| Autor: |
Xiong, Z., Stober, D., Krstić, M., Korup, O., Arango, M. I., Li, H., Werner, M. |
| Předmět: |
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| Zdroj: |
ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences; 2022/2023, Vol. 10 Issue 5/W1, p75-81, 7p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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