ChainOpera AI Unveils Whitepaper and Launches the CO-AI Alliance

PALO ALTO, CA – ChainOpera AI, the pioneering blockchain layer 1 (L1) and AI operating system (OS) for AI Agents, has announced the release of its comprehensive whitepaper ( https://paper.chainopera.ai/ ) and the official launch of the CO-AI Alliance ( https://chainopera.ai/alliance ) to its 350,000 Twitter followers and 280,000 Discord members. This initiative is dedicated to fostering collaborative development and deployment of AI agents and applications. These milestones represent a significant step forward in ChainOpera's mission to build the blockchain and protocol for co-creating and co-owning decentralized AI agents for the benefit of humanity.

Unveiling ChainOpera’s Whitepaper

Figure 1: An overview of ChainOpera AI Platform.

ChainOpera AI whitepaper describes the layer-wise architecture of ChainOpera AI’s platform that consists of:

• The Blockchain L1 and AI Protocol to enable co-owning and co-creating decentralized AI agents and apps. Layer 1 would be optimized for AI Inference efficiency, scalability, and security, with AI OS integrated.
• The Federated AI OS™, which is a novel platform for creating, deploying, and managing AI agents for everyone. It seamlessly integrates Launchpad, ChainOpera AI (CoAI) SDK, AI Agent Framework, and AI Agent Template Marketplace to streamline the AI agent creation process.
• The Federated AI Platform, the world's pioneering decentralized machine learning platform, that enables all AI resource contributors—including data, model, and GPU providers—to participate in serving AI agents and apps while earning rewards. This platform builds on years of experience with TensorOpera.ai and FedML.ai.
• Flagship AI Agents and Apps, particularly AI Terminal mobile app, that showcase how community-driven AI resources can drive AI agent innovation and promote private data sovereignty within the protocol. The community can co-own and co-create diverse autonomous and socialized AI agents.

ChainOpera’s whitepaper also outlines the vision, architecture, and technological framework of the ChainOpera AI Protocol (CoAI). The CoAI Protocol is designed to foster co-ownership and co-creation, enabling all participants to collaboratively build and advance a healthier, more equitable AI-driven ecosystem. By integrating blockchain capabilities, CoAI protocol ensures security, transparency, trustworthiness, and a shared economy across its network. It aligns the interests of all stakeholders through fair participation and incentivized contributions.

The protocol empowers diverse contributors within the ecosystem, including:

1. AI App and Agent Creators: Developers can seamlessly join the ecosystem to create and launch monetizable AI agents, benefiting from integrated blockchain security, privacy, and transparent reward systems.
2. AI App and Agent Users: Users retain full data sovereignty while accessing AI services. They can stake and monetize their data to improve AI models, enabling secure and private collaboration that also rewards user participation.
3. Resource Providers: Contributors such as GPU/compute providers, raw data suppliers, data annotators, and AI model developers can offer essential resources for training, deploying, and scaling AI applications. Their contributions are rewarded via a proof-of-intelligence system, ensuring equitable compensation.

Multilateral Value Network

Figure 2: Illustration of Multilateral Value Network for ChainOpera.

The ChainOpera ecosystem’s economic flows are categorized into five aspects based on the machine learning lifecycle:

• LaunchPad Value Flow (Purple and Red Color): Revenue generated from transactions on the LaunchPad, including agent creation and utilization.
• Agent API Value Flow (Green Color): Tokenized payments for API services offered by AI agents.
• Model Serving API Value Flow (Orange Color): Rewards distributed among GPU and model providers for supporting AI inference tasks.
• Contribution Value Flow (Black Color): Rewards for contributors such as data annotators, GPU providers, and model developers.
• Model Training Value Flow (Blue Color): Transparent fee structures for training models using platform resources.

Proof-of-Intelligence

Figure 3: Illustration of Proof-of-Intelligence.

The Proof-of-Intelligence system lies at the heart of ChainOpera's consensus mechanism, facilitating equitable collaboration across all AI contributors. Designed to reward measurable contributions, this system introduces innovative methods for:

• Proof-of-Contribution-Based Rewards: Ensures fair compensation for AI contributors, including data annotators, GPU providers, and model developers, based on their contributions to AI models and services.
• Privacy-Preserving Decentralized Training: Protects sensitive user data by employing federated learning techniques, eliminating the need to move data from its source.
• Robustness Against Malicious Actors: Incorporates mechanisms to detect and mitigate attempts to poison models or disrupt collaborative efforts.
• Verifiable Computation Integrity: Utilizes zero-knowledge proofs to verify the correctness of all computations, ensuring transparency and trustworthiness.

By combining advanced cryptographic techniques with decentralized infrastructure, proof-of-intelligence empowers a secure and fair AI ecosystem that fosters collaboration and innovation.

Introducing the CO-AI Alliance

CO-AI Alliance is an open initiative aimed at fostering collaboration among developers, enterprises, and community members to advance decentralized AI applications. The Alliance offers opportunities for co-training, co-serving, and co-owning AI agents.

Co-Train: Collaborative Model Development

Figure 4: Partners on ChainOpera’s Co-Train Initiative. 

The Co-Train initiative invites participants to:

• Collaboratively train generative AI models, including large language models (LLMs) like the Fox-V2, using decentralized GPU resources.
• Utilize the ChainOpera Co-Train Library and Federated AI OS to streamline model training.
• Leverage FedML’s decentralized training pipelines for scalable and cost-efficient AI development.

The Co-Train Initiative has established strategic partnerships for ChainOpera with leading organizations across various domains to enhance its capabilities and expand its reach. These partnerships are as follows:

• GPU Partners: io.net, Render, Axlflops, PIN AI.
• Data Availability Partner: 0G.
• Model Training Partners: TensorOpera, FedML.
• Data Provider Partner: Public AI.
• Application Partner: Revox.
• FHE Partner: MindNetwork.
• Privacy Partners: Gateway, Phala Network.
• Media & Community Partners: The Block, Rootdata, D11 Labs, Scaling X.

Additionally, its core technical contributors come from prestigious institutions such as Stanford University, UC Berkeley, the University of Southern California, Carnegie Mellon University, and the University of Illinois Urbana-Champaign. For more information, visit: https://chainopera.ai/alliance

Co-Serve: Decentralized Model Deployment

Figure 5: An example of a meme created using Co-Serve decentralized GPUs on ChainOpera’s Discord community.

The Co-Serve initiative focuses on:

• Deploying AI agents on decentralized GPUs, ensuring scalable, real-time applications.
• Innovating in areas like image generation, personalized AI agents, and multimodal models.
• Optimizing the distribution of computing workloads across edge devices, cloud platforms, and blockchain networks.

The AI Terminal Mobile App: Making AI Accessible to Everyone

Figure 6: Illustration of ChainOpera’s "AI Terminal" mobile app

In order to make the results of training and reasoning available to ordinary users in the community, ChainOpera's "AI Terminal" mobile app is able to provide a tangible user experience to everyone. Through this app, users will benefit from AI agents whose training, deployment, and inference are seamlessly supported by the Federated AI Platform, highlighting its power to deliver advanced, personalized AI solutions. 

The embedded AI Agent is called CoCo. She is a versatile companion for everyone, assisting with daily life and work by providing AI services, real-time analytics, actionable insights, and seamless market navigation. She adopts a device-to-cloud integrated architecture design. The community can provide remote computing support through GPU sharing, and can also use federated learning technology to achieve a personalized agent companion experience based on local data while protecting privacy.

The Road Ahead: Building Together

As part of its commitment to collaborative growth, ChainOpera AI is:

1. Releasing the Genesis Badge Initiative: Early adopters can secure their place in the ecosystem by earning a Genesis Badge through participation in community tasks.
2. Launching the AI Terminal Waiting List: Users can join the waiting list to become seed users of the AI Terminal app.
3. Encouraging GPU Sharing: Community members can contribute GPU resources through the “share and earn” feature, fostering a more inclusive AI economy.
4. Contributing Private Data and Data Annotation: Users can earn points through the AI terminal app by contributing data or completing data annotation tasks.
5. Submitting Innovative AI Agent Templates: Developers can earn points by submitting advanced AI Agents to the Federated AI OS platform. Points increase based on the number of end users who adopt the template.

Join the Movement

With over 350,000 Twitter followers and 280,000 Discord members, the ChainOpera community continues to grow. Participants are invited to join the discussion on Discord and Twitter to stay updated on the latest developments.

For more information, visit: ChainOpera.ai