Cognitive Discovery: Accelerating Technical R&D with AI

Cognitive Discovery is an overarching framework that uses AI to achieve scientific knowledge extraction and representation, to intelligently design and guide simulations, in order to drastically accelerate the pace of scientific discovery. Cognitive Discovery targets to accelerate scientific workflows in technical disciplines and provide a new generation of tools. The workflows follow the cycle: a) Massive literature review in order to understand the problem at hand. Literature refers to all aspects such as mathematical modelling, solution methods, actual computer models and HPC deployment. b) Enrichment of literature data with experimental data and formation of hypotheses. c) Running simulations to test hypotheses and generate new knowledge in order to close any knowledge gaps. All three phases suffer today major disruptions. Simply put: the volume of new literature is exploding (e.g. roughly 450K new publications in materials science are published every year, tens of thousands of papers in numerical and HPC methods need to be reviewed). IoT advances as well as advances in measuring all aspects of HPC systems create an explosion of data. High fidelity models lead to massive configuration spaces the complexity of which clearly outpaces our capability to scale and efficiently run modern HPC systems. We will showcase how AI can help dramatically improve this setting and lead to a massive acceleration for scientific discovery.