If you're tracking your family tree on Ancestry.ca, your ancestors appear on nodes in graphs with the edges showing connections among them. Looking behind the screens of Facebook or LinkedIn, you'd see similar graphs that plot your networks and interactions.
Graph neural networks (GNNs) such as these are ideal for organizing and connecting vast amounts of data on social media. When deep learning methods are applied to graph edges, they extract knowledge and make predictions, track your community activity and generate recommendations. For example, Pinterest improved the performance of its recommendation system by 150% by using GNNs.
They can also serve as powerful probes into uncharted territory, opening doors to new material discovery, advanced circuit design and novel drug invention among others. By developing new graph designs, structures and properties, and using artificial intelligence (AI) and machine learning (ML) to mine information from large data sets, researchers have found immense potential for solving real‑world problems. And in the race to find a COVID-19 vaccine, this has enabled them to discover new molecules for drug development.
"Using AI graph illustrations can improve our ability to quickly predict which molecular properties among billions can be used to develop solutions for specific challenges," says Harry Guo, Research Officer at the National Research Council of Canada's (NRC) Digital Technologies Research Centre. "The GNN project, which is part of the NRC's AI for Design Challenge program, is creating methods to rapidly search and identify graph designs with the most potential for science and engineering design."
The project's state‑of‑the‑art predictive performance was recognized recently in an international MIT‑hosted competition related to AI for Design and COVID-19. The NRC's paper on the topic, prepared with collaborator Montréal, QC‑based Mila research institute in artificial intelligence, was also accepted at the 2020 International Conference on Machine Learning. This success has garnered attention that will soon lead to other projects in this cutting‑edge field.