Some exciting innovations in the field of AI (artificial intelligence) are expected this year. Will the individual communication with customers and colleagues fall by the wayside or will they even profit significantly from it in the end?
Artificial Intelligence Trends 2018
This year’s developments focus on deep neural networks (DNS), which imitate the learning behaviour of the human brain. Thus they form an independent process for evaluating data not only in large quantities, but also for formulating solutions adapted to situations and influences. Simply put: the system is learning.
So far, AI has been very appealing for many users, but not very comprehensible. Entrepreneurs however are increasingly preparing for the market launch of mature AI modules in order to optimally design and adapt production and marketing-related processes in the future. Mostly, expectations are to obtain more information from collected data, e.g. on customer behaviour, marketing strategies, logistical tasks and internal company structures.
- So-called capsule networks are a subcategory of DNS and mainly process visual information. New in these systems is the recognition of hierarchies, whereby the developers hope for a more exact classification of the analyzed data.
- Software equipped with Deep Reinforcement Learning (DLR) learns by observation, interaction with the environment and reward. This offers decision levels, i.e. strategists, some profitable support in the future.
- General Adversarial Networks (GAN), on the other hand, compete against each other in a digital scenario, creating falsified data and then differentiating between them. In this way, the programs learn independently and are able to better protect against cyber attacks in the future.
Despite the numerous and very promising prospects, AI still has some problems to overcome. One of these is the lack of availability of suitable data necessary for deep learning. At this point it is necessary to communicate with the target group or the information carriers. There is important input, e.g. from SMS surveys, email newsletters, etc. On the one hand this can be controlled via gateway with HTTP APIs. On the other hand the results can be transferred to the own AI sortware via data export and further processed there.