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E-raamat: World Conference of AI-Powered Innovation and Inventive Design: 24th IFIP WG 5.4 International TRIZ Future Conference, TFC 2024, Cluj-Napoca, Romania, November 6-8, 2024, Proceedings, Part I

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World Conference of AI-Powered Innovation and Inventive Design: 24th IFIP WG 5.4 International TRIZ Future Conference, TFC 2024, Cluj-Napoca, Romania, November 6-8, 2024, Proceedings, Part ISuurem pilt
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This book constitutes the proceedings of the 24th IFIP WG 5.4 International TRIZ Future Conference on AI-Powered Innovation and Inventive Design, TFC 2024, held in Cluj-Napoca, Romania, during November 68, 2024.





The 42 full papers presented were carefully reviewed and selected from 72 submissions. They were organized in the following topical sections: 





Part I - AI-Driven TRIZ and Innovation





Part II - Sustainable and Industrial Design with TRIZ; Digital Transformation, Industry 4.0, and Predictive Analytics; Interdisciplinary and Cognitive Approaches in TRIZ; Customer Experience and Service Innovation with TRIZ.
.- AI-Driven TRIZ and Innovation.



.- LLM-based Extraction of Contradictions from Patents.



.- AI based search engine to deploy a TRIZ pointer to chemical effects.



.- Integrating Generative AI with TRIZ for Evolutionary Product Design.



. Harnessing Generative AI for Sustainable Innovation: A Comparative Study of
Prompting Techniques and Integration with Nature-Inspired Principles.



.- Neuro-Symbolic AI-Driven Inventive Design of a Benzoic Acid Extraction
Installation from Styrax Resin.



.- Enhancing TRIZ Contradiction Resolution with AI-driven Contradiction
Navigator (AICON).



.- Research on disruptive technology prediction methods based on BERT model
and graph theory analysis.



.- Exploring Cross-Domain Technological Opportunities through Customized
Training of the Bert Model.



.- Resource Mining Method of Idealization Driven Product Innovation Process
of AI-Aided.



.- Use of AI in the TRIZ innovation process: a TESE-based forecast.



.- Evaluating the effectiveness of generative AI in TRIZ: A comparative case
study.



.- On opportunities and challenges of large language models and GPT for
problem solving and TRIZ education.



.- Challenges in Inventive Design Problem Solving with Generative AI:
Interactive Problem Definition, Multi-Directional Prompting, and Concept
Development.



.- The Evolving Landscape of TRIZ: A Generative AI-Powered Perspective.
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