> For the complete documentation index, see [llms.txt](https://2435ghj424g6j.gitbook.io/gm/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://2435ghj424g6j.gitbook.io/gm/ai-model/training.md). # Using Offsetdata for AI Training Offsetdata offers a secure and transparent method for collecting, storing, and utilizing data for AI training purposes. ### Data Collection Data submitted via Offsetdata is organized into collections containing up to 1 million records each. This provides structured datasets suitable for training AI models. Key features of Offsetdata data collections: * Immutably recorded on blockchain to prevent tampering. * Associated metadata provides context and descriptions. * Customizable access controls on who can use the data. * Ability to audit how data is used for training. ### Enabling AI Transparency The blockchain ledger provides transparency into the origin and characteristics of the training data used by AIs. This mitigates issues around bias, quality, and licensing. Developers can validate that models are trained on ethically-sourced data from Offsetdata by auditing the blockchain transactions for the collections utilized. ### Retrieving Data for Training Users who submitted data or purchased access to collections can retrieve the datasets through Offsetdata APIs and SDKs. The data can then be directly used for model training and validation. Offsetdata enables convenient access to high-quality, unbiased data to power more responsible AI development. ### AI Safety With data stored on Offsetdata, developers can better monitor and control how models consume inputs compared to scraping unknown sources. This improves AI safety and stability. The structured data collections minimize training data poisoning attacks that could cause models to learn dangerous behaviours. ### Usage-based Billing Offsetdata charges only for what you use with no upfront costs. Access to data collection for training is metered and billed based on consumption. This allows flexible scaling AI training without significant data acquisition expenses. ### Summary Offsetdata facilitates more trustworthy, accountable AI development through transparent data collection, auditability, and flexible access. Leverage Offsetdata as a secure data marketplace for powering your next AI. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## 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, and the optional `goal` query parameter: ``` GET https://2435ghj424g6j.gitbook.io/gm/ai-model/training.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.