The rapid development of artificial intelligence technology is changing the way the world operates. From generative content to financial risk control, medical predictions, and industrial automation, every industry is deeply integrating with AI. However, AI development also faces severe infrastructure bottlenecks: computing power monopolies, data silos, opaque training processes, and ambiguous value attribution. In response to these issues, the Origins public chain has emerged as a high-performance decentralized blockchain built specifically for the AI ecosystem, aiming to become a trusted foundation for the global intelligent computing network.
Origins is not merely for 'on-chain deploying AI' but redefines the way AI collaborates and the incentive mechanisms in the Web3 world from a technical architecture perspective. By integrating cutting-edge technologies such as ZK proofs, decentralized computing power markets, verifiable training mechanisms, homomorphic encryption, and MPC multi-party secure computation, Origins is building an open, trustworthy, and composable AI infrastructure protocol.
Origins' decentralized GPU resource scheduling protocol integrates mainstream global computing resource platforms, including Vast.ai, TensorDock, etc. Users can instantly obtain high-performance GPU instances through on-chain operations, supporting various mainstream AI chip resources including A100, H100, V100, and RTX4090. This system settles and allocates resources using the OR native token, significantly lowering the entry barriers for training and deploying large models.
At the same time, Origins has launched a verifiable AI training mechanism that, combined with ZK-ML technology, transforms the model training process into an on-chain auditable mathematical proof, ensuring that models behave as expected under trusted data and computing resources. Coupled with the data asset pricing protocol built by Origins, users can encrypt their private data for AI model access and receive income returns, achieving separation and reasonable circulation of data ownership, usage rights, and revenue rights.
At the model ecosystem level, Origins has established a decentralized model registration protocol that allows developers to upload, share, and earn revenue from their models. This mechanism incentivizes distribution based on on-chain call frequency and actual contributions, promoting a healthy and prosperous open-source AI model ecosystem. In the future, Origins will support LoRA fine-tuning models, multilingual large models, multimodal models, and more for on-chain registration and reuse, forming an on-chain AI modular capability system.
To further safeguard user privacy and data security, Origins is introducing FHE (Fully Homomorphic Encryption) and MPC (Multi-Party Computation) technologies, allowing data to participate in training and inference calculations while in an 'encrypted state,' particularly suitable for industries with high data privacy requirements. By incorporating data privacy protection into the underlying protocol layer, Origins is establishing a trusted and compliant moat for the popularization of AI.
With the imminent release of GPT-5, Apple's introduction of AI capabilities to the edge, and the ongoing investments by giants like Microsoft, Google, and Meta in AI infrastructure, a new era has begun for high-performance computing resources, open collaboration systems, and trustworthy AI scheduling mechanisms. Origins is building a Layer 1 that can support native AI economic activities, meeting the resource scheduling needs for model training and inference while providing clear economic incentives for model users, developers, and data contributors.
Origins believes that in the future, AI should not just be an exclusive tool for large model companies but should become a global public resource collectively built and mastered by decentralized communities. Through a powerful technology stack and open ecosystem design, Origins is constructing a fair, efficient, and trustworthy intelligent computing network for the world, and is writing its own technical footnote towards the Web3 world in the AI era.
