> For the complete documentation index, see [llms.txt](https://hitensor-ai.gitbook.io/untitled/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://hitensor-ai.gitbook.io/untitled/2.-problems-within-the-ai-industry.md).

# 2. Problems within the AI Industry

**Despite its rapid evolution, the AI industry grapples with significant challenges:**

**A. High Computational Demands**

The intricate and large-scale nature of AI and ML projects demands extensive computational power, posing a barrier especially for smaller entities and solo developers.

**B. Resource Underutilization**

Globally, a vast amount of computational capacity lies idle, signifying a missed opportunity for more efficient resource use and a reduction in unnecessary electronic waste.

**C. Economic and Accessibility Barriers**

The hefty costs associated with acquiring and maintaining the requisite computational infrastructure often stifle innovation, limiting it to well-funded organizations and creating a disparity in the field of AI development