Intelligent software and advanced algorithms enable us to hand over tasks to machines that until recently could only be done by humans.
Powerful neural networks, so-called deep-learning systems, are capable of replicating the functioning of networked neurons in the human brain. Deep-learning systems are particularly capable of extraordinary performance in object recognition and natural language processing. Images are recognized correctly even if the objects depicted on them are twisted, partially obscured, or taken in unfavorable lighting conditions. Computers achieve error rates that are only half those of humans.
Neural networks are superior to humans wherever patterns need to be identified in text, video, image or audio files. However, humans are still needed as an instance that tells the neural network what the recognized objects are about, i.e. that makes the assignment. There are areas of application for neural networks in every company, with the entire warehouse and logistics sector benefiting particularly strongly from the increase in productivity.
Pattern identification is an important application area for AI technologies, because in these areas machines can already work more error-free and faster than humans thanks to high computer performance. What is particularly exciting is that neural networks are even capable of discovering patterns that were previously unknown. Artificial intelligence (AI) is particularly suited to taking on repetitive tasks and is therefore able to make processes more efficient and significantly increase productivity in the area of warehousing and incoming returns. Employees, on the other hand, are freed from monotonous tasks and can devote themselves to planning or creative activities.