Understanding the World Through Action: RL as a Foundation for Scalable Self-Supervised Learning

Machine learning systems have mastered a breadth of challenging problems in domains ranging from computer vision to speech recognition and natural language processing, and yet the question of how to design learning-enable systems that match the flexibility and generality of human reasoning remains out of reach. This has prompted considerable discussion about what the “missing ingredient’’ in modern machine learning might be, with a number of hypotheses put forward as the big question that the fi...