The Problem: AI Accessibility Gap
Last updated
Last updated
AI fine-tuning remains inaccessible due to several barriers:
Technical Complexity: Requires deep ML knowledge and programming skills
Computational Costs: High GPU/TPU costs prohibitive for individuals and small organizations
Data Preparation: Labor-intensive process requiring specialized expertise
Deployment Complexity: Production deployment introduces additional technical challenges
As Andrew Ng stated, "AI is the new electricity," but unlike electricity, AI's benefits are not universally accessible. The ability to fine-tune AI models remains concentrated among tech giants and specialized companies.
Market Gap Current solutions either: Simplify AI usage at the cost of customization flexibility, or Provide powerful tools that remain inaccessible to non-technical users There's a clear need for solutions that make AI fine-tuning both powerful and accessible.