Event Overview:
Machine learning is an area of artificial intelligence that enables computers to self-learn, without explicit programming. In e-discovery, machine-learning technologies such as Technology Assisted Review (TAR) are helping legal teams dramatically speed document review and thereby reduce its cost. TAR learns which documents are most likely relevant and feeds those first to reviewers, typically eliminating the need to review from 50 to 90 percent of a collection. Join us for a robust presentation on how Technology Assisted Reviews have revolutionized Internal Investigations and other processes. About the Speaker: John Tredennick is the founder and chief executive officer of Catalyst. A nationally known trial lawyer and longtime litigation partner at Holland & Hart, John founded Catalyst in 2000 and is responsible for its overall direction, voice and vision. To learn more about John, click here. Mike Benner, Darren McKellin, Co-Chairs William Dallyn, Alisa Dicaprio, Tracy Greenwood, Imai Jen-La Plante, John Kirch, Vice Chairs Eriko Asai, Board Liaison ACCJ Information, Communications and Technology Committee NOTE 1: This event is OFF THE RECORD. NOTE 2: If you cancel after the stated deadline, the full meeting fee will be charged to your account. Sorry, no substitutions or walk-ins. NOTE 3: If you are driving to Tokyo American Club, please inform the ACCJ in advance as arrangements must be made and a 1,100 yen parking fee will apply. Comments are closed.
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