CNU GenAI Development Programme 2026
By the end of this four-session series, participants should be able to:
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Understand the evolution of generative AI and AI ecosystems in the recent period.
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Compare Chinese, Western and global AI ecosystems.
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Explain the changing role of universities in AI-driven societies.
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Evaluate strategies for building institutional AI capability.
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Understand the significance of human-machine collaboration and partnership working through 'GenAI Critical Collaborative Praxis'.
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Consider the future role of universities in technological and societal transformation.
(Click on the session titles for PPT downloads)
Session 1. Large Language Models in 2026 – a GenAI ecosystem analysis of China & the US.
This first session provides an up-to-date analysis of the rapidly evolving large language model landscape in 2026, examining the capabilities, strategic direction, and emerging ecosystems of the leading US and Chinese AI models. Through a China-US comparison, it argued that the future of AI competition will be determined not simply by model performance, but by the strength of the wider innovation ecosystems that connect technology, universities, industry, governance, and national development.
Session 2. AI Superintelligence and Assistive AI – two developmental pathways for Humanity
The second presentation argues that humanity faces two competing AI pathways - superintelligence centred on autonomous machines and assistive AI centred on human-machine collaboration. It is argued that the transformative challenge of the AI era is not creating intelligence beyond humanity, but developing new forms of collaborative intelligence that enhance human capabilities and social development.
Session 3. Constructing university GenAI ecosystems in the Chinese context
The future of AI depends not only on frontier technologies but on the strength of the socio-economic ecosystems that surround it. This third presentation explores how Chinese universities can become engines of innovation by mobilising collective intelligence, overcoming a Low-Baseline Technological Equilibrium and building effective GenAI institutional ecosystems.
The challenge of the AI era is not simply technological adoption but the development of new forms of human agency. This session examines how personal reflection, collaborative intelligence and critical praxis can help shape more purposeful relationships with generative AI. The aim is to extend understanding of partnership working with the Machine to help formalise current distributed GenAi expertise held by staff and students.