How can artificial intelligence (AI) draw on the principles of nature to solve complex problems? When it comes to recognizing patterns in large amounts of data, AI is faster and more capable than humans. However, he has difficulties when it comes to making connections or dealing with uncertainties and vagueness. Through evolution, development, and learning, nature has developed much more practical problem-solving solutions. Professor Dr.-Ing. Yaochu Jin, Alexander von Humboldt professor of artificial intelligence at Bielefeld University since the fall, is studying how such principles can be transferred to AI.
Professor Humboldt will continue his previous research on nature-inspired artificial intelligence at the University of Bielefeld and research applications of nature-inspired and self-organized AI. âMy goal is to understand and borrow effective mechanisms from nature and transfer them into artificial intelligence for problem solving,â says Jin. The Alexander von Humboldt Foundation is supporting Yaochu Jin’s research with prizes amounting to 3.5 million euros over a period of five years.
The scientist, originally from China, is currently setting up his research laboratory at the Faculty of Technology and forming his research team. Having a team with an interdisciplinary orientation is particularly important for him, as it allows him to bring together approaches from different disciplines such as computer science, biology and medicine. He also stresses the need for international cooperation in his research. For example, he looks forward to research visits from international scientists such as former Chinese students and researchers from the University of Surrey, UK, where he worked before moving to Bielefeld. He is driven by his thirst for knowledge and his curiosity: âI want to do something that is not currently the main approach of AI,â he says. “And I want to know more about possible applications that haven’t been sufficiently explored yet.”
Allow technical systems to organize
There are quite a few areas where AI is reaching its limits. âThe AI ââis designed to work very precisely,â says Jin. “But when the uncertainty kicks in or things aren’t entirely clear, it becomes difficult.” Additionally, AI typically focuses concretely on a specific question or task. Using it becomes a challenge when he has to organize himself to, for example, establish links or find a solution to a task that is not well defined.
Nature, on the other hand, is perfectly capable of dealing with varying degrees of uncertainty. âWhen we are born, our basic equipment can be built on millions of years of evolution,â says Jin. For example, the structure of the brain has long been proven in nature. âBut at the same time, we are changing and adapting to the demands of our environment,â explains the professor. Our brains are neuroplastic and able to constantly rewire themselves to adapt. When you learn a foreign language or play a new sport, for example, your brain changes accordingly. âYou can also see it if you let twin cats grow up in different environments. You will find differences in their neural systems, even though their genetic makeup is virtually identical.
An artificial intelligence that works according to the principles of nature
Therefore, nature is able to respond and adapt flexibly to the widest variety of problems and requirements, while AI is generally rigidly oriented towards concrete problems. Jin, who was previously involved in a research collaboration at the University of Bielefeld’s CoR-Lab when he was at the Honda Research Institute Europe, and recently worked as a Distinguished Professor at the University of Surrey, in UK and as a distinguished Finnish professor at the University of JyvÃ¤skylÃ¤, Finland, therefore seeks to orient AI in a way that mimics these basic principles of nature, thereby making it considerably more flexible. He has done pioneering work in the field of nature-inspired optimization and self-organization and will continue to work on scalable and developmental systems at Bielefeld.
At Bielefeld University, Jin will focus on understanding and simulating intelligence in nature, in particular the co-evolution and development of neural systems and body planes.
Use secure and privacy-aware scalable learning for healthcare
Jin’s future research will also focus in particular on the application of privacy-preserving AI to healthcare. âMy main concern right now is how to use the data while effectively protecting its privacy and security,â he says. âEspecially in healthcare, data is very sensitive and should be as secure as possible. This is why this requires not only adaptive systems but also particularly robust systems that can withstand attacks from the outside.
Jin also has a big dream for his research: he would like to use AI to conduct research on understanding the genetic mechanisms underlying heart failure. âI would like to be able to determine which genes are involved and which interactions between genes increase the risk of heart problems,â he says. “It’s a very complex subject, of course, but I would like to know more about it.”
Professor Humboldt is expected to give his inaugural lecture in March 2022. The event will be organized by the Faculty of Technology at the University of Bielefeld and the Joint Artificial Intelligence Institute which belongs to the universities of Bielefeld and Paderborn. The conference will take place in a hybrid format. When that happens depends on how the coronavirus pandemic continues to develop.
Research Prize helps attract top international researchers
The Alexander von Humboldt Chair has been offered since 2008. It is the most endowed research grant in Germany: it grants 5 million euros to academics who carry out experiments and 3.5 million euros to those who do theoretical research. The prize is awarded by the Alexander von Humboldt Foundation and funded by the Federal Ministry of Education and Research. With the Humboldt Professorship chair, the Foundation wishes to enable German universities to make themselves known in the global competition. It gives universities the opportunity to offer the best researchers internationally competitive conditions. At the same time, the award includes the obligation to offer new Humboldt professors a long-term perspective for their research in Germany.
The first Humboldt Chair at Bielefeld University was awarded to mathematician professor Dr William Crawley-Boevey in 2016. He is considered a leading authority in his field, representation theory of algebras. He moved to Bielefeld from the University of Leeds (UK).
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