What is Your AI Digitisation Strategy ?

The central challenge for companies dealing with huge amounts of data is a digitisation strategy. Here it comes to artificial intelligence and semantic technologies. The integration of the megatrends into enterprise procedures and workflows would be the focus one of the topics of the SEMANTiCS 2019, september in Karlsruhe which occurs from 9 to 12, where top speakers from industry and academia will explore how AI systems can help businesses flourish in the digital age.

“Explainable AI is the is the main element to acceptance and progress of AI,” says SEMANTICS 2019 General Seat Harald Sack. Explainability can make a difference in a few applications, specifically, when AI is put on humans. In other applications, it generally does not play any significant role. Some argue that our brain first acts and tries to explain why it acted in a particular way then, mainly for communication purposes maybe, to justify action and also to convince others.

In lectures, panels and workshops numerous enterprise implementation tasks and use cases will be presented which can only help to bridge that space between the complicated concepts that underpin AI and the useful applications that concretely benefit businesses.

Topics include process automation and optimization, information data and logistics management as well as business development and customer romantic relationship management. In community occasions, international high-tech experts shall also discuss the near future and need for artificial intelligence in a broader context.

The keynotes will be held by prominent experts from the European countries and US, included in this Willem Manders, Mind of Knowledge Management at Shell, Michel Dumontier, Teacher of Data Science at Maastricht University or college, Valentina Presutti, researcher at the Semantic Technology Laboratory of the Country wide Research Council (CNR) in Rome and Michael J. Sullivan, Primary Cloud Solutions Architect at Oracle.

“Those that stick to their islands shall fall back. This is currently the full case with a big part of the data which is kept in silos,” says Andreas Blumauer, managing founder and director of the Semantic Web Company, which organizes the meeting alongside FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Fachhochschule St. Pölten, and the Universities of Amsterdam and Leipzig.

“For every knowledge employee, it is a time-consuming job to recognize highly, connect, understand, and interpret the right information and dots pieces. SEMANTiCS 2019 desires showing IT decision manufacturers how companies can form their own Knowledge Graphs along the complete Connected Data Life Routine, to aid process and decision enhancement predicated on that connected data,” provides Blumauer.

For Volker Tresp, Distinguished Research Scientist at Siemens, the largest challenges ahead as it pertains to enterprises employing Machine Learning, Autonomous AI and Systems, is discovering an effective business design that works for that each company. Quite simply, there is absolutely no one-size-fits-all strategy where it involves leveraging Artificial Cleverness within your own business.

“Machine Learning is an extremely strong and incredibly robust technology. But this will not imply that each ongoing company understands how to transfer this success into a company. Currently, no ongoing company, whose continuing business is on the internet, can do without AI. If as it happens that your company comes with an AI business, then it’s likely you have to change the culture in your business significantly. You can only just achieve success if you have the ability to hire the best talent and if you change the culture in your organization such that it values, listens and appreciates compared to that skill.”

One example of an certain area where correct AI implementation can have an enormous efficiency impact is Healthcare. Hospitals generate large sums of data each full day, and patients can take advantage of the structuring of this data in to the Knowledge Graphs mentioned previously.

“AI applications in image evaluation have already been used to get more than 5 years. Siemens Healthineers have been doing pioneering work and will work on many future use instances,” explains Tresp.