Bown, Oliver (University of Sydney) | Eigenfeldt, Arne (Simon Fraser University) | Hodhod, Rania (Georgia Institute of Technology) | Pasquier, Philippe (Simon Fraser University) | Swanson, Reid (University of California, Santa Cruz) | Ware, Stephen G. (North Carolina State University) | Zhu, Jichen (Drexel University)
The 2012 AIIDE Conference included four workshops: Artificial Intelligence in Adversarial Real-Time Games, Human Computation in Deigital Entertainment and AI for Serious Games, Intelligent Narrative Technologies, and Musican Metacreation. The workshops took place October 8-9, 2012 at Stanford University. This report contains summaries of the activities of those four workshops.
On Saturday, July 22nd Mitzi Morris and I (Michael Betancourt) will be hosting a day-long Stan workshop for the NYC Women in Machine Learning & Data Science Meetup Group. As with most of our workshops the emphasis will be on interactive exercises where everyone builds and running models in Stan. We'll start with the foundations of Bayesian inference and end all the way at fitting latent Gaussian process models. Everything for this course will be in Python and PyStan. If you're in the New York City area and want to attend then you can register at the event page.
Pulling together deep learning workshops for a large number of students, however, can be a time consuming, error prone, and costly exercise. Furthermore, technical issues with the environment setup and compatibility problems during the workshops impede learning and cause student dissatisfaction. These workshops typically have participants bring their laptops and have them download and install new software. However, with the wide range of laptop platforms (Windows, Mac, Linux), numerous configurations, and version conflicts with existing software, workshops can become frustrating both for presenters and attendees. The RAM and disk space available on laptops and their lack of GPUs affect the types of hands-on labs that can be offered, as deep learning workshops benefit heavily from specialized hardware such as GPUs.