SPOTLIGHT
THE SMART FACTORY – AI IN INDUSTRIAL APPLICATIONS The year is 2010. Barack Obama is president of the United States. Smartphones are conquering the world. The financial crisis seems to be over and there is a spirit of optimism in the global economy. At the same time, something fascinating is happening, unnoticed by the public, in the development departments of innovative IT companies. A decades-old technology is beginning its meteoric rise to become one of the most important topics of our time: artificial intelligence. The concepts on which today’s AI rests can be traced back to the 1950s – and they fascinated researchers even then. However, the idea of the „general problem solver“ based on neural networks which emerged then could not be implemented at that time. This was still the case when the topic was met with renewed hype in the 1990s, when Deep Blue became the first computer to win against the then world chess champion Garry Kasparov. It wasn’t until around 2010 when the first commercial turning points occurred that enabled practical applications of artificial intelligence. Essentially, three things had changed: 1. With Web 2.0 there was a socio-technical transition that led to the increased use of the Internet, as well as active sharing and creation of content by everyone. Only then was a large amount of commercially interesting data available. 2. Advances in algorithms, especially deep learning, have made AI applications more powerful and robust. 3. Multi-core CPU architectures made computing power cheaper. In the subsequent years, AI became the focus of Big Tech. The five largest tech companies – Google, Facebook, Amazon, Apple, and Microsoft – are rapidly adapting the now highly profitable technology and building completely new services and business models on it. Their areas of application range from practical utilities, such as navigation in cars, weather forecasts on smartphones, intelligent assistants at home, to complex algorithms with the purpose of predicting and influencing human behavior. With these services, AI has now reached almost every area of our daily lives without us being consciously aware of it. Today, in 2023, we are recovering from the first big bang created by AI. A few months ago, OpenAI presented its AI ChatGPT platform to the public. The underlying language model GPT-3.5 was trained on vast amounts of text data and not only has an enormous wealth of knowledge, but also real language understanding. Does this mean the original idea of the „gen-
eral problem solver“ from the 1950s is within reach? The performance of these models seems so high that the first prophets are already publishing lists of jobs that will no longer exist in five years. Even if this seems somewhat exaggerated, the economic and social consequences that this new technology will bring are certainly significant. However, they remain difficult to assess today. WHAT ROLE DID AI PLAY IN THE EARLY DAYS OF THE 4TH INDUSTRIAL REVOLUTION? “Industry 4.0” gained traction around the same time as the commercial awakening of AI. The term was created in 2011 as part of the high-tech strategy of the German federal government. It is now used as a synonym for „digitalization“ across Europe. In addition to the relevant design principles (networking, information transparency, technical assistance, and decentralization), the original guide also contains references to the use of AI. I am able to report first-hand how industrial companies have dealt with AI in the process of digitalization, because I have been at the forefront. I started my first job as a young engineer at COPA-DATA in 2010. Coming fresh and inspired from a challenging academic program, I was equipped with unassailable self-confidence and the will to single-handedly improve the world. At COPA-DATA, I quickly became known as „the innovative one“ and, in addition to other topics, starting around 2013 I was mainly responsible for the area of AI. With a dedicated team of sales specialists and data scientists, I visited interested companies in the areas of both mechanical engineering and production to talk about AI projects. Particularly in the first few years, these conversations were very similar. They challenged me as a mediator and interpreter between the following three parties: 1. The highly motivated department head/CEO who had read in their favorite business magazine that AI was the next big thing and could solve virtually all problems overnight.
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