# Compared to traditional cloud GPU platforms, how does Janction's distributed idle GPU computing powe a. Computing resources have a natural cost advantage over cloud GPU manufacturers. Idle GPUs are dynamically and flexibly allocated according to customer needs. When AI customer demand is low, GPUs can selectively participate in PoW projects. When AI customer demand is high, GPU can be switched back b. Similar to traditional cloud GPU platforms, Janction has also designed a complete set of monitoring products for real-time monitoring of GPU activity, service quality, etc.; c. It is currently in the cold start stage, and the number of early users is relatively small. Janction’s operation and maintenance personnel can provide more time and energy to ensure service quality, and can summarize the accumulated experience and use it to develop peripheral products to ensure service --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.janction.ai/help-faq/faq/compared-to-traditional-cloud-gpu-platforms-how-does-janctions-distributed-idle-gpu-computing-powe.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.