Federated AI Platform

The federated AI platform, the world's first decentralized machine learning platform, enables all AI resource contributors—including data, model, and GPU providers—to participate in serving AI agents and apps while earning rewards.

It provides an affordable and highly available decentralized AI infrastructure that facilitates economic collaboration among AI agent creators, users, and AI resource providers, creating a more inclusive and fair economy while prioritizing privacy and ownership in AI agents. This section mainly explains the challenges solved by the platform, the capabilities it brings to AI agents, the core technologies driving it, and its integration with the ChainOpera AI ecosystem.

Federated AI Platform: Enabling Collaborative Intelligence

Federated AI Platform solves three fundamental challenges in the current Crypto AI Agent field:

• From the perspective of collaborative economic models, many current Web3 AI agents rely on models and agent services built on the web2 platform, and do not really allow decentralized AI resource providers (data/model/GPUs) to participate in contributions and obtain rewards. The federated AI platform opens up multilateral value flows in the community that can help AI resource providers gain rewards from the end user’s consumption of AI agents.

• From the perspective of GPU computing power, there is currently a lack of an enterprise-grade low-code platform for training and serving AI models that power agents, leveraging a pool of highly available, low-cost, and scalable decentralized GPUs. The Federated AI Platform allows Web3 developers to participate in the model training and deployment required by AI agents, without having deep expertise in AI. It has experienced many years of enterprise services and currently has the ability to serve a large number of AI agent creators and users.

• By leveraging on-device model training and serving, it protects personal privacy and enables the creation of companion AI agents powered by private human data, truly achieving the goal “Your Personal Data, Your AI Agent”. This is backed by ChainOpera team's years of pioneering advancements in federated learning technology.

The above figure illustrates the complete platform architecture of ChainOpera AI. User-contributed data via the mobile AI app “AI Terminal” enables community members to collaboratively train and serve AI models, which directly support AI agents launched through the Federated AI OS. When end users pay for AI agent services, the AI resource providers are rewarded accordingly.

Empowering “AI Terminal”: the Community-driven AI Agent in Your Pocket

ChainOpera's upcoming "AI Terminal" mobile app will serve as a tangible example of the capabilities of the Federated AI Platform. 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 people’s personal companion that represents each person and completes various tasks in daily life and work, such as trading meme coin and BTC. 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.

Core Technologies of the Federated AI Platform

The Federated AI Platform 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, FedML.ai, ScaleLLM, and edge-cloud hybrid model serving have made it unique in the web3 industry. It stands as the only model service provider capable of delivering stable, cost-effective, scalable, and fast model-serving APIs using decentralized resources.

The platform leverages extensive expertise in decentralized computing, including decentralized training, federated learning, and decentralized model serving of LLMs on L1 blockchain. From developer’s perspective, federated AI Platform provide following features:

• AI Marketplace

• Data Services

• Model Training Model Deployment and Inference

• Model Orchestration for AI Agents

• Decentralized GPU Scheduling

The Federated AI Platform helps developers to launch complex model training, deployment, and federated learning anywhere on decentralized GPUs, multi-clouds, edge servers, and smartphones, easily, economically, and securely. Highly integrated with FedML Open Source Library, Federated AI Platform provides holistic support of three interconnected AI infrastructure layers: user-friendly MLOps, a well-managed scheduler, and high-performance ML libraries for running any AI jobs across GPU Clouds.

A typical workflow is shown in figure above. When a developer wants to run a pre-built job in Studio or Job Store, The Launch CLI swiftly pairs AI jobs with the most economical GPU resources, auto-provisions, and effortlessly runs the job, eliminating complex environment setup and management. When running the job, the platform orchestrates the compute plane in different cluster topologies and configuration so that any complex AI jobs are enabled, regardless of model training, deployment, or even federated learning.