Yes! Act now before it's too late and you're forced to play costly catch-up with AI solutions later. Now is the time for medium-sized companies to explore the possibilities of artificial intelligence in order to secure competitive advantages for the future. We make it much easier for you to access the necessary resources. As a fast follower, you benefit from our experience and generate tangible results in the shortest possible time.
Artificial intelligence refers to machines that mimic human cognitive abilities, such as language and strategic thinking. AI applications thus enable machines to perform tasks that could previously only be carried out by humans. Artificial intelligence is generally divided into strong and weak forms.Weak artificial intelligence refers to systems that focus on solving specific problems. The problem is solved on the basis of mathematical and computer science methods that are developed and optimized for the respective requirements. The resulting system may be able to optimize itself. Weak artificial intelligence is already used in many areas (e.g. image recognition, speech recognition, automated translations, etc.).The goal of strong artificial intelligence, on the other hand, is to achieve the same intellectual skills as a human or to surpass them. It could perform all the tasks that only a human can do today. However, it has not yet been possible to develop a strong artificial intelligence, and it is unclear whether this is possible
An algorithm is basically a set of instructions or rules that define how a computer should solve a particular problem.Algorithms are the fundamental tool of computer science and form the basis for the development of software and applications. They are effective solutions to well-defined problems that require clear instructions. Artificial intelligence (AI), on the other hand, is a much broader concept that refers to the development of systems capable of performing tasks that normally require human intelligence. Unlike traditional algorithms, which are based on clear rules, AI systems are able to learn from experience, recognize patterns and improve themselves.
When using publicly available AI chatbots, be aware and sensitize your employees to the fact that every input made online in a generative AI chatbot is transmitted to the operator of the chatbot and potentially stored. The operator can process this information for future responses and thus indirectly disclose the information to the general public. When using generative AI tools, there is therefore a risk that employees will make internal, sensitive or personal data publicly accessible. When using a generative AI model available online, only publicly accessible information should therefore be shared. Never share internal information - especially personal data of customers and employees.And although the performance of freely accessible generative AI models is constantly increasing, be aware that these models can still provide incorrect or distorted answers in some cases. Therefore, always check the answers provided by the services critically before using them. It is also possible that proprietary information is the basis for training an AI model. This information may appear verbatim or almost verbatim in the model's answers without referencing them or including a reference to the author. You should therefore always check whether the output of a generative AI model available online infringes intellectual property rights, in particular third-party copyright claims. To be on the safe side, do not reproduce answers from generative AI models verbatim in documents that are passed on outside your organization.
Deep learning (multi-layered or deep learning) is a special method of information processing and a sub-area of machine learning.Artificial neural networks are used to learn the relationships in extremely large amounts of data. The learning methods are based on the functioning of the human brain, which basically consists of interconnected neurons. These individual neurons carry out simple, elementary operations. A network of thousands or millions of neurons can map very complex relationships.