The Integration of AI and Decentralized Networks: Grass Will Launch an Airdrop Program

The Grass platform has announced that its closed testing phase has ended and is currently taking snapshots to determine the upcoming Airdrop eligibility. Users' network participation will be used as a benchmark for rewards, calculated based on time period weight.

In the coming weeks, the Grass team will provide a detailed Airdrop eligibility checklist and share more information about the tokenomics. The next phase of Grass's development will shift from building core infrastructure to supporting large-scale development, focusing on applications that combine user interest with network functionality.

It is reported that the number of users of Grass has exceeded 2 million. As a decentralized network, Grass aims to provide the necessary data for AI model training by accessing public networks. This makes Grass a key component of the AI data layer during the process of scaling to data set cleaning and preparation, establishing its foundational position in the field of AI.

Financing Background and Technical Features

The team behind Grass successfully completed a $3.5 million seed round financing, bringing the total financing amount to $4.5 million. This funding will be used to enhance Grass's technical infrastructure, expand the node network, and improve the data verification process.

Grass is a decentralized bandwidth market where users can help AI labs obtain the network data needed to train models by selling their idle internet connections. Grass utilizes users' IP addresses to sell excess bandwidth, bypassing many websites' restrictions on data center IP addresses. The entire process ensures user privacy and data security.

The core technology of Grass, Socrates, excels at collecting unstructured data from the web and structuring it, making Grass an AI data warehouse that provides the data needed for model training for other AI systems.

Market Potential and Advantages

Grass is built on Solana, leveraging its high throughput advantages. To address the problem of tracing each fetch task on L1 storage, Grass has constructed a rollup that uses ZK processors to batch process the tracing proofs before publishing them to Solana.

Grass's Web3-first approach offers several advantages over centralized residential agent providers:

1. Fair distribution of AI-generated value
2. Reduce the cost of bundled code for payment application developers
3. Users directly own and operate the network

Other advantages of Grass include:

• Nodes are widely distributed, covering over 190 countries
• A powerful technical foundation that processes 1 million network requests per second.
• Long-term project lifecycle and robust product roadmap
• Gaining support from well-known investment institutions
• Low entry barrier, easy to get started

Grass not only supports the training of traditional AI but also promotes the development of decentralized and open-source AI by creating alternative pathways to access network data. This initiative aims to prevent a few companies from monopolizing the development of AI, ensuring that everyone can fairly access and utilize public network data.

Conclusion

Grass is committed to correcting the mistakes of the Web 2.0 era and promoting the development of Web3 values. By participating in Grass, users can not only receive rewards but also contribute to building a fairer and more just world. Grass's innovation and unique positioning give it an important place in the AI and Web3 fields, with the potential to become an industry leader.