Switzerland is conducting advanced research not only in data science, but also modern hardware like sensors, small microprocessors and smart production. Switzerland isn’t the only country doing this, but it’s a good example of how data science and AI are linked to physical products and production. It’s also a practical illustration of how AI-powered products can ( and should) be designed to help and collaborate with humans, not replace them.
It is said all the time that software changes the world. This is true, but at the same time, physical products are crucial, and of course physical life is mandatory for human beings. So software and virtual realities are not enough – many actions and products have a physical element that must be linked to data, software and algorithms.
Recently I visited an innovation and future vision conference in Switzerland. While I was there, I also visited Switzerland Innovation Park and Swiss Smart Factory. The conference in Bern provided a platform for companies and thought leaders to showcase their latest innovations, products and future visions. This event brought together visionaries, industry leaders, and venture capital firms, highlighting the transformative potential in the areas of sensors, personal data and AI.
Throughout the event, there were compelling discussions on the role of innovation in improving the lives of people. It was acknowledged that while technological advancements have the potential to revolutionize various aspects of our lives, there are also concerns about how companies and governments may misuse personal data that they control. In this context, the consensus was that giving individuals better control over their personal data can empower them to lead better, healthier lives.
AI-based ski instructors
So, how can personal data and AI be combined to make better physical products? One example is AI-based ski instructors.
Prifina, Heierling and Codefabrik are developing skis and helmets that have sensors from Movesense connected to the individual’s own data cloud through Prifina’s user-held data platform, where it can be combined with the user’s other data from wearables. Codefabrik develops applications based on the data.
This illustrates a model where sensors are installed in physical products, data is collected and combined with other data, and AI applications then offer concrete help to users – in this case to help a skier with their performance and training.
Smart production becomes reality
Industry 4.0 has been a popular term for some time, but it hasn’t yet reached its full potential. We visited a demo factory that makes drones, but is also a fully realized smart factory. A customer can tailor a product, order it, and then it automatically goes through a production process that includes 3D printing, robots to assemble parts and also stations of people doing manual assembly work, with the machines giving them very concrete instructions. Also, the delivery and component supply chain is integrated into the same smart process.
This is not a new idea, but it demonstrates that a factory can already work like that. It is like many things with IoT, Industry 4.0, sensorization and AI – they have been talked about for years, but progress has been slow and some people have become skeptical about its potential. But now we’re starting to see many practical applications, services and productions that really get these ideas and concepts to work.
One key lesson from examples like this is that Industry 4.0 involves cooperation between machines and human beings. If the factory concepts are too sci-fi, with robots doing everything, it can kill the implementation of the project. Collaborative robots are able to work with people and not pose a safety risk, compared to traditional industry robots that typically need their own isolated areas.
Collaboration between people, machines and AI
Similarly, AI – whether it’s a factory production floor, ChatGPT or an AI skiing teacher – works best when it supports people. This is something that is often forgotten or ignored when we think about the use and development of AI. Machines and humans each have their strengths, and the best results are achieved when they collaborate. Machines can process a lot of data continuously, execute tasks tirelessly, and consider things based on data.
At the same time, humans are better able to do many tasks – sometimes faster, and usually when it comes to handling unexpected situations. Machines are developing all the time (and hopefully humans are too), but for a very long time now, the most realistic models are the ones based on cooperation between people and machines. And in many cases, this also means physical products and machines.
These kinds of examples also illustrate how AI and smart products can really help people and make their life healthier and work better. One important theme in the discussions in Switzerland was to have solutions that not only make quick money, but can really offer better, more sustainable and ethical solutions for us. This means that companies, and also investors, need to take these aspects seriously.
How shall we build our AI future?
When we talk about whether AI development is good and bad, it is important to remember that it all depends on how we want to build and use new AI tools.
As one speaker commented, a hammer is a very useful and important tool. It would be hard to build anything without a hammer. At the same time, you can destroy many things with a hammer, and also kill someone. It is the same with AI and smart machines.
We are now at a point where many concepts we have talked about for years are starting to become reality. We must really think about how to use them. And by that I mean it’s not just about how a certain technology can be used – it is very much about the values and operations of companies and investors.
For better or worse, they are the ones building the future – they should think carefully about what they really want to do and what kind of future they want to develop.