# Reducing AI Inference Costs ## "Lowering AI inference costs is both a challenge and a priority." To address the dynamics of meme coin communities and the nature of image dissemination, AI computing power faces a significant challenge: linear growth in users results in exponential growth in AI inference costs. To tackle this issue, PinGo Cloud adopts a distributed cloud approach. By leveraging its strong market mobilization capabilities, PinGo will aggregate a large number of mid-to-low-end GPUs (such as RTX 4090) to create a vast distributed GPU computing network. This strategy aims to significantly reduce computing costs while maintaining high performance and scalability. --- # 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://pingo-work.gitbook.io/pingo/technology/reducing-ai-inference-costs.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.