Decentralised Trust Infrastructure to contribute, collaborate with data and built payable models.
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By sourcing and refining data through datanets, OpenLedger enables model development for AI agents, chatbots, copilots, and a diverse range of next-gen applications.
Payable models are specialized language models capable of explaining which data points from datanets influence their inferences. This methodology ensures transparency, enabling the creation of fair models while also distributing rewards equitably to data contributors.
Datanets are our specialized data sourcing networks designed to support our payable models. These networks can be built by companies or subject matter experts, ensuring high-quality, domain-specific data tailored to the needs of our models.
Our payable AI models can powerup a variety of cutting-edge generative AI agents—smart assistants, coding copilots, game engines, trading systems, and more. You can bootstrap your innovative AI agents with specialized datanets and pay as you use them.
We make our AI systems payable through proof of attribution. Proof of Attribution is OpenLedger's core principle, ensuring fair reward distribution to data providers who contributed to model development.
Proof of Attribution provides visibility into how their data is utilized within AI models, ensuring they are fairly credited and compensated for their contributions though a decentralised trust mechanism
It enables developers to trace data sources and understand their impact on model behavior, making it easier to debug, refine, and optimize AI models for improved performance and reliability.
By leveraging Proof of Attribution, they can create AI Agents that are transparent and compliant with regulations, building trust and confidence among end users.
Proof of Attribution provides visibility into how their data is utilized within AI models, ensuring they are fairly credited and compensated for their contributions though a decentralised trust mechanism
It enables developers to trace data sources and understand their impact on model behavior, making it easier to debug, refine, and optimize AI models for improved performance and reliability.
By leveraging Proof of Attribution, they can create AI agents that are transparent and compliant with regulations, building trust and confidence among end users.
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