Lernergebnisse
Recent months have seen an explosive interest in artificial intelligence (AI), especially large language models (LLM) like GPT, Gemini, Llama etc. These powerful models promise to transform the economy but face significant challenges, such as their humungous demand for energy. In contrast, the brain succeeds at surpassing these LLMs in intelligence, while being incredibly energy efficient. Taking inspiration from biology, scientists are developing a potentially breakthrough technology called 'neuromorphic computing' which aims to implement AI by mimicking the way a biological brain works.
Neuromorphic computers are akin to artificial brains in that the circuits of these chips are similar to the neural circuits in the brain. Due to their ability to process large datasets at high speed and using low power, these brain-inspired chips could be highly useful for personalized medicine, wearable health trackers, wearable diagnostic devices, portable brain scanners, wearable brain-computer interfaces etc.
This course will impart to the students an introductory understanding of the cutting-edge field of neuromorphic computing (AI hardware) and its highly promising applications in biomedicine. Students will read and discuss the latest and important research papers in the field of AI hardware and biomedicine. They will gain familiarity with the important problems, recent breakthroughs and future goals of designing hardware for AI that mimics the brain. They will also learn about novel technologies and far-reaching ideas in the field of biomedicine, personalized medicine, neurotechnology, wearable devices and bio-imaging. This knowledge would really help the students prepare for an economy that could be transformed by AI.
In addition to learning about the aforementioned topics, students will also gain general scientific skills. For instance, students will learn how to read scientific papers, how to critically analyse them, how to discuss a paper with colleagues, how to ascertain a paper's positive and negative features. These skills are very important to any scientist or engineer.
