Content Strategy and Governance

From a Documentation Team to Pioneers in AI Transformation
2026年4月10日 • 0 Comment

As a documentation team, we are often the “fall guys” — taking the blame while having little voice. How can we find a way to break the deadlock? By restructuring the manual development process through structural transformation and AI-powered content creation. Supporting localization and global business, we enhance the core value of the team. Through rich media transformation, we increase the team’s output value and customer satisfaction. What plans and explorations have we made at different stages? Let us share our team’s transformation journey, in the hope of providing some inspiration for other teams still exploring their way.

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Analyzing NVIDIA’s Documentation Ecosystem: How Domestic AI Chips Can Bridge the Gap
2026年4月10日 • 0 Comment

NVIDIA’s technical documentation system is at the heart of its CUDA ecosystem dominance, seamlessly connecting products with developers. In this talk, we’ll break down the architecture, writing logic, tools, and publishing systems behind NVIDIA’s official docs — and show how standardized, modular, scenario-based documentation lowers developer barriers and amplifies technical authority. We’ll then compare this with the current state of domestic AI chip documentation, identify critical gaps beyond hardware performance, and explore actionable pathways for China’s chip ecosystem to catch up and break through.

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Reinventing and Evolving: The New Paradigm of Content Strategy Driven by AI
2026年2月10日 • 0 Comment

The rise of generative AI is fundamentally redefining the boundaries and value of content strategy. While the traditional “plan → create → distribute → manage” content loop remains a useful framework, its core has undergone profound changes: shifting from “document creation” to building an “intelligent content ecosystem” and moving from serving “human readers” to accommodating both “machine understanding and invocation.” This isn’t merely an addition to existing content strategies; it represents a paradigm-level transformation.

This session explores the construction of an Intelligent Content Ecosystem, where knowledge continuously gains value through human-AI collaboration. It highlights the value leap for content teams—transitioning from information communicators to strategic decision-support partners. For practitioners, mastering this new logic means evolving from executors into architects of enterprise knowledge infrastructure.

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When AI Makes Everything Faster: Why Has Decision-Making Become the Greatest Bottleneck?
2026年2月10日 • 0 Comment

AI is dramatically expanding the external world: more information, faster analysis, more options. Yet a counterintuitive outcome is emerging: why is decision-making becoming harder — and scarier — with AI?

When AI can present multiple “seemingly reasonable” answers at once, traditional decision-making approaches that rely on external analysis, data, and models begin to break down. External systems can no longer make the real trade-offs for us. This signals a critical shift: the rise of AI is moving decision-making from “looking outward for answers” back to “looking inward for judgment.” In other words, AI is not the adversary of decision-making — it is finally returning the ultimate responsibility of choice back to the human. When AI optimizes the external dimension to its limit, it pushes us to evolve our decision-making role: from being analysts of external information and environments to becoming Chief Decision Officers aligned with our inner values, purpose, and meaning.

What does a Chief Decision Officer do? When options approach infinity and efficiency is high, what truly determines outcomes is no longer how much information we possess, but clarity on:
What are you choosing for?
Which direction are you willing to pay the price for?
Behind your hesitation — is it rational weighing, or internal avoidance?

This topic focuses on the real bottlenecks decision-makers face in the AI era, exploring why decision difficulty is shifting from the technical level to the human level — cognition, psychology, and identity — and introduces the perspective of Purpose-Driven Decision-Making. It helps audiences understand: when AI perfects the external dimension, what truly cannot be avoided is the upgrade of human internal decision-making capability. Decision-making must return to a “whole person” to complete the final judgment. It is not just about external information — it is about integrated human judgment in complex environments.

What the audience will take away is not more tools or models, but a clearer decision-making lens: how to make the critical trade-offs that only a “human” can make — even with AI’s support.

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Anchoring the Digital Trend, Activating the Potential of Data-From the Practice of Data Transformation of Inovance
2026年2月10日 • 0 Comment

In response to the digital transformation trend, technical documentation management urgently requires upgrades, with common pain points including low governance efficiency, compliance challenges in global expansion, and subpar user experience. This presentation highlights Inovance Technology’s practical solutions, detailing actionable approaches to address these pain points through digital means, offering reusable insights for technical documentation professionals.

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AI-Driven Upgrade Across the Full Technical Documentation Lifecycle
2026年2月10日 • 0 Comment

This presentation focuses on lifecycle-based management of technical documentation, covering the complete workflow from concept analysis and content planning to authoring, multi-round reviews, testing and validation, and final release. Drawing on real-world content domain development scenarios, the presentation systematically explores how AI can be applied at each stage, along with practical insights into implementation.

The presentation also defines a structured human-AI collaboration model: AI takes on repetitive and rule-based tasks, allowing human experts to concentrate on value-based decision-making, ensuring technical accuracy, and improving user experience. Through practical case studies, the presentation demonstrates how AI can improve both the efficiency and quality of documentation production, supporting the evolution of technical communication toward more intelligent, standardized, and efficient practices.

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