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Building a "Multi-Party Shared Model Platform" for Industrial Clusters: Co-Creation, Sharing, and Win-Win AI Benefits

📌 Scenario Overview​

In the context of accelerating AI adoption, many SMEs in industrial parks or industry alliances possess valuable business data and practical experience but face challenges in independently training and applying large models due to limitations in computing power, technology, and talent.

With CSGHub Enterprise Edition, park operators or industry alliances can deploy a unified model management platform to facilitate member enterprises in collectively contributing data, co-building models, and sharing outcomes. Through granular permission management and service billing mechanisms, the platform ensures "resource protection with value sharing", creating a secure, efficient, and low-barrier AI infrastructure that collectively elevates the intelligence level of the entire industrial cluster.

🧭 Step-by-Step Guide​

1. Deploy Private Platform as an Industrial-Level Model Hub​

  • Led by park operators or alliances, deploy CSGHub Private Edition on intranets or cloud. The platform supports customizable namespaces and permission domains, enabling multi-party collaboration across different organizations.

2. Member Enterprises Contribute Data Assets​

  • All data is isolated in "Organization" or "Team" spaces for privacy compliance:
    • Enterprise A: Uploads industry text corpora (e.g., customer service dialogues, contract materials)
    • Enterprise B: Contributes product image data (e.g., packaging visuals, quality inspection images)
    • Enterprise C: Provides multimodal resources like voice data or sensor logs
  • Multiple model upload and dataset upload methods are supported.

3. Secure Sharing via Permission Isolation & Collaboration Mechanisms​

  • Platform capabilities:
    • Data access control by project/organization
    • Collaborative data annotation and cleaning
    • Prevents misuse while enabling cross-enterprise cooperation
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4. Joint Training of Industry-Specific Models​

  • After data aggregation, initiate "Joint Training Tasks":
    • Select base models (e.g., LLaMA, DeepSeek)
    • Configure training corpora (multi-enterprise sources supported)
    • Customize parameters and launch tasks
  • Output: Shared industry-tailored models

5. Model Service Sharing & API Billing​

  • All alliance members can:
    • Access and invoke shared models
    • Generate API keys for on-demand inference services
    • Adopt flexible billing (call volume/duration-based; multiple strategies supported)
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✨ Key Outcomes​

  • Establishes industrial-grade AI infrastructure for cross-enterprise resource synergy
  • Lowers AI adoption barriers and costs for SMEs
  • Delivers domain-knowledge-optimized models for superior scenario implementation
  • Drives intelligent transformation across industrial clusters, forming an ecosystem of "co-creation, sharing, and mutual benefit"