TITLE: Opportunities for Machine Learning on the Internet ABSTRACT: The explosion of content and services on the internet presents an enormous number of opportunities for the application of machine learning and adaptive algorithms. However, these opportunities present themselves in many non-obvious scenarios. Although document retrieval remains an important place for learning and statistical algorithms, applications in fields as diverse as text analysis and categorization, machine vision, speech recognition, load and traffic direction and optimization, data mining, and user behavior modeling are already being successfully deployed on the internet. In this talk, I will review some of the fast growing trends, in terms of what types of businesses are being proposed and funded, and explore the potential for learning approaches in these and future companies. Finally, time permitting, I will talk about how to overcome the difficulty of getting funding through VCs and incubators for technology based companies. I hope to keep this presentation as interactive, and question driven, as possible. BIO: Shumeet Baluja received a PhD degree in computer science from Carnegie Mellon University in 1996. From 1996-1998 he was a research scientist and coordinator at Justsystem Pittsburgh Research Center. From 1998-1999, he was the Chief Scientist at Lycos, Inc., where he created and led the Research and Applied Technology Group. Currently, he is the Vice President of Research and Development at eCompanies, LLC (an internet company incubator, http://www.ecompanies.com), and an adjunct faculty member in the Computer Science Department at Carnegie Mellon University. His current research focuses on the application of learning and statistical techniques to real-world problems in document classification and retrieval, very large database data-mining and trend analysis, mass-market user interface design, and enabling technologies for utilizing the internet.