Gaia is a decentralized computing infrastructure enabling the creation, deployment, scaling, and monetization of AI agents. It leverages open-source LLMs to provide advantages in privacy, cost, and reduced bias. The platform uses Gaia domains to organize nodes, ensuring trust, performance, and economic incentives. Payments and rewards are managed using Purpose Bound Money smart contracts. The GaiaNet token facilitates governance, staking, and transactions. Nodes consist of a high-performance runtime, fine-tuned LLMs, and various tools. Customization options include prompt engineering, knowledge base adjustments, and model fine-tuning.
• scalability
• cost efficiency
• privacy
• reduced systematic bias
• monetization of ai agents
• ai agent creation and deployment
• decentralized computing infrastructure
• open-source llms support
Gaia is a decentralized computing infrastructure that enables individuals to create, deploy, scale, and monetize their AI agents.
The primary goals are to empower individuals to incorporate their private knowledge and expertise into personal LLM agent apps and to enable them to scale and monetize their LLM agents as services.
Open-source LLMs offer advantages in privacy, cost, and reduced systematic bias. They are also rapidly closing the performance gap with closed-source LLMs.
A Gaia domain organizes Gaia nodes under a single Internet domain name, ensuring trust, performance monitoring, load balancing, and economic incentives for node operators. It acts as a trust provider and economic facilitator within the decentralized network.
Gaia addresses these challenges by providing a decentralized infrastructure that supports application portability, virtualization, and security isolation. It offers a solution to high costs and privacy concerns associated with traditional SaaS by enabling users to create, deploy, and monetize their own AI agents with customizable components. The network uses Purpose Bound Money smart contracts to manage payments and incentivize trust, and it organizes nodes into Gaia domains to ensure reliable and trusted AI agent services.
Payments are managed through GaiaNet domains' smart contracts using Purpose Bound Money. Users pay for API services in stable coins, and domain operators distribute revenue to node operators and incentivize trust through tokenomics designs like mining and staking.
The GaiaNet token is used for DAO governance, staking to vouch for domain operators' trustworthiness, and as a payment utility to facilitate transactions and balance network supply and demand.
A Gaia node provides LLM services to the public. It consists of a high-performance runtime, a finetuned LLM, a knowledge embedding model, a vector database, a prompt manager, an open API server, and a plugin system for external tools.
Everyone is welcome to run a Gaia node on their own machine, whether it is a CPU or a GPU machine.
Yes, RAM is critical for running a Gaia node. A minimum of 8GB is required to run a small-size LLM like the Qwen-0.5B model or the Phi-3-mini model. A machine with 16GB is much better.
Yes. We will support newly released open-source LLMs as soon as possible. Stay updated by following Gaia’s Hugging Face page and the node-config GitHub repository, which contains instructions for running all the popular nodes.
Yes, we offer a tool that simplifies the creation of knowledge embeddings. Just upload your chunked text, and we'll generate the embeddings for you. Additionally, we have documentation and have tested popular tools like LlamaIndex to help you create embeddings on your own machine. See the Knowledge bases guide here.
Absolutely! The Gaia node is a drop-in replacement for OpenAI API in agent and LLM apps. On the Gaia node dashboard, you will see a table that shows how to replace OpenAI parameters in those apps.
After successfully running a Gaia node on your machine, you should join the Gaia protocol network and earn rewards for sharing your computing power. To do this, bind your node ID and device ID to a MetaMask account. Detailed instructions can be found here.
You can customize your Gaia node in several ways: * Prompt Engineering: Modify the system prompt to adjust the LLM's behavior. * Knowledge Base: Customize the knowledge base to better suit your needs. * Model Fine-Tuning: Fine-tune the model with domain-specific knowledge to improve performance in specific areas.
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