Past Events

This workshop and tutorial will focus on the promise of generative adversarial networks, or GANs: how we can exploit their benefits while minimizing their potential harm. Topics will include the nuts and bolts of generative models, their applications, generative art, and the science and theory of GANs.

Successful hardware innovation in AI will not take place in isolation, but will emerge from a rich, layered, research ecosystem ranging from material science to software engineering. This workshop will explore novel, long-term opportunities for AI hardware, and feature faculty talks, panel discussion, and a poster session.

To advance further, deep learning systems will have to become more transparent. They will need to prove they are reliable, can withstand malicious attacks, and can explain their reasoning, especially in safety-critical applications like self-driving cars. The symposium will feature faculty talks, a poster session and refreshments.