Bridging the Academia-Industry Divide

The booming development of artificial intelligence (AI) has caused a huge gap between scholarly work and the industrial practice. The gap creates problems to the two sectors consequently affecting the smooth flow of knowledge and skills. The way out of this problem is by taking a broad approach to AI education, aiming at breaking the gap that exists between theoretical foundation and practical applications. This paper suggests a framework of bringing together academic and industrial views in AI education. The integration of theory and practice will help students create the whole picture of AI technologies and implications. The described solution focuses on joint university-industry projects, where students could solve state-of-art problems and also have an opportunity to receive an insight into industrial practices. In addition to that, the framework integrates interdisciplinary considerations as it is realized interdisciplinary AI applications exist in different categories.