A new forum called Real World AI has been established at the Diplomatic Coouncil. It focuses on the use of artificial intelligence in physical systems and environments such as robots, autonomous vehicles, drones, manufacturing plants, buildings or entire cities (smart city). Occasionally, the term ‘physical AI’ is also used, for example by Jensen Huang, CEO of Nvidia.
The two entrepreneurs Dr Daniel Trauth from the real-world AI pioneer dataMatters and Harald Müller from the Bonner Wirtschafts-Akademie (BWA) will share the leadership of the new forum as co-chairs. The focus is explicitly not on AI research, but on the application of AI outside of computer environments and on the effects on the economy, society and politics.
‘We are taking AI out of computers,’ says Dr Daniel Trauth, summing up the focus of the new forum. He cites smart factories, smart buildings and smart cities as examples of the widespread use of AI in the real world. Sensor technology is one of the keys to the “smartification of the world”: ’In the future, we will have sensors all around us that collect data and send it to AI centres for evaluation. Sensors are the link between the environment and AI.’ In addition to data collection and evaluation, the new forum will also focus on the application of AI in the real world, for example in the form of self-driving cars, autonomous drones or AI robots.
Harald Müller emphasises the consequences of these developments: ‘If artificial intelligence in the form of humanoid AI robots takes over human activities in more and more areas, this will not be without serious consequences for our society.’ He explains: ‘On the one hand, robots that can think and also tackle things are urgently needed to counter the shortage of skilled workers. On the other hand, these humanoids may find their way into our daily work routine faster than the demographic factor sends the baby boomer generation into retirement. Among other things, this raises the question of how to finance our social systems, which have so far been supported by the value added by human labour. In addition, there are a number of ethical issues to which our society and thus politics must find answers.’
AI cycle: sensors, AI, robots
Dr Daniel Trauth and Harald Müller outline the use of artificial intelligence in the real world as an AI cycle. Cameras and other sensors (measuring systems for temperature, humidity, CO2 levels, fine dust, noise, etc.) capture the situation as comprehensively as possible in a production hall, an office building or on the streets of a municipality, for example, and transmit it by radio to data centres where it is evaluated using AI systems. On the basis of the insights gained in this way, people make informed decisions and, where appropriate, robots take action in the real world to solve problems that arise.
‘Heat hotspots in a community detected by permanent temperature monitoring can be mitigated by appropriate shading measures,’ says Dr Daniel Trauth, citing an example of a specific project in which he is involved in a city in Germany. ‘At identified crime hotspots, surveillance drones and police robots can provide more security,’ says Harald Müller, pointing to a field of application that is already a reality in Asia.
Dr Daniel Trauth gives an example from the production sector: he is involved in a project with the Fraunhofer-Gesellschaft on AI quality control in machining. Machining, in which material is turned, drilled, milled or ground into the desired shape and size, is an essential part of manufacturing technology in many industries, from automotive production to the manufacture of medical instruments. Errors in the machining process can have serious consequences, ranging from product failures to safety issues. ‘AI camera control can significantly reduce inspection times and the costs of quality assurance, while significantly improving the accuracy of quality assessment,’ says Dr Daniel Trauth, explaining the benefits of ‘Real World AI’ using this example.
Harald Müller expects to see a sharp increase in the use of AI robots in manufacturing over the next few years. According to studies, humanoid robots could take over more than 50 per cent of manual tasks in manufacturing by 2030. They are particularly suitable for rapid deployment in areas such as logistics, assembly and material handling. According to the BWA boss, there will be more and more production areas in the future to which humans will no longer be granted access at all during operation. The reason: if only robots are at work in a production hall, they can work two to five times faster than is necessary and permitted for safety reasons when humans are in the room. Harald Müller predicts that the proportion of ‘human-free zones’ could increase to up to 50 per cent of the production area over the next five years. He points out: ‘If half of the production runs at double or even quadruple speed, we will find ourselves in a completely different industrial working environment.’
AIoT: AI and the Internet of Things come together
As an alternative to the term ‘real-world AI’, the term ‘AIoT’ is also used as a play on words from ‘AI’ and ‘IoT’ (Internet of Things). The so-called ‘Internet of Things’ means that more and more objects in the real world are being made ‘smart’, i.e. they can connect to the Internet via a radio connection. Apple's ‘thing finders’ called AirTag are an example of this. When attached to an object, they are constantly searching for a Bluetooth connection with an iPhone in order to transmit their location or the location of the respective object (briefcase, handbag, backpack, bicycle, etc.) via Apple's worldwide network, making it easy to find the object. It is estimated that there are around 40 billion networked IoT devices worldwide.
For use in smart cities, the LoRaWAN (Long Range Wide Area Networks) radio standard is a better alternative to Bluetooth for transmitting data from sensors to a municipal data room for evaluation. Data transmission via LoRaWAN requires so little energy that the sensors can function for many years without intervention before they need to be replaced. Dr Daniel Trauth: ‘LoRaWAN networks provide a secure and cost-effective backbone for smart cities.’
Co-Chairs Dr Daniel Trauth and Harald Müller
Dr.-Ing. Dipl.-Wirt. Ing. Daniel Trauth founded dataMatters as a spin-off of RWTH Aachen University and led it to become an international player at the interface between the real economy and AI. He has been honoured for this with over 20 awards (RWTH Spin-off Award 2019, digitalPioneer 2020, and many more) and was accepted as Executive Chair into the Diplomatic Council.
Harald Müller founded BWA over 25 years ago as a specialist in personnel development, outplacement, personnel consulting and training, as well as in labour market programmes such as employee transfer. In dealing with the consequences of structural changes, BWA acts as a neutral mediator between employers and trade unions for the benefit of employees. With the help of BWA, more than ten thousand employees have found a new professional future. Harald Müller is not only active as Executive Chair of the Diplomatic Council, but is also a member of the advisory board of the ‘Education and Employment’ foundation, which is committed to the socially acceptable management of economic structural change.
Picture (from left to right): Andreas Dripke, Executive Chairman Diplomatic Council, Dr. Daniel Trauth, Co-Chair Real World AI Forum, Harald Müller, Co-Chair Real World AI Forum, Hang Nguyen, Secretary General.