> For the complete documentation index, see [llms.txt](https://neuralbyte.gitbook.io/neuralbyte-erc/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://neuralbyte.gitbook.io/neuralbyte-erc/introduction/challenges-in-traditional-ai-model-training.md).

# Challenges in Traditional AI Model Training

**Challenges in Traditional AI Model Training:**

* Dependency on GPU and TPU: Traditional AI model training heavily relies on Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs), which can be expensive and have limited availability.
* Cost Barriers: The high cost of GPU and TPU usage poses a significant barrier for small-scale developers and researchers, hindering innovation and progress in the AI field.
* Scalability Issues: Scaling AI model training with traditional hardware often faces limitations in terms of scalability and efficiency, particularly for large-scale projects.