We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
INTEGRATING AI HARDWARE IN ACADEMIC TEACHING: EXPERIENCES AND SCOPE FROM BRANDENBURG AND BAVARIA.
- Authors
Xiong, Z.; Stober, D.; Krstić, M.; Korup, O.; Arango, M. I.; Li, H.; Werner, M.
- Abstract
The field of artificial intelligence (AI) has gained increasing importance in recent years due to its potential to sustain growth and prosperity in a disruptive way. However, the role of special hardware for AI is still underdeveloped, and dedicated AI-capable hardware is crucial for effective and efficient processing. Moreover, hardware aspects are often neglected in university teaching, which emphasizes theoretical foundations and algorithmic implementations. As a result, there is a need for courses that focus on AI hardware development and its diverse applications. In response to this need, the BB-KI Chips consortium aims to develop a series of hardware-oriented courses with real-world AI applications. This consortium includes the Technical University of Munich (TUM) and the University of Potsdam (UP), which both offer a wide range of courses that focus on AI basics, AI algorithmic development, general computer architectures, chip design, and as well applications of AI. In the BB-KI-CHIPS project, these different capacities are planned to be tightly integrated into a unified curriculum covering knowledge from chip design over AI algorithms and techniques to applications.
- Subjects
BAVARIA (Germany); BRANDENBURG (Germany); TECHNISCHE Universitat Munchen; ARTIFICIAL intelligence; COMPUTER architecture; COLLEGE teaching; HARDWARE; CAPACITY requirements planning
- Publication
ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 2022, Vol 10, Issue 5/W1, p75
- ISSN
2194-9042
- Publication type
Article
- DOI
10.5194/isprs-annals-X-5-W1-2023-75-2023