The basic requirement for the implementation of AI in the publishing industry is the availability and quality of the data. The difficulty, however, is to bring together the information required to do so from mostly heterogeneous and incompatible system landscapes and data sources. Data in publishing are, for example, KPIs, reviews, subscriptions, terminations, metadata, etc. This process takes a lot of time for relational databases, which is also cost-intensive.
So-called NoSQL databases are meanwhile the alternative, since they offer the possibility to transfer and map the whole data fast and user-friendly into a system.
How can AI be used in publishing? Even lecturers generate - often unconsciously - a kind of "traffic data" by reading manuscripts, evaluating and sorting them for further processing. Since AI can also mimic individual behavior here, it is possible to relieve editors. How? With the help of AI, it is conceivable to sort manuscripts in terms of their compatibility with the respective publishing program.
Sifting the amount of data from the different databases is a huge challenge. An AI approach is immersive data, which means visualizing the data streams using virtual or augmented reality to make them manageable.
Virtual Reality, or VR for short, is a technology that could revolutionize storytelling in the future. It allows immersion into the virtual world and thus combines literature, film and game. This development is still in its beginning, but the publishing industry is already experimenting - with impressive results.
„The Chinese-British publisher Design Media is developing a combination of an analog book and interactive sequences that can be experienced with virtual reality glasses and an app.“
Internet giants such as Amazon make life difficult for stationary retailers. Artificial intelligence can help offset disadvantage and create individual shopping experiences. Recently, the internet giant in the United States tested a stationary supermarket - without cash, but equipped with intelligent sensors and deep learning algorithms. It should be created a stress-free shopping experience without a long queue for the customer. It collects important data about purchasing and purchasing behavior.
Times when utilities were pure power producers are over. The latest technological developments have blurred the boundaries between producer and consumer. Consumers and companies that consume energy also produce energy themselves. They become so-called prosumers. This trend makes it harder for energy suppliers to estimate when prosumers get electricity from the grid and when they feed it - for example, via solar panels or cogeneration units.
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