# Elimination of GPU and TPU Dependency Unlike traditional AI processing methods that rely on specialized hardware such as GPUs and TPUs, NeuralByte leverages the collective computing power of its decentralized network. By distributing processing tasks across multiple nodes, NeuralByte effectively overcomes the limitations imposed by centralized hardware, offering scalability and flexibility to users. * NeuralByte Token integrates seamlessly with GPU and TPU clusters, harnessing their parallel processing capabilities for accelerated AI and ML workloads. * Users can specify their requirements for GPU or TPU resources, and the marketplace matches them with suitable providers. * Compatibility with diverse hardware configurations ensures flexibility 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://neuralbyte.gitbook.io/neuralbyte-erc/ecosystem/elimination-of-gpu-and-tpu-dependency.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.