# The Problem: AI Accessibility Gap

#### Current Challenges

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.

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**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.
