religious imagery. But again, neither party has the data to base their conclusions on; it's wild extrapolations, it's metaphor (like AI is a demon), it's philosophical argumentation. I think we need to have a more measured approach, where we measure AI's performance, where we understand that superhuman success on a narrow task like Go doesn't translate to even human performance level on a broad range of tasks, the kind that people do. I like saying my six-year-old is a lot smarter than AlphaGo—he can cross the street, more or less."
- November 19, 2016 | Oren EtzioniArtificial Intelligence advocate Oren Etzioni makes a case for the life-saving benefits of AI used wisely to improve our way of life. Acknowledging growing fears about AI’s potential for abuse of power, he asks us to consider how to responsibly balance our desire for greater intelligence and autonomy with the risks inherent in this new and growing technology. Less
- December 12, 2014 | UW CSE ColloquiumDeep learning has catapulted to the front page of the New York Times, formed the core of the so-called “Google brain,” and achieved impressive results in vision, speech recognition, and elsewhere. Yet building intelligent systems requires us to go way beyond the capabilities of deep learning and today’s data-mining systems. The future of the Big Data paradigm lies in extending these powerful methods to acquire knowledge from text, databases, diagrams, images and video. We also need to reason tractably using this acquired knowledge to make sense of the world, and to draw novel conclusions.
- October 7, 2014 | Oren EtzioniDeep learning has catapulted to the front page of the New York Times, formed the core of the so-called “Google brain,” and achieved impressive results in vision, speech recognition, and elsewhere. Yet building intelligent systems requires us to go way beyond the capabilities of deep learning and today’s data-mining systems. The future of the Big Data paradigm lies in extending these powerful methods to acquire knowledge from text, databases, diagrams, images and video. We also need to reason tractably using this acquired knowledge to make sense of the world, and to draw novel conclusions.
- March 10, 2013 | Oren EtzioniOren Etzioni discusses Open Information Extraction research at the University of Washington.