> For the complete documentation index, see [llms.txt](https://maximize-ai.gitbook.io/maximize-ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://maximize-ai.gitbook.io/maximize-ai/maxiscreen/the-problem-ai-accessibility-gap.md).

# 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.

\
**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.