Collective intelligence studies the group brainpower that emerges from the interactions of many individuals. It's commonly observed in nature—for example, when a group of fish decides which direction to swim or when elephants choose where to migrate. Google Brain's David Ha, a research scientist, shares methods for using collective intelligence to improve today’s deep learning models.
The current generation of neural network models achieves state-of-the-art performance on tasks across fields spanning computer vision, natural language processing, and reinforcement learning. But as these models become larger and more complex, they suffer from issues including poor robustness, the inability to adapt to novel task settings, and other problems. Collective behavior, however, tends to produce systems that are robust, adaptable, and have less rigid assumptions about their environment configurations.
In this keynote, Ha highlights several active areas in modern deep learning research that incorporate the principles of collective intelligence to advance current capabilities, including lessons in deep reinforcement, multi-agent, and meta learning. He will provide examples from Reddit, Conway's Game of Life, Minecraft, Puzzle Pong, and more. Ha works in the Google Brain team in Japan, where his research interests include complex systems, self-organization, and creative applications of machine learning. Prior to joining Google, Ha worked at Goldman Sachs as a Managing Director.