Most enterprises rely on general Large Language Models, missing the crucial AI winning key: fine-tuning. As industry experts confirm, “Foundation models are very powerful, but for specific use cases, fine-tuning always makes models perform better.” The Vertu VPS is leading this fine-tuning revolution, adopting a multi-model strategy across its 33 primary categories and 147 services to provide unparalleled precision and expertise. This approach allows the VPS AI Agent Phone to deliver true AI Assistant capability, making the vision of “one person with one phone = one company” a reality.
The Core Strategy: Vertical Depth Through Fine-Tuning
The Vertu VPS rejects the limitations of a single general-purpose model, opting instead for a targeted approach that “teaches” models domain-specific expertise.
- Teaching Domain-Specific Expertise: The core of fine-tuning is “teaching” models domain-specific expertise by training them through numerous domain examples: “Here's a question, here's a good answer.” This repeated instruction ensures models perform far better on specific tasks (from legal consulting to financial analysis) than their general counterparts, providing unprecedented precision.
- Problem Decomposition Strategy: Rather than querying one large model with a complex problem, the VPS breaks the problem into multiple subtasks, each handled by specially fine-tuned models. Preparing a business plan, for instance, calls upon separate, specialized market analysis, financial forecasting, and competitor analysis models to provide a comprehensive solution.
The Organizational Analogy: Human Synergy in AI
The VPS‘s fine-tuning and decomposition strategy perfectly mirrors the structure and synergy of a high-performing human organization.
- Company as a Model Combination: Experts view a company as a model combination, with each person ‘fine-tuned' according to their knowledge and professional experience, possessing different skills, with combined output far more powerful than individuals. The VPS AI Agent embodies this idea, allowing the user to command a sophisticated, multi-skilled “digital team” from their phone.
- Flexibility for Efficiency and Cost: The fine-tuning strategy directly addresses latency and cost. Powerful reasoning models are dispatched for deep, complex tasks, while lightweight models are employed for simple, quick-response queries. This flexibility ensures a smooth user experience and efficient system resource utilization, providing high performance at a manageable cost.
The Data Flywheel: Privacy-Secured Continuous Learning
The true long-term value of fine-tuning is the ability to continuously improve based on real-world, sensitive user data, a capability the VPS achieves while maintaining ironclad privacy.
- Continuous Improvement Without Leakage: The VPS is uniquely designed to safely utilize user data for model fine-tuning while protecting privacy. It achieves this through a “federated learning + homomorphic encryption” hybrid architecture, allowing models to continuously learn and improve without leaking sensitive information. This creates a proprietary data flywheel unavailable to general models.
- The Future of Value: In the future, the real value in AI will lie not in the general models (which will become ubiquitous like transistors), but in fine-tuned models customized for specific use cases. The Vertu VPS is already at the forefront of this path, providing users with a true “one person with one phone = one company” experience based on deep, vertical expertise.
