# Decentralized Model Training Decentralized Model Training in Low-Code AI leverages the power of distributed computing and blockchain technology to enable collaborative and secure model development. Unlike traditional centralized AI systems, where all training is performed on a single server or data center, Low-Code AI’s decentralized approach allows for the training process to be spread across multiple contributors. This provides several key benefits, including enhanced security, improved model accuracy, and a more equitable ecosystem. --- # 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://low-codeai.gitbook.io/docs/how-it-works/decentralized-model-training.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.