Tantárgy adatlapja
The objective of the course is to review the fundamentals and applications of recent AI-based tools, especially based on the GPT architecture. The course also considers the effect of these newly available tools in different areas, like software development, education, assessments, and ethical aspects of products created with them. Discussed topics are • Introduction of AI tools • Details of the underlying architectures, like GPT-3 • Recent publications discussing the development of new generative models • Tools and applications in software development o Available AI tools o Theory, models and data driving the tools o Roles of programmers in this new situation o Ethical and educational aspects • Tools and applications in educ ation o Available AI tools o Theory, models and data driving the tools o Roles of teachers and students in this new situation o Ethical and educational aspects (methodologies, assessments) • Tools and applications in other areas o Available AI tools o Theory, models and data driving the tools o Predicted changes induced by AI tools in the discussed field o Ethical and educational aspects (methodologies, assessments) • New strategies, possible future directions for research and development in one of the discussed areas |
List of the most important 2–5 pieces of required and recommended literature (lecture notes, textbooks fundamental articles) with bibliographical details (author, title, edition information (or specific pages), ISBN) |
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le="font-family: Arial"> • E. A. M. van Dis, J. Bollen, W. Zuidema, R. van Rooij, and C. L. Bockting, “ChatGPT: five priorities for research,” Nature, vol. 614, no. 7947, pp. 224–226, Feb. 2023, doi: 10.1038/d41586-023-00288-7. • C. Zhou et al., “A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT,” Feb. 2023, doi: 10.48550/arxiv.2302.09419. • P. Tillet, H. T. Kung, and D. Cox, “Triton: an intermediate language and compiler for tiled neural network computations,” in Proceedings of the 3rd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, Jun. 2019, pp. 10–19, doi: 10.1145/3315508.3329973. • “GitHub Copilot · Your AI pair programmer · GitHub.” https://github.com/features/copilot/ (accessed Mar. 09, 2023). |
List of those required professional competences, competence elements to the development of which the subject characteristically, materially contributes |
Understanding of the architecture of AI tools used in various applications and the underlying theories Ability to gather relevant publications connected to the subject of the course Ability to summarize scientific publications in the field of AI tools, draw conclusions and formulate relevant questions possibly leading to new research directions Ability to plan and document relevant measurement scenarios for the evaluation of AI tools Experience wi th AI tools through test cases, possibly through the modification of the code base of open-source tools Ability to reflect on the ethical and educational aspects of the information gathered on AI tools through paper review or experiments |
