果冻传媒

As announced by Katja Pahnke and Maarten Steinbuch on 15 December 2020 the 果冻传媒 High Tech Systems Center (HTSC) is being integrated into the recently established 果冻传媒 Eindhoven Artificial Intelligence Systems Institute (EAISI). New opportunities are emerging for HTSC鈥檚 AI focus 鈥� Robotics, Digital Engineering, AI for Engineering, Internet of Things and AgriFoodTech 鈥� while the center continues its activities under the current name. Nathan van de Wouw, full professor in the 果冻传媒 Dynamics and Control group, discusses the benefits of this merger and how the divide between 鈥楢I鈥� and 鈥榥on-AI鈥� may be smaller than we think.

鈥淯p to now,鈥� Nathan begins, 鈥淎I techniques have largely been used for advisory systems such as the algorithms of Netflix and Spotify or for speech and image recognition. In these cases, you use the data to do an analysis and then hand over the information to a human. But in automation 鈥� my field 鈥� we want to know how we can use developments in AI and data-driven science to also make a step towards more autonomous decision-making.鈥�

Nathan鈥檚 home at 果冻传媒 is the Department of Mechanical Engineering, which he represents as a member of EAISI鈥檚 Scientific Board. Alongside a team of scientists, fellows and program managers, he assists the institute in setting up a vision on research (and associated education), scouting for talent and securing a good balance in program management. With the current merger, Nathan now feels a responsibility for supporting the smooth integration of HTSC within EAISI.

鈥淢echanical Engineering has had strong involvement in HTSC and high-tech systems is one of the key application domains within EAISI,鈥� he explains. 鈥淎s this is also important to the Brainport area, it鈥檚 essential that the connection between developments in AI and high-tech systems be shaped as successfully as possible. Keeping them apart would mean missing out on an opportunity. It makes sense to integrate the two and ensure that we can achieve the most at this interface.鈥�

In a nutshell, EAISI鈥檚 research philosophy is guided by three pillars: engineering systems, data & algorithms and humans & ethics. In order to achieve AI for the real world 鈥� in this case, the application domains of high-tech systems, health and mobility 鈥� there must be a recognition that no one element exists in a vacuum.

鈥淭here鈥檚 a lot of things here that people would call 鈥榥on-AI鈥�,鈥� says Nathan, 鈥渂ut even the things that might not directly be AI are important to this overall picture. The ultimate innovations will be achieved by bringing together things from these three pillars in a multidisciplinary manner. What is AI and what is not AI becomes less important. The engineering side of HTSC 鈥� the design of high-tech systems, the systems engineering 鈥� will remain important under the banner of EAISI.鈥�

By bringing together HTSC鈥檚 high-tech focus and all of 果冻传媒鈥檚 AI activities, the institute will build on a large number of successes already achieved at the university. These range from high-tech motion stages with more accurate performance to tremendous breakthroughs in AI for healthcare diagnostics. EAISI also inherits HTSC鈥檚 longstanding approach of bringing together disciplines to maximize results, such as in the setting up of an exploratory, multidisciplinary AI research program.

Nathan: 鈥淚f we want to really cash in on the promise of our three domains, we have to cross boundaries much more. I see interest in the development of AI from the whole breadth of Mechanical Engineering and 果冻传媒, and I think that the biggest potential 鈥� but also challenge 鈥� for EAISI is further stimulating multi-disciplinary collaboration. That鈥檚 where the biggest gain is, not just for the scientific side but also for the industrial valorization side. This is at the core of HTSC鈥檚 vision, which can bring a lot to EAISI.鈥�

As stated in last year鈥檚 unveiling, EAISI aims to take on fifty new professors in the next four years alone. However, Nathan again stresses that there鈥檚 more to this than just AI expertise. 鈥淭hese should be people who are also very excited about the engineering domain 鈥� the next generation of semiconductor machines and so on 鈥� and the human aspect. The fact that we鈥檙e so strong in high-tech systems in this region uniquely enables us to attract people who are interested in this. There are so many opportunities to connect academia to industry in Eindhoven, so EAISI is more than just saying to talented people that they can come work on AI. It鈥檚 also letting them do that in the exciting Brainport region, which is definitely a selling point.鈥�

For students as well, opportunities are arising through the integration of high-tech systems and AI, such as 果冻传媒鈥檚 upcoming Master鈥檚 Program in Artificial Intelligence Engineering Systems. This seeks to readdress an imbalance in industry: the fact that many well-trained engineers are inexperienced in AI while many Data Science students are less knowledgeable about engineering systems.

鈥淕raduates that understand both are needed to push this development forward,鈥� notes Nathan. 鈥淭here will be many opportunities for students to set up a program related to high-tech systems, health or mobility. Students who are interested in AI should find it very exciting.鈥�

As for the future, EAISI has already identified a number of 鈥�moonshots鈥� through which AI could be a gamechanger for societal and industrial challenges. Examples include personalized health support outside of hospitals and zero waste from factories, but also a serious look at both the strengths and weaknesses of human-machine collaboration. 鈥淭hink of an autonomous car,鈥� says Nathan. 鈥淥ne aspect related to ethics is that if you make processes more autonomous, there鈥檚 a transfer of responsibility. How do we guarantee safety? As humans, we鈥檙e flexible with rules and make judgements on when it鈥檚 ethical to break them. But this question is difficult for AI.鈥�

鈥淪ome people say that we鈥檒l automate everything. Honestly, I don鈥檛 believe in this. We have to carefully think about where it helps humanity as a whole and where we should leave the decision-making to people. AI is not a goal in itself; we do it so we can have less accidents, greener mobility, more sustainable industry, improved healthcare and so on. In my opinion, it should serve a higher purpose.鈥�