Steinbeis Consulting Center AI (STAI) has become an official member of EXCELLERAT’s interest groups, a project funded by the European Union's Horizon 2020 research and innovation program
The focus between the two companies will be on high-performance cloud computing, research & development, and integration of state-of-the-art artificial intelligence models for practical purposes.
Steinbeis Consulting Center AI (STAI) is a Stuttgart-based AI consulting firm. It focuses on software development solutions to give industry companies a competitive edge. Under the strong arm of Steinbeis, an international knowledge and technology transfer group of over 1100 companies, STAI creates smart tools to assist manufacturing, banking, retail, e-commerce industries.
EXCELLERAT, the European Centre of Excellence for Engineering Applications, is a single point of access for expertise on how data management, data analytics, visualisation, simulation-driven design and Co-design with high-performance computing (HPC) can benefit engineering, especially in the aeronautics, automotive, energy and manufacturing sectors.
EXCELLERAT aims to tackle the ever-rising complexity of scientific and development endeavours. Thus, Exascale computing is the focus, which will solve highly complex and costly engineering problems, and create enhanced technological solutions even at the development stage.
"The collaboration is an important strategic step for the development of applied artificial intelligence technologies in Germany. STAI is confident that such a collaboration will help to multiply the practical applications of supercomputers. Modern industry challenges require advanced approaches, and our partnership will allow us to create more innovative cases."
Aleksandr Malyshev, Executive Officer at Steinbeis Consulting Center AI
Such a partnership should positively affect the digital twins' industry, computer vision, and the applied machine learning market. Speed is a massive player in contributing to the deep learning and AI efforts in an organization. Machine learning models are allowed to train for 25-30 days. With the existing non distributed approach, companies can't even improve the model until the next 30 days. The current tests show that High-Performance Computing (HPC) workloads give up to a 120x reduction in time to solution. It could go from 30 days to 6 hours to fully train. The given performance has a significant effect on AI applications in manufacturing, health, retail, and banking.