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Taiwan Tech and AAEON Technology Inc. deepen partnership and showcase Edge AI innovation result.[24 Apr. 2026]

Taiwan Tech and AAEON Technology Inc. jointly held an “Industry - Academia Collaborative R&D Achievements Exhibition” on March 18, 2026, under the theme “Edge AI and AI Applications”. The exhibition showcased key research achievements and innovative applications developed through their collaboration in artificial intelligence and edge computing.

A group photo of company executives and faculty project leaders at the “Industry–Academia Collaborative R&D Achievements Exhibition” jointly organized by Taiwan Tech and AAEON.

A group photo of company executives and faculty project leaders at the “Industry–Academia Collaborative R&D Achievements Exhibition” jointly organized by Taiwan Tech and AAEON.

The exhibition highlighted two main focuses: “Applying AI to Enhance Enterprise Operational Efficiency” and “Development and Application of Edge AI Technologies”. Through guided demonstrations and project presentations, a range of practical and innovative solutions were showcased, including an automated final product inspection platform, an AI-based defect detection system, and intelligent document analysis applications integrated with large language models (LLMs), as well as AI knowledge system development. These achievements demonstrated the integration of AI from research to real-world applications, effectively addressing industry demands for smart manufacturing and digital transformation.

A group photo of company representatives and Taiwan Tech faculty and students at the exhibition.

A group photo of company representatives and Taiwan Tech faculty and students at the exhibition.

At the enterprise application level, both parties shared real-world AI implementation outcomes, covering AI-assisted software development, AI-driven system management, data-driven AI transformation in enterprises, and the use of low-code AI tools. These presentations illustrated how companies can leverage AI to improve operational efficiency and decision-making quality. In terms of industrial applications, the exhibition also featured key technologies such as BMC firmware, the MIPI GMSL2 platform, and the RICO-Q6490 platform, demonstrating the depth of software-hardware integration and edge AI computing capabilities.

Professor Yuan-Hsiang Lin, Chair of the Department of Electronic and Computer Engineering at Taiwan Tech, noted that industry - academia collaboration has become a key driver of technological innovation and talent cultivation. Through practice-oriented partnerships, research outcomes can better align with industry needs, accelerating commercialization and real-world implementation.

AAEON Technology stated that its long-term and close collaboration with Taiwan Tech not only accelerates the development and validation of innovative technologies but also helps build a comprehensive talent pipeline, strengthening the company’s competitiveness in the AI field. Over the past year, the company has invested more than NT$15 million, supporting 12 collaborative projects and involving 86 faculty members and students.

A student team presented the “AI Knowledge System Development Project”, demonstrating innovative achievement that integrate LLMs with enterprise SQL databases, attracting significant attention from attending guests.

A student team presented the “AI Knowledge System Development Project”, demonstrating innovative achievement that integrate LLMs with enterprise SQL databases, attracting significant attention from attending guests.

The exhibition concluded successfully with a networking and Q&A session, during which faculty, students, and industry representatives engaged in in-depth discussions on AI development trends and practical applications. The event highlighted the complete chain of industry - academia collaboration, from research and development to implementation. Moving forward, both parties will continue to deepen their partnership, advancing Edge AI and intelligent applications to drive industrial upgrading and digital transformation.

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