The emergence of graph neural networks, which apply the techniques of deep learning to data that is naturally structured as a graph. For example, in social networks, nodes represent people and edges represent the relationships between individuals.
Using graph neural networks, businesses can take this user data and make recommendations based on a user’s features as well as their social context. In sports, we have similar social structures: teams. We can represent each player as a node and their relationship to their teammates and opponents as edges. Using graph neural networks allow us to understand how players act in the context of their team and opponents, as well as how individuals use teamwork to create better outcomes.