At the beginning there's always a large data set

Every AI project starts with a sound analysis and preparation of existing data and questions. The driving question is always: "How can we make use of our collected data?" Each problem to be solved is individual and requires a lot of experience in data and business engineering. Once the existing starting position is clear, a model is built, trained and improved with the help of a suitable algorithm until a satisfactory solution can be found.

Relevant References
Clients (excerpt)
WIRZ Communications
Graubünden Ferien
Tamedia AG

«In einer Welt, die von irrelevanten Informationen überschwemmt wird, ist Klarheit Macht.»

Der Historiker Yuval Noah Harari

Who benefits from artificial intelligence?

The potential of artificial intelligence can be used in any industry. For example, speech recognition can help to process customer enquiries 24/7 and to understand, summarise or (well!) translate texts. Image recognition e.g. helps in building databases, product tagging or diagnosing diseases. In general, any relevant decision or interaction can be improved with large amounts of data. This allows to react quickly to changes and to gain economic advantage. In many cases, the targeted use of data even opens up new business areas. Artificial intelligence does not claim to replace human interaction. Rather, it can be used for its improvement and enrichment. In fact, our belief is: man and machine get really strong when being joint!

A wonderful example of this is the AI «KenSpace», which produces amazing results using processed data from Schuler Auctions.

Data are the new oil

In order to be able to use artificial intelligence successfully, vast amounts of data are required. The quality and completeness of the data is central to the results. In addition to good data, enormous storage capacities and computing power are further prerequisites for success. However, these can be well covered with standardized solutions from the cloud.

Traditional programming vs. machine learning

In the traditional software development one finds the answers with the help of rules and data. In the field of artificial intelligence, rules and answers are interchanged: rule models are derived with the help of (very many) answers and data. These in turn can be used for prognoses.

Interesting blog posts about Artificial Intelligence: