Alessandro Negro, Chief Scientist at GraphAware, explores why the future of artificial intelligence lies at the intersection of graph technology and machine learning.
He demonstrates that graphs are far more than just a storage solution; they are a pervasive force throughout the entire ML lifecycle. From serving as a sophisticated data source that handles complex relationships and data sparsity, to providing an intuitive structure for storing models like Markov chains and decision trees, graphs offer a level of context that traditional flat data structures simply cannot match.