One of the most enjoyable aspects of my role as CTO for Capgemini's Business Services is being able to work with technology companies that are pioneering breakthrough innovations – and this is one of the reasons we created our global partnership with Celaton in 2016. Their work around AI and machine learning is impressive to say the least, and the industry is taking notice – Celaton recently received the 2017 Queen's Award for Enterprise in Innovation for the development of their inSTREAM offering. I've had the pleasure of collaborating with Celaton's CEO, Andrew Anderson, applying inSTREAM to improve business process transformation for our clients. In this blog, Andrew shares some of his insights on how machine learning can help manage unpredictable data volume and deliver significant benefits in finance and accounting. According to a recent study, we create a staggering 2.5 quintillion bytes of data every day.

Today, Milton Keynes based Artificial Intelligence software company, Celaton has been named a winner of the Queen's Award for Enterprise in Innovation 2017. The Queen's Awards for Enterprise are the UK's most prestigious business awards to celebrate and encourage business excellence. Established in 2004, Celaton Limited has designed and implemented a machine learning software platform which, enables better customer service, faster. An Innovation Award has been given for the development of inSTREAM . Businesses receive a plethora of content on a daily basis from customers, suppliers and staff, which is highly labour intensive to process, make actionable and gain insights from.

Celaton's intelligent automation software, inSTREAM, enables organisations to deliver better customer service, faster. Unique to inSTREAM is its ability to learn through the natural consequence of processing, watching what people do and interacting with them. It applies artificial intelligence to streamline labour intensive clerical tasks and decision making in a way that hasn't been possible before. Despite the ever increasing choice of media channels, customers continue to communicate in an unstructured and descriptive way. While it may be easy for people to understand this, it's not possible for machines because they can only understand structured formats.

Celaton today announced the release of inSTREAM version 6, its intelligent automation platform that applies sophisticated algorithms, including artificial intelligence and cognitive learning, to streamline and automate the processing of semi-structured and unstructured content. Unstructured and semi-structured unpredictable content flows into organisations every day by email, post, paper, fax, social media, web feeds and other electronic data streams and creates challenges for customers due to the cost and need for experienced staff to process it. Unique to inSTREAM is its ability to learn the pattern of content through the natural consequence of processing and monitoring human intervention. Confidence is improved through accelerated learning. Efficiency is improved through accelerated learning.

Milton Keynes, U.K. - 30 March 2016: Celaton today announced the release of inSTREAM version 6, its intelligent automation platform that applies sophisticated algorithms, including artificial intelligence and cognitive learning, to streamline and automate the processing of semi-structured and unstructured content. Unstructured and semi-structured unpredictable content flows into organisations every day by email, post, paper, fax, social media, web feeds and other electronic data streams and creates challenges for customers due to the cost and need for experienced staff to process it. Unique to inSTREAM is its ability to learn the pattern of content through the natural consequence of processing and monitoring human intervention. Confidence is improved through accelerated learning. Efficiency is improved through accelerated learning.

Lisp, etc.) are designed for off-line use. Poi,-1 is for use by a person communicating directly with a computer via a typewriter. With this in mind I have aimed at a tolerable efficiency of execution, and an ability to define and name new operations, with comprehensive monitoring facilities. On the other hand actual error messages are rather simple. At the very lowest level, the computer can be used just as a desk calculator.

Lisp, etc.) are designed for off-line use. With the above examples in mind, certain principles seem obvious. The online user can make best use of such a system by building up complex entities in small units. For example, when calculating a large expression, it is better to work out parts of it and store these parts in variables, rather than try to do the whole thing at once. In the above examples pop-1 has appeared as a language with a fixed vocabulary.