Enterprise AI Analysis
City AI: a strategic framework for urban artificial intelligence application and development
Given the potentially large economic and social impact of AI technological advancement like LLMs, further in-depth thinking is demanded about the ways in which AI exists in cities. In addition to discussions on ethical regulation, there are relatively few cross-cutting studies on how to realize the synergistic development of AI innovation and city, especially taking AI as a complete industry and governance object, under a broader urban and social context. Based on the policy practice of AI development in Shenzhen, this paper proposes a comprehensive framework for the integrated development of AI and the city, which involves the comprehensive consideration of technology systems, application scenarios, educational literacy and governance schemes. Meanwhile, the transformative trend of urban governance triggered by potential general artificial intelligence at a deeper level is further discussed in terms of planning concepts, digital architecture and governance decision-makings. By city AI integration, AI is expected to be better spread into general social activities and, through the driving effect of industrial economy, contribute to the competitiveness and sustainable development of cities.
Executive Impact & Key Metrics
Understand the scale and scope of AI integration in urban environments, as highlighted by this research into Shenzhen's strategic approach.
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Application Scenarios Identified
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Strategic Framework Pillars
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Deep Analysis & Enterprise Applications
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Technology System
Application Scenarios
Education & Literacy
Governance Scheme
AI Technology System Evolution
The paper emphasizes a comprehensive AI technology system, encompassing infrastructure, data, and models. This framework guides development direction, optimizes resource distribution, and clarifies research scope. The rise of LLMs highlights critical needs like significant computing power, high-quality datasets (moving from model-centric to data-centric thinking), and specific algorithms combining multimodal sensing and hardware control systems.
Shenzhen's approach recognizes the industrialization of AI, focusing on open-source solutions and an application-oriented generative path. The aim is to lengthen the AI industry chain and foster a dynamic industrial ecosystem where new architectures and business models naturally emerge from extensive promotion and popularization.
Strategic Application Scenarios
GPT-represented large models have vast potential in smart cities, from customer service to urban management. Shenzhen carefully selects and promotes AI applications in key fields and industries through a multi-level, multi-dimensional approach. Criteria for scenario selection include: mature application cases, alignment with Shenzhen's industrial advantages, and direct governmental support for implementation.
A total of 18 projects across 6 categories (including public service, urban management, health, manufacture) were identified. These focus on daily work and public services, leveraging both vertical industry-specific and regional comprehensive management models. The strategy also includes fostering "industry large models" as a pragmatic route to technology development and application while general large models mature.
Education & AI Literacy
A skilled workforce and digitally literate citizens are foundational for AI-city integration. Shenzhen’s educational strategy covers basic, higher, vocational, and social education. This involves integrating information awareness, digitalization, and computational thinking into primary and secondary education. Public education campaigns aim to enhance digital literacy and cultivate citizens capable of applying information technology to solve problems.
The supply of local talent is crucial, as foreign imports are limited. Vocational education, linked to the AI industry, is a primary path to cultivate autonomous multidisciplinary professionals who understand AI, computing, design, business, and biomedicine. This ensures a continuous supply of talent to meet the evolving demands of the AI sector.
AI Governance Scheme
Effective AI governance schemes are essential for trustworthy, responsible, and human-centered AI. The paper highlights the need for a synergistic mechanism that accommodates multi-stakeholder participation (public, private, academia, citizens). Shenzhen's existing AI industry regulations frame these roles, ensuring all actors are mobilized in urban AI construction.
A dynamic work chain, guided by an expert advisory committee, facilitates coordination. Development plans and application scenarios are annually updated and monitored. The rights of social groups are clarified, enabling participation in resource exchange, governance framework development, and sharing AI benefits. Practical measures include special offices, government priority markings for AI applications, dedicated fiscal funds, and ethical review mechanisms for social experiments and AI-generated content, with a legal basis established by the Shenzhen Special Economic Zone.
Transformative Impact
AI's Potential to Reshape Urban Economy and Social Fabric
Enterprise Process Flow: Shenzhen's AI Development Path
Open-source GPT-like Models
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Application-Oriented Generative Path
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Application Scenarios Drive Models
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Software Pulls Hardware Deployment
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Independent R&D Ecologies
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Dynamic Industrial Ecosystem
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Case Study: LLM Integration in Urban Public Service in Shenzhen
Shenzhen's digitalization engineering in urban public service, involving text processing, transitioned from traditional NLP toolboxes to a comprehensive LLM engineering approach. Key aspects include:
1. Secure Data Usage: Public data used for pre-training was handled with full safety considerations, deploying models in an independent, Internet-isolated environment.
2. User-Centric Design: Business personnel actively participated in designing work logic, testing results, and providing feedback (customer reception, matter distribution, knowledge query).
3. IP Ownership & Training: A special working group ensured that intellectual property rights of models trained with public data belonged to the public sector. Additionally, a free LLM training program for business personnel was included in the project contract.
This project represents an early, significant exploration of LLM use in public affairs across Chinese cities.
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Your Enterprise AI Roadmap
A phased approach ensures smooth integration and maximum value from your AI investments, mirroring successful urban AI strategies.
Phase 1: Strategic Planning & Ecosystem Building
Establish overarching goals, assess current infrastructure, identify key stakeholders, and define ethical guidelines. Focus on fostering collaboration and securing leadership buy-in for a comprehensive AI strategy.
Phase 2: Technology System Development & Application Piloting
Develop or acquire necessary AI infrastructure, data systems, and models. Prioritize and pilot application scenarios with clear value and measurable results, adapting an application-oriented generative path.
Phase 3: Talent Development & Ethical Governance
Invest in upskilling your workforce through education and training programs for AI literacy. Implement a dynamic governance scheme with multi-actor participation, focusing on transparency, fairness, and accountability.
Phase 4: Continuous Iteration & Public Engagement
Regularly monitor, evaluate, and iterate on AI implementations. Engage with internal and external communities to ensure adaptive responses to technological change and foster a sustainable AI-driven environment.
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