Game Theory reveals the Future of Deep Learning

If you've been following my articles up to now, you'll begin to perceive, what's apparent to many advanced practitioners of Deep Learning (DL), is the emergence of Game Theoretic concepts in the design of newer architectures. This makes intuitive sense for two reasons. The first intuition is that DL systems will eventually need to tackle situations with imperfect knowledge. In fact, we've already seen this in DeepMind's AlphaGo that uses partial knowledge to tactically and strategically best the world-best human in the game of Go. The second intuition is that systems will not remain monolithic as they are now, but rather would involve multiple coordinating (or competing) cliques of DL systems.