Is Your Organization’s Infrastructure Holding Back Your Adoption of AI at Scale?
Is Your Organization’s Infrastructure Holding Back Your Adoption of AI at Scale?

Abstract: 

451 Research, part of S&P Global Market Intelligence, surveys of enterprise machine learning specialists reveal that at least half of organizations believe their technology infrastructure isn’t prepared for the future demands that will be placed on it by the adoption of AI and machine learning at scale. In this session, Nick will examine why that is and how it can be overcome, via deep dives into current and future use cases across multiple industries and the strategies being adopted to ensure AI is successful at their organization.

Bio: 

Nick Patience is 451 Research’s lead analyst for AI and machine learning, an area he has been researching since 2001. He is part of the company’s Data, AI & Analytics research channel but also works across the entire research team to uncover and understand use cases for machine learning. Nick is also a member of 451 Research’s Center of Excellence for Quantum Technologies.

Nick has a long background in research into how applications can take advantage of data – in particular unstructured data – using AI and machine learning. He is a co-founder of 451 Research and re-joined the team in 2015 after almost three years running product marketing at machine learning-driven eDiscovery and information governance software company Recommind (now part of OpenText). He has held various senior management roles at 451 Research in both New York and London since 1999.

Prior to starting 451 Research, Nick was a financial and technology journalist with ComputerWire (now part of Datamonitor) in London and New York. Nick has a master's degree in computing science from the University of London, and a BA in Philosophy and Music from Middlesex University.