The Evolution of Decisioning in IT, and What Happens Next

PAUL VINCENT, Industry Analyst covering Application and Business Process Platforms

Abstract: Application development continues to evolve, with many technologies addressing user needs and an ever increasing volume and complexity of use cases. This keynote looks at how the current trends of development democratization, task to process automation, and low-code are impacting the interest in, and adoption, of decision technologies, and extrapolates to their evolution in the late 2020s.

Neuro-Symbolic AI and Decision Rules

Program Manager at IBM

Abstract: The fight between the symbolic and sub-symbolic schools of AI appears to be mostly over, as there seems to be a growing consensus that AI needs the two approaches to join forces, lest we will face a new AI winter. In this talk, I will look at the fast growing field of Neuro-Symbolic AI from the point of view of rules : how neural networks are used to represent, learn and execute rules, what are (some of) the associated problems and challenges, what are the benefits from these approaches and why they are important for the future of AI. I will present solutions that have been proposed for different kinds of rules, and I will focus particularly on the case of decision rules.

Knowledge Graphs: Theory, Applications and Challenges

Professor in the Oxford University Department of Computer Science

Abstract: Knowledge Graphs have rapidly become a mainstream technology that combines features of databases and AI. In this talk I will introduce Knowledge Graphs, explaining their features and the theory behind them. I will then consider some of the challenges inherent in both the theory and implementation of Knowledge Graphs and present some solutions that have made possible the development of popular language standards and robust and high-performance Knowledge Graph systems. Finally, I will illustrate the wide applicability of knowledge graph technology with example use cases including configuration management, fraud detection, semantic search & browse, and data wrangling.