Dr James Stovold, Principal
Emerging Digital Technology
James is the Principal for CamIn’s Global Emerging Digital Technology Division. He is responsible for driving business development, client relations and introducing innovative digital technologies into his client’s product portfolios. With a research background in robotics, cybersecurity, internet-of-things, artificial intelligence, and industry experience across multiple verticals, James is ideally placed to integrate modern technological innovations into legacy corporate systems. James received his Masters and PhD in Computer Science and Electronics from The University of York. Since then he has worked as a lead data scientist, supporting executive directors in multiple FTSE100 companies, and as a lecturer at Swansea University.
MEng Computer Science & Electronics
University of York
PhD Computer Science & Electronics
University of York
CONNECT WITH JAMES
j.stovold [at] camin.com
+44 (0)7388 2664 65
RObotics & ai
User interaction; etc.
banking & financial services
Machine learning & AI;
Optimisation & decision making;
Robotic process automation;
Production line optimisation;
Our industries of focus in Emerging Digital Technology.
EMERGING DIGITAL TECHNOLOGY
Technology scouting and roadmapping of emerging cybersecurity technologies throughout full production value chain to solve challenges and expand service line.
Our most recent projects in Emerging Digital Technology.
Our most recent µInsight in Emerging Digital Technology.
How natural language processing will revolutionise our daily lives
Natural Language Processing is a rapidly changing field that has revolutionised the way people access required information, how they communicate with each other, and how they interact with their electronic devices. NLP technology helps to protect our inboxes from spam messages, to analyse documents to detect plagiarism, and evaluates customer opinions to build market forecasts, among many other commercial applications. NLP-based applications are now an inseparable component of our everyday lives. Consistent decreases in computational costs and increases in the amount information available for processing have led to further commercial growth in this area, and produced a diverse range of products that rely on understanding human language. Rule-based systems are being replaced by statistically-based products, which provide improved performance when supplied with increasing amounts of data, and are less dependent on the type of information being analysed. By 2020, the market for NLP applications is expected to grow to $13.4 billion at a compound annual growth rate of 18.4%.