Munich Innovation Hub for Applied AI

Overview

The Munich Innovation HUB for applied AI integrates the applied AI activities of the Munich Metropolitan Region and in particular of the institutions fortiss, the appliedAI initiative of UnternehmerTUM  and of the Munich School of Robotics and Machine Intelligence  (MSRM) in one place. The target is to support established companies and especially SMEs on their AI journey to transform their business. Following a comprehensive maturity logic, interested companies are supported from starting with AI and digital activities until becoming professional in using AI technologies. This typically happens in the form of initial workshops, the assessment of their AI maturity followed by expert sessions and provision of supporting documents. A broad set of individual offerings as well as a large network of over 500 startups complements the support. 

appliedAI is part of the UnternehmerTUM, a large non-for-profit institution with the goal to "support innovation and entrepreneurship in Germany". appliedAI's goal as a department of UnternehmerTUM is to "lift Germany to the AI age by accelerating the adoption of AI technology". fortiss is a state-funded research institution with a focus to support the transformation of SMEs. Therefore, both institutions in the DIH follow the non-for-profit approach as an ecosystem for innovation. 

The support is based on a maturity assessment tool and selected measures consisting of engineering support, education and upskilling opportunities as well as strategic and operational support. The Munich Innovation HUB for applied AI serves as a central hub to connect our partners with startups and other partners to become part of an ecosystem for applying AI. This is supported by a diverse range of activities like conferences, meetups, workshops, best practice sharing. 

The coordination within the appliedAI Initiative of UnternehmerTUM provides a central contact point for the following activities of the involved cooperation partners:

Innovation Lab for AI: Bringing together companies, researchers and students in order to work at innovative AI based solutions and (software) prototypes
Qualification for AI: Training and qualification actions for AI technologies and methods adapted to the needs of industry professionals
Research on AI: Application-oriented research, together with partners from practice and based on practice-relevant and future-oriented questions.
Entrepreneurship: Supportive activities for establishing professional and entrepreneurial knowledge and the creation of start-ups, including access to finance.
Network of Partners in AI: Bringing together research, established companies and startups to work together and solve current challenges in an industrial context as well as to solve practical questions in the application of AI in the industry.
Access to infrastructure for AI: Tech partners support our ecosystem with latest technologies and expertise.

As part of the CPSE Labs initiative, the HUB also supports businesses by funding experiments. At present the Lab funded a number of research experiments designed by businesses (and other organisations) working in a variety of technology and engineering domains. The funding of experiments are focused and fast-track. They have explicit objectives to clearly improve the business's ability to innovate, with specific criteria in terms of technology use and overall objective.

The HUB has experience of a variety of projects. Read some short case studies and funded experiments of previous work below: 

The AIT (Austrian Institute of Technology) case study examined the use of the 4DIAC platform in a smart grid laboratory  (see http://www.cpse-labs.eu/gs_smartgridcasestudy.php).
The ACIN case study allowed the Vienna Institute of Technology's Automation and Control Institute to demonstrate the real time capability of the 4DIAC platform (see http://www.cpse-labs.eu/gs_invertedpendulumcasestudy.php)
Festo case study. In this case study the world's leading supplier of pneumatic and electrical automation technology worked with fortiss to develop a prototype adaptable factory (see https://www.fortiss.org/en/research/projects/fortiss_future_factory_f/)
Integration of Co-Simulation Methods into a real-time Platform for CPS (see http://www.cpse-labs.eu/experiment.php?id=c1_gs_cosim)
AI Use Case Families 1.0 (see https://appliedai.de/use-case-library-v1/)
Digital technologies.