Together with its partners, the company builder Körber Digital develops user-oriented software-as-a-service products that increase manufacturing efficiency worldwide. Always there as support: artificial intelligence. We spoke to Managing Director Daniel Szabo about the integration of AI in the mechanical engineering industry, the relevance of ecosystems and Berlin as the ideal place for AI development.
Hello Mr Szabo, thank you very much for taking the time for this interview! What is your favourite new development in the field of artificial intelligence?
It is fascinating overall to see the speed at which the digital possibilities of Artificial Intelligence are developing. This concerns so many different areas of application that it is virtually impossible to name just one... At the moment, I find DALL-E 2 one of the most fascinating AI developments (https://openai.com/dall-e-2/). It is an AI system that has learned the relationship between images and the descriptive text. For example, it is possible to create realistic images and graphics from a text description. This AI system is an excellent example of the boundless creativity and variety of applications of artificial intelligence - and above all of the fact that it is fun to deal with AI and experiment around with what is possible. However, the project also shows the importance of a responsible approach to AI. In the case of DALL-E 2, this means, among other things, limiting the generation of violent or hateful images as well as sexual content.
Your company Körber Digital is involved in the integration of AI in the mechanical engineering industry. What solutions and products in particular do you offer?
For our mission "AI-powered manufacturing efficiency", we develop manufacturer and industry-independent SaaS solutions based on three main pillars: Data access and analytics, connectivity and innovative technology. Currently, our portfolio consists of three, soon to be four, ventures.
In 2020, we launched our first venture, FactoryPal, which uses a sophisticated machine learning algorithm to continuously optimise Overall Equipment Effectiveness (OEE) by up to 30 per cent.
Our second venture, InspectifAI, focuses on the development and implementation of AI-supported methods in the optical inspection of pharmaceutical products, which increase the detection rate of the inspection machine by up to 100 per cent - with a simultaneous reduction in the ejection rate of good products.
With our third venture, DAIN Studios, we aim to expand our ability to harness the power of AI to create visible business value on our customers' side. DAIN Studios helps companies define a clear vision, strategic goals and actionable implementation plan for data and AI, and identify new data-driven opportunities. Our latest project, VAIBE, to be spun out later this year, focuses on blue collar employee engagement and motivation, using game mechanics and strategies and the psychology of success, rather than pure rewards.
Why should the use of AI become the goal of all engineering companies? How can they benefit from it?
Smartly combined data and their analysis make processes faster and more profitable: Big Data thus becomes Smart Data. The economic potential of Data Science with a focus on Machine Learning is extremely large, which is why we are making it a fundamental part of mechanical engineering - and other mechanical engineering companies should do the same.
By developing data analysis models based on mechanical engineering know-how, digital software solutions can improve plant availability and lead to reduced downtime, increased energy efficiency, longer service life as well as an optimised production result. Our digital offering can thus make plants many times more efficient and effective and thus generate greater added value for customers than would be possible through hardware engineering, for example with regard to the sustainability aspect.
Why is co-creation and a functioning ecosystem so important, especially in the field of AI?
Körber's motto is "stronger together" - its truthfulness is particularly evident in the field of AI. Because together, we usually find the most innovative solutions to far-reaching challenges, in our case in industry.
More concretely: To create added value for customers using AI, you need a relevant problem, access to real data, software know-how and deep, relevant process knowledge. Without access to data, it is impossible to iteratively develop solutions, let alone create customer value. Therefore, it is a prerequisite to develop the solution together with the problem owner and data owner. However, since there are only a few organisations that have all the necessary skills to develop an AI solution in-house, it is elementary to be well integrated into an ecosystem of experts. This is because in the ecosystem you can achieve positive network effects in which everyone emerges as a winner. By creating a system where knowledge sharing is prioritised, all actors can benefit from jointly achieved progress.
There is an increasing emphasis on reducing corporate CO2 emissions and on corporate social responsibility. What kind of sustainable solution in production processes using AI does your product offer?
Our digital solutions increase the efficiency of existing machinery, eliminating the need to purchase resource-intensive new machinery and also reducing the use of resources per unit of product produced. It also significantly reduces raw material and end product waste.
As a company builder, you work with many companies and start-ups. What advice would you give to young founders who want to start up in the field of AI?
Founders should not focus on technology, but on value generation. Technology is only a means to an end to create value for customers. In addition, in the AI field it is important to find partners early on in order to build a product through access to their data. However, the focus of the co-development partner should not be directly on the maximum value-skimming, rapid commercialisation of the solution. Instead, you have to create a win-win.
What are your company's goals for the future?
There is currently a strong trend in the manufacturing industry from "hardware first, software as add-on" to "software first, AI as add-on". And according to forecasts, production and supply chains will be fully networked and self-optimising as early as 2025. Therefore, our focus is already on using data, cloud and AI to develop data-centric products and services that have a significant impact on our customers.
In doing so, we pursue a clear vision: we want to become the number 1 in the market - for AI in manufacturing and supply chain. In addition, we supported the international technology group Körber AG in its digital transformation with the goal of generating one third of sales via digital solutions at group level as early as 2024.
Why is Berlin the ideal place for AI developments? How do you think the scene will develop over the next few years?
Germany is generally very well positioned in the field of AI and has the ideal starting conditions with its hidden champions. Berlin in particular has long been considered a startup hotspot and has Europe's largest digital ecosystem with a large talent pool - this is especially true for the technology industry. The metropolis attracts young, highly qualified people from all over the world. Thus, it is the ideal environment to start and scale businesses and drive innovation.