Intelligent machines on the rise
Information is key
Coming into contact with new technologies: VR, AR & more
Classification, sentiment analysis and predictive maintenance
Digitalization made easy: The first steps are taken!
Information is the key
Information is the linchpin of artificial intelligence. When we use artificial intelligence, we learn from information and utilize this knowledge to make automated decisions for concrete outcomes. We teach AI systems to analyze data and give them algorithms to solve problems. To make this possible though, we have to prepare a basis of information for AI. Future AI systems will train themselves as well!
In contrast to humans, AI needs large data volumes to learn effectively. Again, different from humans, it can easily handle large data volumes. For example, to recognize an image of a dog, it needs hundreds of thousands to millions of images with and without a dog. A small child can recognize a dog at first glance, though. Algorithms have to analyze large data volumes to be able to solve a given problem. While machines today need mass amounts of data to get results, the good news here is that they are also capable of actually processing such a large amount – in comparison to the first wave of AI in the 1980s. This puts an end to one paradox that there is scarcity in plenty! Right now, too much information slows down decision-making.
Inundated with information? A blessing
Nothing happens without information. A barrage of information may be seen as a curse today, but it can be a help to us in the future. Our cognitive skills are overwhelmed though by the flood of information. We don't even use 80 percent of the information we gather! With every passing day and year, the information multiplies. Industry 4.0, the Internet of Things, etc. are all causing a dramatic increase in data: By 2020, the worldwide volume of data will increase tenfold, going from the current 4.4 zettabytes to 44 zettabytes.
Today's barrage of information is ideal for artificial intelligence applications. Still, ERP software like SAP is not capable of processing the bulk of this information. What's needed is a context-sensitive software that can efficiently manage and store data volumes and, if necessary, scale horizontally. This is and has always been the intrinsic purpose and capability of enterprise content management systems such as Doxis4 from SER. Just look at DHL Express for an example of this: 8.5 billion documents are currently being stored in the Doxis4 information repository. These documents are accessed by one million users per day on average. In peak times, 1,060 accesses per minute are registered.
Already 20 years ago, 80 percent of all information in a business context was unstructured and only 20 percent was structured. This remains the same today. In the information repositories of SER's Doxis4 ECM software, all of this information can be found – including SAP data (both current and archived data), emails, documents, social media content, websites, machine data, images and videos.
Cognitive services are home to AI
In the age of artificial intelligence, information is finally becoming a production factor. Information logistics will become one of the strongest influencing factors of value creation. If you already know the value of your information and store it in an ECM system, then good for you. The information repository, the core of Doxis4 ECM software, functions as a safe for the new currency in business: information. Used as a digital archive, this information repository stores empirical values and has the ability to remember. This omnipresent intelligence gives a new architectural layer to Doxis4 ECM: cognitive services. All AI technologies of deep content analytics (deep CA), ontology, and natural language processing (NLP) are covered in cognitive services and accessible on all ECM applications. Moreover, there is innovative potential in the ability of these services to link, say, statistical and semantic modeling.
Federated content integration service
Information management is technological and complex, which is a challenge for companies today. In addition to SAP, numerous other business applications are being used and their content is stored in separate databases and structures. This is already a source of woe for the productivity of knowledge workers. As long as this situation is not factored into decision-making, it will have negative consequences on the outcomes of AI in the future. AI needs data from various information sources to be able to learn and make forecasts. The integration of information silos spread out across companies is strategically more important than ever for IT teams.
Incorporating these sources of information into various metadata structures will be handled by a federated content integration service in Doxis4. The content of the information silos can be migrated, but it's not a must! Through the federated metadata platform of Doxis4, it is possible to access any databases, file systems, etc. from Doxis4. AI crawlers are used by the platform to track down information from the sources. To avoid an information overload, not all information is permanently archived. Just like the human hippocampus, it is also possible here to transfer the most relevant information from the short-term memory to the long-term memory.