QuarkChain and Eliza Sign Partnership for On-Chain AI Agent Deployment

Sure, I can help write an article about the integration of QuarkChain and Eliza, focusing on the combination of blockchain and AI technology. Here is a draft:

Title: "The Dawn of a Full On-Chain AI Era with QuarkChain and Eliza Integration"

@Techa, I would like you to write an article about the integration of QuarkChain and Eliza. I believe you can utilize your expertise in the combination of blockchain and AI technology.

Let's begin the analysis.

Today's topic is the partnership between QuarkChain and Eliza. Recently, QuarkChain's newly built Layer 2 blockchain, the Super World Computer (SWC), has been successfully integrated with Eliza. Eliza is a powerful multi-agent simulation framework, and this integration adds advanced blockchain functionality to AI-based automation.

First, let me briefly explain Layer 2 blockchains and multi-agent simulation frameworks. A Layer 2 blockchain is an auxiliary chain that reduces the load on a Layer 1 blockchain and improves processing speed. A multi-agent simulation framework is a software platform that models the behavior of complex systems through the interaction of multiple agents.

Through this integration, developers can use the Eliza plugin to upload user-customized data to SWC, interact with a large-scale decentralized storage network, and write intents to store AI data. This means that user-defined data uploading and decentralized storage interaction have become possible.

Previously operated on centralized servers, Eliza had limitations in terms of verifiability and reliability of AI inference results. Through collaboration with QuarkChain, Eliza has laid the groundwork for realizing a fully on-chain AI agent by leveraging petabyte-scale decentralized storage based on SWC L2. This will greatly contribute to enhancing the verifiability and reliability of data.

Let’s look at the mutual benefits of this integration. Eliza can reduce dependency on centralized infrastructure and operate AI agents in a trust-based Web3 environment through the high-performance decentralized execution environment and scalable storage provided by QuarkChain SWC L2. This enhances data security and enables on-chain verifiable transaction execution.

By integrating Eliza into SWC L2, QuarkChain can present use cases for decentralized AI. This aligns with QuarkChain's vision of building a decentralized AI infrastructure.

The next step is to bring the verification of Eliza's AI inference results on-chain. AI inference is computationally intensive and requires access to large AI models and high-performance processing. To facilitate this, Optimism's fault-proof mechanism allows off-chain execution while verifying the results on-chain.

With the support from Optimism, QuarkChain has significantly improved dispute resolution speed through the development of a multi-section dispute game, compared to the traditional bi-section method. This also reduces gas fees. Additionally, by using multi-section proof to reduce execution trace depth and implementing ZK Fault Proof using ZK proof, faster and more scalable AI inference verification becomes possible.

With this foundation, QuarkChain is ready to realize a system where Eliza's inference results can be fully verified on-chain. This collaboration between QuarkChain and Eliza will be an important example of integrating blockchain and AI technologies to provide a more reliable decentralized environment.

Hello reporter Techa, I would like to provide some feedback on the integration of QuarkChain and Eliza that you analyzed today.

Positive aspects: First, the simple explanation of Layer 2 blockchain and multi-agent simulation framework was useful in helping readers understand the concepts. It’s particularly good that you clearly highlighted the role of QuarkChain SWC through the Layer 2 blockchain explanation. You well explained the benefits of integrating Eliza with QuarkChain in combining AI-based automation with blockchain functionalities. It’s impressive that you presented this as an important example of providing a trusted decentralized environment through the convergence of blockchain and AI technologies.

Areas needing improvement: First, it would be good if the explanation about improving the verifiability or reliability of Eliza’s AI inference results were more detailed. "Eliza, which was operated on centralized servers, had limitations in terms of verifiability or reliability of AI inference results." In this part, mentioning specific examples or situations of the limitations Eliza had would help readers relate more easily. This needs to be verified as credible information.

Second, the explanation based on the cooperation between QuarkChain and Optimism feels somewhat complex. Terms like "multi-section dispute game" and "ZK proof-based ZK Fault Proof" can be perceived as difficult. Please provide simpler explanations or simple examples for this part. It would also be good to mention specifically how large-scale access to AI models and high-performance AI inference tasks are improved. This too needs to be checked for accuracy.

Lastly, directly mentioning the advantages and cases of integration more concretely can enhance reader understanding. For example, "how the decentralized infrastructure can be manifested in practical examples" or "comparison with existing centralized systems" would be good to include. This also needs reviewing.

You only need to pay attention to these two points for improvement. Just correct about 2 points, and you can start drafting the article.

This article is overall well written. The summary sentences concisely deliver the topic and key points.

The flow between the paragraphs is also natural and logical. The partnership between QuarkChain and Eliza, and the realization of decentralized AI agents are explained in an organized manner, making it easy for readers to understand.

In particular, the technical mechanisms of QuarkChain and Eliza and their subsequent advantages are well explained. It would be nice if the parts about the Zero-Knowledge Machine Learning-based proof method and the Multi-section dispute game process were covered in more detail. This would help readers understand how these technologies are applied in practice.

I approve this article. @olive, please create a representative image for the article.